Split (1)

train · 58.2k rows

datasetId stringlengths 2 117	author stringlengths 2 42 ⌀	last_modified timestamp[us, tz=UTC]	downloads int64 0 9.36M	likes int64 0 3.89k	tags list	task_categories list	createdAt timestamp[us, tz=UTC]	card stringlengths 19 1.01M	embedding list
open-llm-leaderboard/details_LeoLM__leo-hessianai-7b	open-llm-leaderboard	2023-10-25T10:03:36Z	258	0	[ "region:us" ]	null	2023-10-08T17:16:38Z	--- pretty_name: Evaluation run of LeoLM/leo-hessianai-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_LeoLM__leo-hessianai-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T10:03:23.884304](https://huggingface.co/datasets/open-llm-leaderboard/details_LeoLM__leo-hessianai-7b/blob/main/results_2023-10-25T10-03-23.884304.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0009437919463087249,\n\ \ \"em_stderr\": 0.0003144653119413205,\n \"f1\": 0.056075922818791854,\n\ \ \"f1_stderr\": 0.0013232326016856207,\n \"acc\": 0.38874610827245293,\n\ \ \"acc_stderr\": 0.009469282540407879\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0009437919463087249,\n \"em_stderr\": 0.0003144653119413205,\n\ \ \"f1\": 0.056075922818791854,\n \"f1_stderr\": 0.0013232326016856207\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.056103108415466264,\n \ \ \"acc_stderr\": 0.006338668431321877\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7213891081294396,\n \"acc_stderr\": 0.01259989664949388\n\ \ }\n}\n```" repo_url: https://huggingface.co/LeoLM/leo-hessianai-7b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|arc:challenge\|25_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-08T17-16-14.181420.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T10_03_23.884304 path: - '/details_harness\|drop\|3_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-25T10-03-23.884304.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T10_03_23.884304 path: - '/details_harness\|gsm8k\|5_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-25T10-03-23.884304.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hellaswag\|10_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T17-16-14.181420.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T17_16_14.181420 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T17-16-14.181420.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T10_03_23.884304 path: - '/details_harness\|winogrande\|5_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-25T10-03-23.884304.parquet' - config_name: results data_files: - split: 2023_10_08T17_16_14.181420 path: - results_2023-10-08T17-16-14.181420.parquet - split: 2023_10_25T10_03_23.884304 path: - results_2023-10-25T10-03-23.884304.parquet - split: latest path: - results_2023-10-25T10-03-23.884304.parquet --- # Dataset Card for Evaluation run of LeoLM/leo-hessianai-7b ## Dataset Description - Homepage: - Repository: https://huggingface.co/LeoLM/leo-hessianai-7b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_LeoLM__leo-hessianai-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T10:03:23.884304](https://huggingface.co/datasets/open-llm-leaderboard/details_LeoLM__leo-hessianai-7b/blob/main/results_2023-10-25T10-03-23.884304.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0009437919463087249, "em_stderr": 0.0003144653119413205, "f1": 0.056075922818791854, "f1_stderr": 0.0013232326016856207, "acc": 0.38874610827245293, "acc_stderr": 0.009469282540407879 }, "harness\|drop\|3": { "em": 0.0009437919463087249, "em_stderr": 0.0003144653119413205, "f1": 0.056075922818791854, "f1_stderr": 0.0013232326016856207 }, "harness\|gsm8k\|5": { "acc": 0.056103108415466264, "acc_stderr": 0.006338668431321877 }, "harness\|winogrande\|5": { "acc": 0.7213891081294396, "acc_stderr": 0.01259989664949388 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.4394943416118622, -0.6048251390457153, 0.10013925284147263, 0.27560409903526306, -0.15673163533210754, 0.07316058874130249, -0.384801983833313, -0.25879448652267456, 0.4246799945831299, 0.4907771348953247, -0.7025391459465027, -0.9231427907943726, -0.6401982307434082, 0.19419103860855103, -0.1714811474084854, 1.232085943222046, -0.19010630249977112, -0.0693691298365593, 0.11504742503166199, -0.2850026786327362, -0.23396369814872742, -0.347573459148407, -0.5401130318641663, 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open-llm-leaderboard/details_01-ai__Yi-34B	open-llm-leaderboard	2023-12-01T14:52:34Z	258	3	[ "region:us" ]	null	2023-11-02T14:49:36Z	--- pretty_name: Evaluation run of 01-ai/Yi-34B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [01-ai/Yi-34B](https://huggingface.co/01-ai/Yi-34B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_01-ai__Yi-34B_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-08T19:46:38.378007](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-34B_public/blob/main/results_2023-11-08T19-46-38.378007.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.6081166107382551,\n\ \ \"em_stderr\": 0.004999326629880105,\n \"f1\": 0.6419882550335565,\n\ \ \"f1_stderr\": 0.004748239351156368,\n \"acc\": 0.6683760448499347,\n\ \ \"acc_stderr\": 0.012160441706531726\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.6081166107382551,\n \"em_stderr\": 0.004999326629880105,\n\ \ \"f1\": 0.6419882550335565,\n \"f1_stderr\": 0.004748239351156368\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.5064442759666414,\n \ \ \"acc_stderr\": 0.013771340765699767\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8303078137332282,\n \"acc_stderr\": 0.010549542647363686\n\ \ }\n}\n```" repo_url: https://huggingface.co/01-ai/Yi-34B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_drop_3 data_files: - split: 2023_11_08T19_46_38.378007 path: - '/details_harness\|drop\|3_2023-11-08T19-46-38.378007.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-08T19-46-38.378007.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_08T19_46_38.378007 path: - '/details_harness\|gsm8k\|5_2023-11-08T19-46-38.378007.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-08T19-46-38.378007.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_08T19_46_38.378007 path: - '/details_harness\|winogrande\|5_2023-11-08T19-46-38.378007.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-08T19-46-38.378007.parquet' - config_name: results data_files: - split: 2023_11_08T19_46_38.378007 path: - results_2023-11-08T19-46-38.378007.parquet - split: latest path: - results_2023-11-08T19-46-38.378007.parquet --- # Dataset Card for Evaluation run of 01-ai/Yi-34B ## Dataset Description - Homepage: - Repository: https://huggingface.co/01-ai/Yi-34B - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [01-ai/Yi-34B](https://huggingface.co/01-ai/Yi-34B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_01-ai__Yi-34B_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-08T19:46:38.378007](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-34B_public/blob/main/results_2023-11-08T19-46-38.378007.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.6081166107382551, "em_stderr": 0.004999326629880105, "f1": 0.6419882550335565, "f1_stderr": 0.004748239351156368, "acc": 0.6683760448499347, "acc_stderr": 0.012160441706531726 }, "harness\|drop\|3": { "em": 0.6081166107382551, "em_stderr": 0.004999326629880105, "f1": 0.6419882550335565, "f1_stderr": 0.004748239351156368 }, "harness\|gsm8k\|5": { "acc": 0.5064442759666414, "acc_stderr": 0.013771340765699767 }, "harness\|winogrande\|5": { "acc": 0.8303078137332282, "acc_stderr": 0.010549542647363686 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.44488072395324707, -0.6534472107887268, 0.2042730748653412, 0.24979785084724426, -0.12729641795158386, 0.07315274327993393, -0.3182014524936676, -0.20884990692138672, 0.36671486496925354, 0.538284957408905, -0.7756656408309937, -0.9645205736160278, -0.6217008829116821, 0.14153295755386353, -0.15936027467250824, 1.1751494407653809, -0.23279139399528503, -0.2327272742986679, 0.03060055896639824, -0.33844560384750366, -0.32088449597358704, -0.35573694109916687, -0.5513032674789429, 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bigheiniuJ/JimmyLuAugRestChat	bigheiniuJ	2023-11-09T16:12:58Z	258	0	[ "region:us" ]	null	2023-11-09T16:12:57Z	--- dataset_info: features: - name: output dtype: string - name: input dtype: string - name: seed dtype: string - name: split dtype: string - name: task dtype: string - name: options sequence: string - name: id dtype: int64 - name: aug_type dtype: string - name: aug_time dtype: int64 splits: - name: train num_bytes: 71287951 num_examples: 143531 download_size: 11818939 dataset_size: 71287951 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "JimmyLuAugRestChat" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.5147848129272461, -0.42461955547332764, 0.1087317243218422, 0.1744530349969864, -0.1671866625547409, 0.25791752338409424, 0.2087937742471695, -0.30857011675834656, 1.2045409679412842, 0.4300641119480133, -0.9361323118209839, 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sanskrit_classic	null	2022-11-03T16:07:56Z	257	2	[ "task_categories:text-generation", "task_categories:fill-mask", "task_ids:language-modeling", "task_ids:masked-language-modeling", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:100K<n<1M", "source_datasets:original", "language:sa", "license:other", "region:us" ]	[ "text-generation", "fill-mask" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - sa license: - other multilinguality: - monolingual size_categories: - 100K<n<1M source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: null pretty_name: SanskritClassic dataset_info: features: - name: text dtype: string config_name: combined splits: - name: train num_bytes: 40299787 num_examples: 342033 download_size: 7258904 dataset_size: 40299787 --- # Dataset Card for [Dataset Name] ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage:[sanskrit_classic](https://github.com/parmarsuraj99/hf_datasets/tree/master/sanskrit_classic) - Repository:[GitHub](https://github.com/parmarsuraj99/hf_datasets/tree/master/sanskrit_classic) - Paper:N/A - Leaderboard:N/A - Point of Contact:[parmarsuraj99]([email protected]) ### Dataset Summary A collection of classical sanskrit texts ### Supported Tasks and Leaderboards Language modeling ### Languages Sanskrit ## Dataset Structure ### Data Instances {'text': 'मा कर्मफलहेतुर्भूर्मा ते सङ्गोऽस्त्वकर्मणि॥'} ### Data Fields `text`: a line ### Data Splits \| \| Train \| \|-------------------\|--------\| \| n_instances \| 342033 \| ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information ``` @Misc{johnsonetal2014, author = {Johnson, Kyle P. and Patrick Burns and John Stewart and Todd Cook}, title = {CLTK: The Classical Language Toolkit}, url = {https://github.com/cltk/cltk}, year = {2014--2020}, } ``` ### Contributions Thanks to [@parmarsuraj99](https://github.com/parmarsuraj99) for adding this dataset.	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NYTK/HuRC	NYTK	2022-07-07T13:03:49Z	257	1	[ "task_categories:question-answering", "task_ids:extractive-qa", "task_ids:abstractive-qa", "annotations_creators:crowdsourced", "language_creators:found", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:extended\|other", "language:hu", "license:cc-by-4.0", "region:us" ]	[ "question-answering" ]	2022-03-02T23:29:22Z	--- YAML tags: annotations_creators: - crowdsourced language_creators: - found - expert-generated language: - hu license: - cc-by-4.0 multilinguality: - monolingual pretty_name: HuRC size_categories: - unknown source_datasets: - extended\|other task_categories: - question-answering task_ids: - extractive-qa - abstractive-qa --- # Dataset Card for HuRC ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: [HuRC dataset](https://github.com/nytud/HuRC) - Paper: - Leaderboard: - Point of Contact: [lnnoemi](mailto:[email protected]) ### Dataset Summary This is the dataset card for the Hungarian Corpus for Reading Comprehension with Commonsense Reasoning (HuRC), which is also part of the Hungarian Language Understanding Evaluation Benchmark Kit HuLU. The dataset contains 80 614 instances. Each instance is composed of a lead, a passage and a cloze-style query with a masked entity. The task is to select the named entity that is being masked in the query. The data was automatically collected from the online news of Népszabadság online (nol.hu). ### Languages The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU. ## Dataset Structure ### Data Instances For each instance, there is an id, a lead, a passage, a query and a MASK. An example: ``` { "id": "1", "lead": ["A Közigazgatási és Igazságügyi Minisztérium szerint a Bárka Színház esetében felmerült a felelőtlen gazdálkodás gyanúja, egyes értesülések szerint pedig ebben \"a színház igazgatójának és gazdasági vezetőjének felelőssége is felmerül\""], "passage": [ "A teátrumnak Navracsics Tibor közigazgatási és igazságügyi miniszterhez és Kocsis Máté VIII. kerületi polgármesterhez", "reagálva a tárca azt írta, hogy a felelőtlen gazdálkodás gyanújában \"egyes értesülések szerint a színház igazgatójának és gazdasági vezetőjének felelőssége is felmerül\". A KIM \"éppen ezért nagyon várja az Állami Számvevőszék készülő jelentését, hogy tiszta képet kaphasson a színház működéséről\".", "A minisztérium hangsúlyozta, hogy az elmúlt évben is mindent elkövetett azért, hogy a Bárka Színház \"valós, rangos művészeti térként\" működjön, és a továbbiakban is ez a szándéka, de jelenleg a társulat működtetését a minisztérium fenntartói támogatás formájában jogszerűen még nem tudja megoldani.", "A teátrum az átadás-átvétel elhúzódásának okát keresve tette közzé nyílt levelét, amelyben elmaradó fizetésekre, előadásokra és bemutatókra hívta fel a figyelmet, és jelezte, hogy várja a helyzet megoldását.", "A színház átadás-átvétele jelenleg zajlik, a folyamat végeztével a Bárka a józsefvárosi önkormányzattól állami tulajdonba, a tervek szerint a Közigazgatási és Igazságügyi Minisztérium fenntartásába kerül." ], "query": "A KIM 2014-es költségvetésében szerepel a Bárka Színház, de amíg nem a minisztérium a [MASK] fenntartója, addig ez a költségvetési keret nem nyitható meg.", "MASK": "Bárka", } ``` ### Data Fields - id: unique id of the instances; - lead: a short summary of the article as it was extracted from the source texts; - passage: 3-6 paragraphs of texts as the body of the article; - query: the last paragraph of an article, some kind of summary or conclusion, with a named entity masked (with [MASK]) in it; - MASK: the masked named entity. ### Data Splits HuRC has 3 splits: train, validation and test. \| Dataset split \| Number of instances in the split \| Proportion of the split \|---------------\|----------------------------------\| ---------\| \| train \| 64614 \| 80%\| \| validation \| 8000 \|10%\| \| test \| 8000 \|10%\| The test data is distributed without the MASK fields. To evaluate your model, please [contact us](mailto:[email protected]), or check [HuLU's website](hulu.nlp.nytud.hu) for an automatic evaluation (this feature is under construction at the moment). ## Dataset Creation ### Source Data #### Initial Data Collection and Normalization To produce the Hungarian material, we used the daily articles from Népszabadság Online which had titles and summaries as well. We selected 3-6 paragraphs from each article from the ones which contain proper nouns both in the main part and the summary as well. We trained a NER model using huBERT (Nemeskey 2021) for recognizing proper nouns. NerKor (Simon és Vadász 2021) and Huggingface’s token-level classification library were used to fine-tune the model. Our model achieved an F-score of 90.18 on the test material. As a final step, we found pairs of proper names which are present both in the main article and the summary. Multiple articles contained more than one such pairs so we used those more than once. This resulted in a database of 88655 instances (from 49782 articles). The quantitative properties of our corpus are as follows: Number of articles: 88655 Number of different articles (type): 49782 Token: 27703631 Type: 1115.260 Average length of text (token): 249.42 (median: 229) Average question length (token): 63.07 (median: 56). We fine-tuned the corpus by hand. One annotator per 100 unit checked and validated the dataset for which we provided our own demo interface. Automatic masking and the previous occurrence of the entity was checked. This resulted in a database of 80 614 validated entries. ## Additional Information ### Licensing Information HuRC is released under the cc-by-4.0 license. ### Citation Information If you use this resource or any part of its documentation, please refer to: Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. XVIII. Magyar Számítógépes Nyelvészeti Konferencia. (in press) ``` @inproceedings{ligetinagy2022hulu, title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából}, author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.}, booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia}, year={2022} } ``` ### Contributions Thanks to [lnnoemi](https://github.com/lnnoemi) for adding this dataset.	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huggingartists/dj-artem-artemov	huggingartists	2022-10-25T09:27:49Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/dj-artem-artemov" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.105061 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/7499a229de60cdfb23ce61f5924c401d.416x416x1.png')"> </div> </div> <a href="https://huggingface.co/huggingartists/dj-artem-artemov"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">DJ Artem Artemov</div> <a href="https://genius.com/artists/dj-artem-artemov"> <div style="text-align: center; font-size: 14px;">@dj-artem-artemov</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/dj-artem-artemov). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/dj-artem-artemov") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|56\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/dj-artem-artemov") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/kesha	huggingartists	2022-10-25T09:33:19Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/kesha" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.792077 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/cc47affdd77273058c17a9df5f5b8a0c.400x400x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/kesha"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Kesha</div> <a href="https://genius.com/artists/kesha"> <div style="text-align: center; font-size: 14px;">@kesha</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/kesha). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/kesha") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|450\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/kesha") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/king-krule	huggingartists	2022-10-25T09:33:25Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/king-krule" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.153776 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/6effd9dd0951f41966e769504644a338.675x675x2.gif')"> </div> </div> <a href="https://huggingface.co/huggingartists/king-krule"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">King Krule</div> <a href="https://genius.com/artists/king-krule"> <div style="text-align: center; font-size: 14px;">@king-krule</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/king-krule). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/king-krule") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|111\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/king-krule") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone	huggingartists	2022-10-25T09:34:14Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.032823 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://assets.genius.com/images/default_avatar_300.png?1631203230')"> </div> </div> <a href="https://huggingface.co/huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Krept & Konan, Bugzy Malone, SL, Morisson, Abra Cadabra, RV & Snap Capone</div> <a href="https://genius.com/artists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone"> <div style="text-align: center; font-size: 14px;">@krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|1\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/krept-and-konan-bugzy-malone-sl-morisson-abra-cadabra-rv-and-snap-capone") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/lil-peep	huggingartists	2022-10-25T09:35:00Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/lil-peep" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.792328 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/919c7ba130d3861740cbe7fbd7f83c59.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/lil-peep"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Lil Peep</div> <a href="https://genius.com/artists/lil-peep"> <div style="text-align: center; font-size: 14px;">@lil-peep</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/lil-peep). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/lil-peep") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|547\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/lil-peep") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/little-big	huggingartists	2022-10-25T09:35:26Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/little-big" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.151956 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/32e68b9d7093213fd4c06984ee3ff6aa.900x900x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/little-big"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Little Big</div> <a href="https://genius.com/artists/little-big"> <div style="text-align: center; font-size: 14px;">@little-big</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/little-big). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/little-big") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|86\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/little-big") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/mating-ritual	huggingartists	2022-10-25T09:37:47Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/mating-ritual" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.158744 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/2a5b556758315c192c7b1e6e86634c7d.600x600x1.png')"> </div> </div> <a href="https://huggingface.co/huggingartists/mating-ritual"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Mating Ritual</div> <a href="https://genius.com/artists/mating-ritual"> <div style="text-align: center; font-size: 14px;">@mating-ritual</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/mating-ritual). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/mating-ritual") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|61\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/mating-ritual") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/totpoc	huggingartists	2022-10-25T09:48:43Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/totpoc" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.245029 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/ea3dc2eb7b35254ae3764df28bc02500.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/totpoc"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">totpoc</div> <a href="https://genius.com/artists/totpoc"> <div style="text-align: center; font-size: 14px;">@totpoc</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/totpoc). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/totpoc") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|78\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/totpoc") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/upsahl	huggingartists	2022-10-25T09:49:14Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/upsahl" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.168635 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/e0fa9b5bdd037ab75031dd7372d05cd6.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/upsahl"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">UPSAHL</div> <a href="https://genius.com/artists/upsahl"> <div style="text-align: center; font-size: 14px;">@upsahl</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/upsahl). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/upsahl") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|107\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/upsahl") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/veggietales	huggingartists	2022-10-25T09:49:47Z	257	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/veggietales" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.220878 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/d14c9e27b39f0e250784a2dce037a03d.720x720x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/veggietales"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">VeggieTales</div> <a href="https://genius.com/artists/veggietales"> <div style="text-align: center; font-size: 14px;">@veggietales</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/veggietales). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/veggietales") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|163\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/veggietales") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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LeoLM/HellaSwag_de	LeoLM	2023-08-29T13:31:56Z	257	0	[ "region:us" ]	null	2023-08-10T13:49:51Z	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: ind dtype: int64 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string - name: activity_label_de dtype: string - name: ctx_de dtype: string - name: endings_de sequence: string - name: translation_de dtype: string splits: - name: train num_bytes: 1592717 num_examples: 1000 - name: validation num_bytes: 31417275 num_examples: 10042 download_size: 18521030 dataset_size: 33009992 --- # Dataset Card for "hellaswag_de"	[ -0.5371738076210022, -0.1567337065935135, -0.014258136972784996, 0.25007209181785583, -1.1034979820251465, 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open-llm-leaderboard/details_synapsoft__Llama-2-7b-hf-flan2022-1.2M	open-llm-leaderboard	2023-10-13T06:59:47Z	257	0	[ "region:us" ]	null	2023-08-29T11:39:05Z	--- pretty_name: Evaluation run of synapsoft/Llama-2-7b-hf-flan2022-1.2M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [synapsoft/Llama-2-7b-hf-flan2022-1.2M](https://huggingface.co/synapsoft/Llama-2-7b-hf-flan2022-1.2M)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_synapsoft__Llama-2-7b-hf-flan2022-1.2M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-13T06:59:34.296378](https://huggingface.co/datasets/open-llm-leaderboard/details_synapsoft__Llama-2-7b-hf-flan2022-1.2M/blob/main/results_2023-10-13T06-59-34.296378.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.25870385906040266,\n\ \ \"em_stderr\": 0.004484736946763185,\n \"f1\": 0.2965908137583894,\n\ \ \"f1_stderr\": 0.004480084563201026,\n \"acc\": 0.40002920104621126,\n\ \ \"acc_stderr\": 0.008888005892783395\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.25870385906040266,\n \"em_stderr\": 0.004484736946763185,\n\ \ \"f1\": 0.2965908137583894,\n \"f1_stderr\": 0.004480084563201026\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.04473085670962851,\n \ \ \"acc_stderr\": 0.005693886131407052\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.755327545382794,\n \"acc_stderr\": 0.012082125654159738\n\ \ }\n}\n```" repo_url: https://huggingface.co/synapsoft/Llama-2-7b-hf-flan2022-1.2M leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|arc:challenge\|25_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-29T11:38:40.621041.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_13T06_59_34.296378 path: - '/details_harness\|drop\|3_2023-10-13T06-59-34.296378.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-13T06-59-34.296378.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_13T06_59_34.296378 path: - '/details_harness\|gsm8k\|5_2023-10-13T06-59-34.296378.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-13T06-59-34.296378.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hellaswag\|10_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T11:38:40.621041.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T11:38:40.621041.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_29T11_38_40.621041 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-29T11:38:40.621041.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-29T11:38:40.621041.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_13T06_59_34.296378 path: - '/details_harness\|winogrande\|5_2023-10-13T06-59-34.296378.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-13T06-59-34.296378.parquet' - config_name: results data_files: - split: 2023_08_29T11_38_40.621041 path: - results_2023-08-29T11:38:40.621041.parquet - split: 2023_10_13T06_59_34.296378 path: - results_2023-10-13T06-59-34.296378.parquet - split: latest path: - results_2023-10-13T06-59-34.296378.parquet --- # Dataset Card for Evaluation run of synapsoft/Llama-2-7b-hf-flan2022-1.2M ## Dataset Description - Homepage: - Repository: https://huggingface.co/synapsoft/Llama-2-7b-hf-flan2022-1.2M - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [synapsoft/Llama-2-7b-hf-flan2022-1.2M](https://huggingface.co/synapsoft/Llama-2-7b-hf-flan2022-1.2M) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_synapsoft__Llama-2-7b-hf-flan2022-1.2M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-13T06:59:34.296378](https://huggingface.co/datasets/open-llm-leaderboard/details_synapsoft__Llama-2-7b-hf-flan2022-1.2M/blob/main/results_2023-10-13T06-59-34.296378.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.25870385906040266, "em_stderr": 0.004484736946763185, "f1": 0.2965908137583894, "f1_stderr": 0.004480084563201026, "acc": 0.40002920104621126, "acc_stderr": 0.008888005892783395 }, "harness\|drop\|3": { "em": 0.25870385906040266, "em_stderr": 0.004484736946763185, "f1": 0.2965908137583894, "f1_stderr": 0.004480084563201026 }, "harness\|gsm8k\|5": { "acc": 0.04473085670962851, "acc_stderr": 0.005693886131407052 }, "harness\|winogrande\|5": { "acc": 0.755327545382794, "acc_stderr": 0.012082125654159738 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.38139232993125916, -0.6521210670471191, 0.25539618730545044, 0.2648507356643677, -0.15154437720775604, 0.19903424382209778, -0.40520694851875305, -0.29340818524360657, 0.5402360558509827, 0.4846702516078949, -0.6814709305763245, -0.851146399974823, -0.7168813347816467, 0.16703137755393982, -0.2087775319814682, 1.1378244161605835, -0.2450672835111618, -0.2606793940067291, 0.03580616042017937, -0.30618593096733093, -0.3279477059841156, -0.44909384846687317, -0.5311623215675354, 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open-llm-leaderboard/details_Norquinal__llama-2-7b-claude-chat	open-llm-leaderboard	2023-09-17T21:50:30Z	257	0	[ "region:us" ]	null	2023-08-30T02:05:45Z	--- pretty_name: Evaluation run of Norquinal/llama-2-7b-claude-chat dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Norquinal/llama-2-7b-claude-chat](https://huggingface.co/Norquinal/llama-2-7b-claude-chat)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Norquinal__llama-2-7b-claude-chat\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T21:50:18.954049](https://huggingface.co/datasets/open-llm-leaderboard/details_Norquinal__llama-2-7b-claude-chat/blob/main/results_2023-09-17T21-50-18.954049.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0016778523489932886,\n\ \ \"em_stderr\": 0.00041913301788269335,\n \"f1\": 0.0588590604026846,\n\ \ \"f1_stderr\": 0.0013399207626085948,\n \"acc\": 0.4131723645607008,\n\ \ \"acc_stderr\": 0.009771744871869251\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0016778523489932886,\n \"em_stderr\": 0.00041913301788269335,\n\ \ \"f1\": 0.0588590604026846,\n \"f1_stderr\": 0.0013399207626085948\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.07733131159969674,\n \ \ \"acc_stderr\": 0.00735771352322235\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7490134175217048,\n \"acc_stderr\": 0.012185776220516153\n\ \ }\n}\n```" repo_url: https://huggingface.co/Norquinal/llama-2-7b-claude-chat leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|arc:challenge\|25_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-30T02:05:21.068223.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T21_50_18.954049 path: - '/details_harness\|drop\|3_2023-09-17T21-50-18.954049.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T21-50-18.954049.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T21_50_18.954049 path: - '/details_harness\|gsm8k\|5_2023-09-17T21-50-18.954049.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T21-50-18.954049.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hellaswag\|10_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T02:05:21.068223.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T02:05:21.068223.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_30T02_05_21.068223 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-30T02:05:21.068223.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-30T02:05:21.068223.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T21_50_18.954049 path: - '/details_harness\|winogrande\|5_2023-09-17T21-50-18.954049.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T21-50-18.954049.parquet' - config_name: results data_files: - split: 2023_08_30T02_05_21.068223 path: - results_2023-08-30T02:05:21.068223.parquet - split: 2023_09_17T21_50_18.954049 path: - results_2023-09-17T21-50-18.954049.parquet - split: latest path: - results_2023-09-17T21-50-18.954049.parquet --- # Dataset Card for Evaluation run of Norquinal/llama-2-7b-claude-chat ## Dataset Description - Homepage: - Repository: https://huggingface.co/Norquinal/llama-2-7b-claude-chat - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [Norquinal/llama-2-7b-claude-chat](https://huggingface.co/Norquinal/llama-2-7b-claude-chat) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Norquinal__llama-2-7b-claude-chat", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T21:50:18.954049](https://huggingface.co/datasets/open-llm-leaderboard/details_Norquinal__llama-2-7b-claude-chat/blob/main/results_2023-09-17T21-50-18.954049.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0016778523489932886, "em_stderr": 0.00041913301788269335, "f1": 0.0588590604026846, "f1_stderr": 0.0013399207626085948, "acc": 0.4131723645607008, "acc_stderr": 0.009771744871869251 }, "harness\|drop\|3": { "em": 0.0016778523489932886, "em_stderr": 0.00041913301788269335, "f1": 0.0588590604026846, "f1_stderr": 0.0013399207626085948 }, "harness\|gsm8k\|5": { "acc": 0.07733131159969674, "acc_stderr": 0.00735771352322235 }, "harness\|winogrande\|5": { "acc": 0.7490134175217048, "acc_stderr": 0.012185776220516153 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.30892908573150635, -0.6988357305526733, 0.1421414464712143, 0.30200886726379395, -0.16932040452957153, 0.14411981403827667, -0.34372827410697937, -0.2552763819694519, 0.46865877509117126, 0.6320120096206665, -0.707230269908905, -0.9873259663581848, -0.6611238718032837, 0.14122357964515686, -0.2714284062385559, 1.096651315689087, -0.21199041604995728, -0.23006728291511536, 0.09596562385559082, -0.2880576252937317, -0.3358292579650879, -0.44909173250198364, -0.5739153623580933, 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open-llm-leaderboard/details_KnutJaegersberg__megatron-gpt2-345m-evol_instruct_v2	open-llm-leaderboard	2023-12-01T14:06:18Z	257	0	[ "region:us" ]	null	2023-09-11T15:25:39Z	--- pretty_name: Evaluation run of KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2](https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_KnutJaegersberg__megatron-gpt2-345m-evol_instruct_v2_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-06T21:23:09.566813](https://huggingface.co/datasets/open-llm-leaderboard/details_KnutJaegersberg__megatron-gpt2-345m-evol_instruct_v2_public/blob/main/results_2023-11-06T21-23-09.566813.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0010486577181208054,\n\ \ \"em_stderr\": 0.00033145814652191626,\n \"f1\": 0.045425755033557384,\n\ \ \"f1_stderr\": 0.0011926647330667845,\n \"acc\": 0.2616416732438832,\n\ \ \"acc_stderr\": 0.007018620654786821\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0010486577181208054,\n \"em_stderr\": 0.00033145814652191626,\n\ \ \"f1\": 0.045425755033557384,\n \"f1_stderr\": 0.0011926647330667845\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5232833464877664,\n\ \ \"acc_stderr\": 0.014037241309573642\n }\n}\n```" repo_url: https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_drop_3 data_files: - split: 2023_11_04T22_13_52.567889 path: - '/details_harness\|drop\|3_2023-11-04T22-13-52.567889.parquet' - split: 2023_11_06T21_23_09.566813 path: - '/details_harness\|drop\|3_2023-11-06T21-23-09.566813.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-06T21-23-09.566813.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_04T22_13_52.567889 path: - '/details_harness\|gsm8k\|5_2023-11-04T22-13-52.567889.parquet' - split: 2023_11_06T21_23_09.566813 path: - '/details_harness\|gsm8k\|5_2023-11-06T21-23-09.566813.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-06T21-23-09.566813.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_04T22_13_52.567889 path: - '/details_harness\|winogrande\|5_2023-11-04T22-13-52.567889.parquet' - split: 2023_11_06T21_23_09.566813 path: - '/details_harness\|winogrande\|5_2023-11-06T21-23-09.566813.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-06T21-23-09.566813.parquet' - config_name: results data_files: - split: 2023_11_04T22_13_52.567889 path: - results_2023-11-04T22-13-52.567889.parquet - split: 2023_11_06T21_23_09.566813 path: - results_2023-11-06T21-23-09.566813.parquet - split: latest path: - results_2023-11-06T21-23-09.566813.parquet --- # Dataset Card for Evaluation run of KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2 ## Dataset Description - Homepage: - Repository: https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2](https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_KnutJaegersberg__megatron-gpt2-345m-evol_instruct_v2_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-06T21:23:09.566813](https://huggingface.co/datasets/open-llm-leaderboard/details_KnutJaegersberg__megatron-gpt2-345m-evol_instruct_v2_public/blob/main/results_2023-11-06T21-23-09.566813.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0010486577181208054, "em_stderr": 0.00033145814652191626, "f1": 0.045425755033557384, "f1_stderr": 0.0011926647330667845, "acc": 0.2616416732438832, "acc_stderr": 0.007018620654786821 }, "harness\|drop\|3": { "em": 0.0010486577181208054, "em_stderr": 0.00033145814652191626, "f1": 0.045425755033557384, "f1_stderr": 0.0011926647330667845 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5232833464877664, "acc_stderr": 0.014037241309573642 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.500562310218811, -0.6337292194366455, 0.27709972858428955, 0.05101494491100311, -0.18452206254005432, 0.059945765882730484, -0.44920435547828674, -0.1805589497089386, 0.32414430379867554, 0.5342333912849426, -0.5884941816329956, -0.8476720452308655, -0.703324019908905, 0.17484667897224426, -0.08100935071706772, 1.176840901374817, -0.2551742494106293, -0.1700821816921234, 0.04316742718219757, -0.15313363075256348, -0.2961312532424927, -0.4558730125427246, -0.5104628801345825, 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open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k	open-llm-leaderboard	2023-09-13T10:13:59Z	257	0	[ "region:us" ]	null	2023-09-13T10:12:58Z	--- pretty_name: Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2927085297989137,\n\ \ \"acc_stderr\": 0.03275517148401362,\n \"acc_norm\": 0.29622047886660385,\n\ \ \"acc_norm_stderr\": 0.032746678820457335,\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.46928327645051193,\n \"acc_stderr\": 0.014583792546304038,\n\ \ \"acc_norm\": 0.4974402730375427,\n \"acc_norm_stderr\": 0.014611199329843777\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5497908783110934,\n\ \ \"acc_stderr\": 0.004964979120927565,\n \"acc_norm\": 0.7288388767177854,\n\ \ \"acc_norm_stderr\": 0.004436505187567003\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2222222222222222,\n\ \ \"acc_stderr\": 0.035914440841969694,\n \"acc_norm\": 0.2222222222222222,\n\ \ \"acc_norm_stderr\": 0.035914440841969694\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.2894736842105263,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.2894736842105263,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.25660377358490566,\n \"acc_stderr\": 0.02688064788905197,\n\ \ \"acc_norm\": 0.25660377358490566,\n \"acc_norm_stderr\": 0.02688064788905197\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.24305555555555555,\n\ \ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.24305555555555555,\n\ \ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165085,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165085\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.20809248554913296,\n\ \ \"acc_stderr\": 0.030952890217749895,\n \"acc_norm\": 0.20809248554913296,\n\ \ \"acc_norm_stderr\": 0.030952890217749895\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.37,\n\ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.029513196625539355,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.029513196625539355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.03999423879281336,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.03999423879281336\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2689655172413793,\n \"acc_stderr\": 0.03695183311650232,\n\ \ \"acc_norm\": 0.2689655172413793,\n \"acc_norm_stderr\": 0.03695183311650232\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948365,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948365\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.20634920634920634,\n\ \ \"acc_stderr\": 0.0361960452412425,\n \"acc_norm\": 0.20634920634920634,\n\ \ \"acc_norm_stderr\": 0.0361960452412425\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.04093601807403326,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.04093601807403326\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.24838709677419354,\n\ \ \"acc_stderr\": 0.02458002892148101,\n \"acc_norm\": 0.24838709677419354,\n\ \ \"acc_norm_stderr\": 0.02458002892148101\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.1921182266009852,\n \"acc_stderr\": 0.02771931570961478,\n\ \ \"acc_norm\": 0.1921182266009852,\n \"acc_norm_stderr\": 0.02771931570961478\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206824,\n \"acc_norm\"\ : 0.29,\n \"acc_norm_stderr\": 0.045604802157206824\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.36363636363636365,\n \"acc_stderr\": 0.03756335775187896,\n\ \ \"acc_norm\": 0.36363636363636365,\n \"acc_norm_stderr\": 0.03756335775187896\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.2676767676767677,\n \"acc_stderr\": 0.03154449888270285,\n \"\ acc_norm\": 0.2676767676767677,\n \"acc_norm_stderr\": 0.03154449888270285\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.2538860103626943,\n \"acc_stderr\": 0.03141024780565319,\n\ \ \"acc_norm\": 0.2538860103626943,\n \"acc_norm_stderr\": 0.03141024780565319\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.24358974358974358,\n \"acc_stderr\": 0.02176373368417392,\n\ \ \"acc_norm\": 0.24358974358974358,\n \"acc_norm_stderr\": 0.02176373368417392\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.23333333333333334,\n \"acc_stderr\": 0.02578787422095932,\n \ \ \"acc_norm\": 0.23333333333333334,\n \"acc_norm_stderr\": 0.02578787422095932\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.23109243697478993,\n \"acc_stderr\": 0.027381406927868956,\n\ \ \"acc_norm\": 0.23109243697478993,\n \"acc_norm_stderr\": 0.027381406927868956\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.3155963302752294,\n \"acc_stderr\": 0.019926117513869662,\n \"\ acc_norm\": 0.3155963302752294,\n \"acc_norm_stderr\": 0.019926117513869662\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.2962962962962963,\n \"acc_stderr\": 0.031141447823536023,\n \"\ acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.031141447823536023\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.3333333333333333,\n \"acc_stderr\": 0.03308611113236435,\n \"\ acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.03308611113236435\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.3881856540084388,\n \"acc_stderr\": 0.0317229500433233,\n \ \ \"acc_norm\": 0.3881856540084388,\n \"acc_norm_stderr\": 0.0317229500433233\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.273542600896861,\n\ \ \"acc_stderr\": 0.029918586707798824,\n \"acc_norm\": 0.273542600896861,\n\ \ \"acc_norm_stderr\": 0.029918586707798824\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2748091603053435,\n \"acc_stderr\": 0.039153454088478354,\n\ \ \"acc_norm\": 0.2748091603053435,\n \"acc_norm_stderr\": 0.039153454088478354\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.4132231404958678,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.4132231404958678,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04557239513497751,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04557239513497751\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.2147239263803681,\n \"acc_stderr\": 0.03226219377286774,\n\ \ \"acc_norm\": 0.2147239263803681,\n \"acc_norm_stderr\": 0.03226219377286774\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.29464285714285715,\n\ \ \"acc_stderr\": 0.04327040932578729,\n \"acc_norm\": 0.29464285714285715,\n\ \ \"acc_norm_stderr\": 0.04327040932578729\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690878,\n\ \ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690878\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.3504273504273504,\n\ \ \"acc_stderr\": 0.03125610824421881,\n \"acc_norm\": 0.3504273504273504,\n\ \ \"acc_norm_stderr\": 0.03125610824421881\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.2988505747126437,\n\ \ \"acc_stderr\": 0.01636925681509314,\n \"acc_norm\": 0.2988505747126437,\n\ \ \"acc_norm_stderr\": 0.01636925681509314\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.30057803468208094,\n \"acc_stderr\": 0.024685316867257796,\n\ \ \"acc_norm\": 0.30057803468208094,\n \"acc_norm_stderr\": 0.024685316867257796\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.3300653594771242,\n \"acc_stderr\": 0.026925654653615686,\n\ \ \"acc_norm\": 0.3300653594771242,\n \"acc_norm_stderr\": 0.026925654653615686\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2733118971061093,\n\ \ \"acc_stderr\": 0.02531176597542612,\n \"acc_norm\": 0.2733118971061093,\n\ \ \"acc_norm_stderr\": 0.02531176597542612\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.3055555555555556,\n \"acc_stderr\": 0.025630824975621344,\n\ \ \"acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.025630824975621344\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.28368794326241137,\n \"acc_stderr\": 0.02689170942834396,\n \ \ \"acc_norm\": 0.28368794326241137,\n \"acc_norm_stderr\": 0.02689170942834396\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.28748370273794005,\n\ \ \"acc_stderr\": 0.011559337355708502,\n \"acc_norm\": 0.28748370273794005,\n\ \ \"acc_norm_stderr\": 0.011559337355708502\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.28104575163398693,\n \"acc_stderr\": 0.018185218954318075,\n \ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.018185218954318075\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.4163265306122449,\n \"acc_stderr\": 0.03155782816556165,\n\ \ \"acc_norm\": 0.4163265306122449,\n \"acc_norm_stderr\": 0.03155782816556165\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.34328358208955223,\n\ \ \"acc_stderr\": 0.03357379665433431,\n \"acc_norm\": 0.34328358208955223,\n\ \ \"acc_norm_stderr\": 0.03357379665433431\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.2710843373493976,\n\ \ \"acc_stderr\": 0.034605799075530276,\n \"acc_norm\": 0.2710843373493976,\n\ \ \"acc_norm_stderr\": 0.034605799075530276\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.39766081871345027,\n \"acc_stderr\": 0.0375363895576169,\n\ \ \"acc_norm\": 0.39766081871345027,\n \"acc_norm_stderr\": 0.0375363895576169\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n }\n}\n```" repo_url: https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|arc:challenge\|25_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hellaswag\|10_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T10-12-42.075501.parquet' - config_name: results data_files: - split: 2023_09_13T10_12_42.075501 path: - results_2023-09-13T10-12-42.075501.parquet - split: latest path: - results_2023-09-13T10-12-42.075501.parquet --- # Dataset Card for Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k ## Dataset Description - Homepage: - Repository: https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2927085297989137, "acc_stderr": 0.03275517148401362, "acc_norm": 0.29622047886660385, "acc_norm_stderr": 0.032746678820457335, "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 }, "harness\|arc:challenge\|25": { "acc": 0.46928327645051193, "acc_stderr": 0.014583792546304038, "acc_norm": 0.4974402730375427, "acc_norm_stderr": 0.014611199329843777 }, "harness\|hellaswag\|10": { "acc": 0.5497908783110934, "acc_stderr": 0.004964979120927565, "acc_norm": 0.7288388767177854, "acc_norm_stderr": 0.004436505187567003 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.035914440841969694, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.035914440841969694 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.2894736842105263, "acc_stderr": 0.03690677986137283, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.25660377358490566, "acc_stderr": 0.02688064788905197, "acc_norm": 0.25660377358490566, "acc_norm_stderr": 0.02688064788905197 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.24305555555555555, "acc_stderr": 0.0358687928008034, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.0358687928008034 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.23, "acc_stderr": 0.042295258468165085, "acc_norm": 0.23, "acc_norm_stderr": 0.042295258468165085 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749895, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749895 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.2851063829787234, "acc_stderr": 0.029513196625539355, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.029513196625539355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.03999423879281336, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.03999423879281336 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2689655172413793, "acc_stderr": 0.03695183311650232, "acc_norm": 0.2689655172413793, "acc_norm_stderr": 0.03695183311650232 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.20634920634920634, "acc_stderr": 0.0361960452412425, "acc_norm": 0.20634920634920634, "acc_norm_stderr": 0.0361960452412425 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.24838709677419354, "acc_stderr": 0.02458002892148101, "acc_norm": 0.24838709677419354, "acc_norm_stderr": 0.02458002892148101 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.1921182266009852, "acc_stderr": 0.02771931570961478, "acc_norm": 0.1921182266009852, "acc_norm_stderr": 0.02771931570961478 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206824, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206824 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.36363636363636365, "acc_stderr": 0.03756335775187896, "acc_norm": 0.36363636363636365, "acc_norm_stderr": 0.03756335775187896 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.2676767676767677, "acc_stderr": 0.03154449888270285, "acc_norm": 0.2676767676767677, "acc_norm_stderr": 0.03154449888270285 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.2538860103626943, "acc_stderr": 0.03141024780565319, "acc_norm": 0.2538860103626943, "acc_norm_stderr": 0.03141024780565319 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.24358974358974358, "acc_stderr": 0.02176373368417392, "acc_norm": 0.24358974358974358, "acc_norm_stderr": 0.02176373368417392 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.23333333333333334, "acc_stderr": 0.02578787422095932, "acc_norm": 0.23333333333333334, "acc_norm_stderr": 0.02578787422095932 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.23109243697478993, "acc_stderr": 0.027381406927868956, "acc_norm": 0.23109243697478993, "acc_norm_stderr": 0.027381406927868956 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.3155963302752294, "acc_stderr": 0.019926117513869662, "acc_norm": 0.3155963302752294, "acc_norm_stderr": 0.019926117513869662 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.2962962962962963, "acc_stderr": 0.031141447823536023, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.031141447823536023 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.03308611113236435, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.03308611113236435 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.3881856540084388, "acc_stderr": 0.0317229500433233, "acc_norm": 0.3881856540084388, "acc_norm_stderr": 0.0317229500433233 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.273542600896861, "acc_stderr": 0.029918586707798824, "acc_norm": 0.273542600896861, "acc_norm_stderr": 0.029918586707798824 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2748091603053435, "acc_stderr": 0.039153454088478354, "acc_norm": 0.2748091603053435, "acc_norm_stderr": 0.039153454088478354 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.4132231404958678, "acc_stderr": 0.04495087843548408, "acc_norm": 0.4132231404958678, "acc_norm_stderr": 0.04495087843548408 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04557239513497751, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04557239513497751 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.2147239263803681, "acc_stderr": 0.03226219377286774, "acc_norm": 0.2147239263803681, "acc_norm_stderr": 0.03226219377286774 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.29464285714285715, "acc_stderr": 0.04327040932578729, "acc_norm": 0.29464285714285715, "acc_norm_stderr": 0.04327040932578729 }, "harness\|hendrycksTest-management\|5": { "acc": 0.2524271844660194, "acc_stderr": 0.04301250399690878, "acc_norm": 0.2524271844660194, "acc_norm_stderr": 0.04301250399690878 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.3504273504273504, "acc_stderr": 0.03125610824421881, "acc_norm": 0.3504273504273504, "acc_norm_stderr": 0.03125610824421881 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.2988505747126437, "acc_stderr": 0.01636925681509314, "acc_norm": 0.2988505747126437, "acc_norm_stderr": 0.01636925681509314 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.30057803468208094, "acc_stderr": 0.024685316867257796, "acc_norm": 0.30057803468208094, "acc_norm_stderr": 0.024685316867257796 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.3300653594771242, "acc_stderr": 0.026925654653615686, "acc_norm": 0.3300653594771242, "acc_norm_stderr": 0.026925654653615686 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.2733118971061093, "acc_stderr": 0.02531176597542612, "acc_norm": 0.2733118971061093, "acc_norm_stderr": 0.02531176597542612 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.3055555555555556, "acc_stderr": 0.025630824975621344, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.025630824975621344 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.28368794326241137, "acc_stderr": 0.02689170942834396, "acc_norm": 0.28368794326241137, "acc_norm_stderr": 0.02689170942834396 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.28748370273794005, "acc_stderr": 0.011559337355708502, "acc_norm": 0.28748370273794005, "acc_norm_stderr": 0.011559337355708502 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.28104575163398693, "acc_stderr": 0.018185218954318075, "acc_norm": 0.28104575163398693, "acc_norm_stderr": 0.018185218954318075 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.3, "acc_stderr": 0.04389311454644286, "acc_norm": 0.3, "acc_norm_stderr": 0.04389311454644286 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.4163265306122449, "acc_stderr": 0.03155782816556165, "acc_norm": 0.4163265306122449, "acc_norm_stderr": 0.03155782816556165 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.34328358208955223, "acc_stderr": 0.03357379665433431, "acc_norm": 0.34328358208955223, "acc_norm_stderr": 0.03357379665433431 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.2710843373493976, "acc_stderr": 0.034605799075530276, "acc_norm": 0.2710843373493976, "acc_norm_stderr": 0.034605799075530276 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.39766081871345027, "acc_stderr": 0.0375363895576169, "acc_norm": 0.39766081871345027, "acc_norm_stderr": 0.0375363895576169 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7213359475135803, -0.8484181761741638, 0.32670751214027405, 0.18475861847400665, -0.1704566776752472, -0.034883931279182434, 0.022068370133638382, -0.23859050869941711, 0.596319317817688, -0.05192076787352562, -0.5172117352485657, -0.6921650767326355, -0.46485793590545654, 0.21287091076374054, -0.049273956567049026, 0.7852668762207031, -0.19515636563301086, -0.12146781384944916, 0.0673133060336113, -0.024092571809887886, -0.23333092033863068, -0.28983354568481445, 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justinphan3110/harmful_harmless_instructions	justinphan3110	2023-11-07T23:53:44Z	257	0	[ "region:us" ]	null	2023-11-07T23:53:41Z	--- dataset_info: features: - name: sentence sequence: string - name: label sequence: bool splits: - name: train num_bytes: 20636 num_examples: 128 - name: test num_bytes: 62788 num_examples: 384 download_size: 49815 dataset_size: 83424 --- # Dataset Card for "harmful_harmless_instructions" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.2447517365217209, -0.6251293420791626, 0.17587678134441376, 0.2878987193107605, -0.2971280813217163, -0.45227473974227905, 0.28861531615257263, -0.1711784154176712, 0.4670294225215912, 0.8594460487365723, -0.8530851006507874, -1.004335641860962, -0.583166778087616, -0.4656458795070648, -0.40524235367774963, 1.6251587867736816, 0.23199528455734253, 0.039651818573474884, -0.33482325077056885, -0.04865555465221405, -0.7350829243659973, 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CyranoB/polarity	CyranoB	2022-10-25T08:54:09Z	256	1	[ "task_categories:text-classification", "task_ids:sentiment-classification", "annotations_creators:crowdsourced", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:1M<n<10M", "source_datasets:original", "language:en", "license:apache-2.0", "arxiv:1509.01626", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - crowdsourced language: - en license: - apache-2.0 multilinguality: - monolingual size_categories: - 1M<n<10M source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification pretty_name: Amazon Review Polarity --- # Dataset Card for Amazon Review Polarity ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://registry.opendata.aws/ - Repository: https://github.com/zhangxiangxiao/Crepe - Paper: https://arxiv.org/abs/1509.01626 - Leaderboard: [Needs More Information] - Point of Contact: [Xiang Zhang](mailto:[email protected]) ### Dataset Summary The Amazon reviews dataset consists of reviews from amazon. The data span a period of 18 years, including ~35 million reviews up to March 2013. Reviews include product and user information, ratings, and a plaintext review. ### Supported Tasks and Leaderboards - `text-classification`, `sentiment-classification`: The dataset is mainly used for text classification: given the content and the title, predict the correct star rating. ### Languages Mainly English. ## Dataset Structure ### Data Instances A typical data point, comprises of a title, a content and the corresponding label. An example from the AmazonPolarity test set looks as follows: ``` { 'title':'Great CD', 'content':"My lovely Pat has one of the GREAT voices of her generation. I have listened to this CD for YEARS and I still LOVE IT. When I'm in a good mood it makes me feel better. A bad mood just evaporates like sugar in the rain. This CD just oozes LIFE. Vocals are jusat STUUNNING and lyrics just kill. One of life's hidden gems. This is a desert isle CD in my book. Why she never made it big is just beyond me. Everytime I play this, no matter black, white, young, old, male, female EVERYBODY says one thing ""Who was that singing ?""", 'label':1 } ``` ### Data Fields - 'title': a string containing the title of the review - escaped using double quotes (") and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n". - 'content': a string containing the body of the document - escaped using double quotes (") and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n". - 'label': either 1 (positive) or 0 (negative) rating. ### Data Splits The Amazon reviews polarity dataset is constructed by taking review score 1 and 2 as negative, and 4 and 5 as positive. Samples of score 3 is ignored. Each class has 1,800,000 training samples and 200,000 testing samples. ## Dataset Creation ### Curation Rationale The Amazon reviews polarity dataset is constructed by Xiang Zhang ([email protected]). It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information Apache License 2.0 ### Citation Information McAuley, Julian, and Jure Leskovec. "Hidden factors and hidden topics: understanding rating dimensions with review text." In Proceedings of the 7th ACM conference on Recommender systems, pp. 165-172. 2013. Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015) ### Contributions Thanks to [@hfawaz](https://github.com/hfawaz) for adding this dataset.	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Jeska/autonlp-data-vaccinfaq	Jeska	2021-10-19T12:06:57Z	256	0	[ "task_categories:text-classification", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- task_categories: - text-classification --- # AutoNLP Dataset for project: vaccinfaq ## Table of content - [Dataset Description](#dataset-description) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) ## Dataset Descritpion This dataset has been automatically processed by AutoNLP for project vaccinfaq. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "target": 6, "text": "What je naam?" }, { "target": 6, "text": "Hoe heet je?" } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "target": "ClassLabel(num_classes=181, names=['chitchat_ask_bye', 'chitchat_ask_hi', 'chitchat_ask_hi_de', 'chitchat_ask_hi_en', 'chitchat_ask_hi_fr', 'chitchat_ask_hoe_gaat_het', 'chitchat_ask_name', 'chitchat_ask_thanks', 'faq_ask_aantal_gevaccineerd', 'faq_ask_aantal_gevaccineerd_wereldwijd', 'faq_ask_afspraak_afzeggen', 'faq_ask_afspraak_gemist', 'faq_ask_algemeen_info', 'faq_ask_allergisch_na_vaccinatie', 'faq_ask_alternatieve_medicatie', 'faq_ask_andere_vaccins', 'faq_ask_astrazeneca', 'faq_ask_astrazeneca_bij_ouderen', 'faq_ask_astrazeneca_bloedklonters', 'faq_ask_astrazeneca_prik_2', 'faq_ask_attest', 'faq_ask_autisme_na_vaccinatie', 'faq_ask_auto-immuun', 'faq_ask_begeleiding', 'faq_ask_beschermen', 'faq_ask_beschermingsduur', 'faq_ask_beschermingspercentage', 'faq_ask_besmetten_na_vaccin', 'faq_ask_betalen_voor_vaccin', 'faq_ask_betrouwbaar', 'faq_ask_betrouwbare_bronnen', 'faq_ask_bijsluiter', 'faq_ask_bijwerking_AZ', 'faq_ask_bijwerking_JJ', 'faq_ask_bijwerking_algemeen', 'faq_ask_bijwerking_lange_termijn', 'faq_ask_bijwerking_moderna', 'faq_ask_bijwerking_pfizer', 'faq_ask_bloed_geven', 'faq_ask_borstvoeding', 'faq_ask_buitenlander', 'faq_ask_chronisch_ziek', 'faq_ask_combi', 'faq_ask_complottheorie', 'faq_ask_complottheorie_5G', 'faq_ask_complottheorie_Bill_Gates', 'faq_ask_contra_ind', 'faq_ask_corona_is_griep', 'faq_ask_corona_vermijden', 'faq_ask_covid_door_vaccin', 'faq_ask_curevac', 'faq_ask_derde_prik', 'faq_ask_dna', 'faq_ask_duur_vaccinatie', 'faq_ask_eerst_weigeren', 'faq_ask_eerste_prik_buitenland', 'faq_ask_essentieel_beroep', 'faq_ask_experimenteel', 'faq_ask_foetus', 'faq_ask_geen_antwoord', 'faq_ask_geen_risicopatient', 'faq_ask_geen_uitnodiging', 'faq_ask_gestockeerd', 'faq_ask_gezondheidstoestand_gekend', 'faq_ask_gif_in_vaccin', 'faq_ask_goedkeuring', 'faq_ask_groepsimmuniteit', 'faq_ask_hartspierontsteking', 'faq_ask_hersenziekte', 'faq_ask_hoe_dodelijk', 'faq_ask_hoe_weet_overheid', 'faq_ask_hoeveel_dosissen', 'faq_ask_huisarts', 'faq_ask_huisdieren', 'faq_ask_iedereen', 'faq_ask_in_vaccin', 'faq_ask_info_vaccins', 'faq_ask_janssen', 'faq_ask_janssen_een_dosis', 'faq_ask_jong_en_gezond', 'faq_ask_keuze', 'faq_ask_keuze_vaccinatiecentrum', 'faq_ask_kinderen', 'faq_ask_kosjer_halal', 'faq_ask_leveringen', 'faq_ask_logistiek', 'faq_ask_logistiek_veilig', 'faq_ask_magnetisch', 'faq_ask_man_vrouw_verschillen', 'faq_ask_mantelzorger', 'faq_ask_maximaal_een_dosis', 'faq_ask_meer_bijwerkingen_tweede_dosis', 'faq_ask_minder_mobiel', 'faq_ask_moderna', 'faq_ask_mondmasker', 'faq_ask_motiveren', 'faq_ask_mrna_vs_andere_vaccins', 'faq_ask_naaldangst', 'faq_ask_nadelen', 'faq_ask_nuchter', 'faq_ask_ontwikkeling', 'faq_ask_onvruchtbaar', 'faq_ask_oplopen_vaccinatie', 'faq_ask_pfizer', 'faq_ask_phishing', 'faq_ask_pijnstiller', 'faq_ask_planning_eerstelijnszorg', 'faq_ask_planning_ouderen', 'faq_ask_positieve_test_na_vaccin', 'faq_ask_prioritaire_gropen', 'faq_ask_privacy', 'faq_ask_probleem_registratie', 'faq_ask_problemen_uitnodiging', 'faq_ask_quarantaine', 'faq_ask_qvax_probleem', 'faq_ask_reproductiegetal', 'faq_ask_risicopatient', 'faq_ask_risicopatient_diabetes', 'faq_ask_risicopatient_hartvaat', 'faq_ask_risicopatient_immuunziekte', 'faq_ask_risicopatient_kanker', 'faq_ask_risicopatient_luchtwegaandoening', 'faq_ask_smaakverlies', 'faq_ask_snel_ontwikkeld', 'faq_ask_sneller_aan_de_beurt', 'faq_ask_taxi', 'faq_ask_test_voor_vaccin', 'faq_ask_testen', 'faq_ask_tijd_tot_tweede_dosis', 'faq_ask_timing_andere_vaccins', 'faq_ask_trage_start', 'faq_ask_tweede_dosis_afspraak', 'faq_ask_tweede_dosis_vervroegen', 'faq_ask_twijfel_bijwerkingen', 'faq_ask_twijfel_effectiviteit', 'faq_ask_twijfel_inhoud', 'faq_ask_twijfel_ivm_vaccinatie', 'faq_ask_twijfel_noodzaak', 'faq_ask_twijfel_ontwikkeling', 'faq_ask_twijfel_praktisch', 'faq_ask_twijfel_vaccins_zelf', 'faq_ask_twijfel_vrijheid', 'faq_ask_uit_flacon', 'faq_ask_uitnodiging_afspraak_kwijt', 'faq_ask_uitnodiging_na_vaccinatie', 'faq_ask_vaccin_doorgeven', 'faq_ask_vaccin_immuunsysteem', 'faq_ask_vaccin_variant', 'faq_ask_vaccinatiecentrum', 'faq_ask_vaccine_covid_gehad', 'faq_ask_vaccine_covid_gehad_effect', 'faq_ask_vakantie', 'faq_ask_veelgestelde_vragen', 'faq_ask_vegan', 'faq_ask_verplicht', 'faq_ask_verschillen', 'faq_ask_vrijwillig_Janssen', 'faq_ask_vrijwilliger', 'faq_ask_waar_en_wanneer', 'faq_ask_waarom', 'faq_ask_waarom_niet_verplicht', 'faq_ask_waarom_ouderen_eerst', 'faq_ask_waarom_twee_prikken', 'faq_ask_waarom_twijfel', 'faq_ask_wanneer_algemene_bevolking', 'faq_ask_wanneer_iedereen_gevaccineerd', 'faq_ask_wat_is_corona', 'faq_ask_wat_is_rna', 'faq_ask_wat_is_vaccin', 'faq_ask_wat_na_vaccinatie', 'faq_ask_welk_vaccin_krijg_ik', 'faq_ask_welke_vaccin', 'faq_ask_wie_ben_ik', 'faq_ask_wie_doet_inenting', 'faq_ask_wie_is_risicopatient', 'faq_ask_wie_nu', 'faq_ask_wilsonbekwaam', 'faq_ask_zwanger', 'get_started', 'nlu_fallback', 'test'], names_file=None, id=None)", "text": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 11651 \| \| valid \| 1267 \|	[ -0.5316134691238403, -0.5429306030273438, 0.1192181408405304, 0.15051022171974182, -0.052762471139431, 0.03564441576600075, 0.2094685435295105, -0.265144407749176, 0.35525384545326233, 0.15469220280647278, -0.6352500915527344, -0.7699576020240784, -0.3367837369441986, 0.6539660096168518, -0.17807705700397491, 0.7902734279632568, -0.11195474863052368, 0.2259315699338913, 0.18550848960876465, -0.20455269515514374, 0.4041615128517151, -0.2784723937511444, -0.443817138671875, 0.04671282321214676, 0.6826964616775513, 0.5975192785263062, 0.5153907537460327, 0.4511016309261322, 0.22141292691230774, 0.3297824561595917, -0.2533044219017029, 0.12699563801288605, -0.10681337118148804, -0.1291056126356125, -0.1203637570142746, -0.5160735845565796, -0.5268308520317078, 0.29740065336227417, 0.018759526312351227, 0.5100168585777283, 0.10841858386993408, 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NYTK/HuWNLI	NYTK	2023-03-27T09:53:33Z	256	3	[ "task_categories:other", "task_ids:coreference-resolution", "annotations_creators:found", "language_creators:found", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:extended\|other", "language:hu", "license:cc-by-sa-4.0", "structure-prediction", "region:us" ]	[ "other" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found - expert-generated language: - hu license: - cc-by-sa-4.0 multilinguality: - monolingual size_categories: - unknown source_datasets: - extended\|other task_categories: - other task_ids: - coreference-resolution pretty_name: HuWNLI tags: - structure-prediction --- # Dataset Card for HuWNLI ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: [HuWNLI dataset](https://github.com/nytud/HuWNLI) - Paper: - Leaderboard: - Point of Contact: [lnnoemi](mailto:[email protected]) ### Dataset Summary This is the dataset card for the Hungarian translation of the Winograd schemata formatted as an inference task. A Winograd schema is a pair of sentences that differ in only one or two words and that contain an ambiguity that is resolved in opposite ways in the two sentences and requires the use of world knowledge and reasoning for its resolution (Levesque et al. 2012). This dataset is also part of the Hungarian Language Understanding Evaluation Benchmark Kit [HuLU](hulu.nlp.nytud.hu). The corpus was created by translating and manually curating the original English Winograd schemata. The NLI format was created by replacing the ambiguous pronoun with each possible referent (the method is described in GLUE's paper, Wang et al. 2019). We extended the set of sentence pairs derived from the schemata by the translation of the sentence pairs that - together with the Winograd schema sentences - build up the WNLI dataset of GLUE. ### Languages The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU. ## Dataset Structure ### Data Instances For each instance, there is an orig_id, an id, two sentences and a label. An example: ``` {"orig_id": "4", "id": "4", "sentence1": "A férfi nem tudta felemelni a fiát, mert olyan nehéz volt.", "sentence2": "A fia nehéz volt.", "Label": "1" } ``` ### Data Fields - orig_id: the original id of this sentence pair (more precisely, its English counterpart's) in GLUE's WNLI dataset; - id: unique id of the instances; - sentence1: the premise; - sentence2: the hypothesis; - label: "1" if sentence2 is entailed by sentence1, and "0" otherwise. ### Data Splits The data is distributed in three splits: training set (562), development set (59) and test set (134). The splits follow GLUE's WNLI's splits but contain fewer instances as many sentence pairs had to be thrown away for being untranslatable to Hungarian. The train and the development set have been extended from nli sentence pairs formatted from the Hungarian translation of 6 Winograd schemata left out from the original WNLI dataset. The test set's sentence pairs are translated from GLUE's WNLI's test set. This set was distributed without labels. 3 annotators annotated the Hungarian sentence pairs. The test set of HuWNLI is also distributed without labels. To evaluate your model, please [contact us](mailto:[email protected]), or check [HuLU's website](hulu.nytud.hu) for an automatic evaluation (this feature is under construction at the moment). ## Dataset Creation ### Source Data #### Initial Data Collection and Normalization The data is a translation of the English Winograd schemata and the additional sentence pairs of GLUE's WNLI. Each schema and sentence pair was translated by a human translator. Each schema was manually curated by a linguistic expert. The schemata were transformed into nli format by a linguistic expert. During the adaption method, we found two erroneous labels in GLUE's WNLI's train set (id 347 and id 464). We corrected them in our dataset. ## Additional Information Average human performance on the test set is 92,78% (accuracy). ### Licensing Information HuWNLI is released under the Creative Commons Attribution-ShareAlike 4.0 International License. ### Citation Information If you use this resource or any part of its documentation, please refer to: Ligeti-Nagy, N., Héja, E., Laki, L. J., Takács, D., Yang, Z. Gy. and Váradi, T. (2023) Hát te mekkorát nőttél! - A HuLU első életéve új adatbázisokkal és webszolgáltatással \[Look at how much you have grown! - The first year of HuLU with new databases and with webservice\]. In: Berend, G., Gosztolya, G. and Vincze, V. (eds), XIX. Magyar Számítógépes Nyelvészeti Konferencia. Szeged, Szegedi Tudományegyetem, Informatikai Intézet. 217-230. ``` @inproceedings{ligetinagy2023hulu, title={át te mekkorát nőttél! - A HuLU első életéve új adatbázisokkal és webszolgáltatással}, author={Ligeti-Nagy, N. and Héja, E. and Laki, L. J. and Takács, D. and Yang, Z. Gy. and Váradi, T.}, booktitle={XIX. Magyar Számítógépes Nyelvészeti Konferencia}, year={2023}, editors = {Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika}, address = {Szeged}, publisher = {JATEPress}, pages = {217–230} } ``` Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából \[HuLU: Hungarian benchmark dataset to evaluate neural language models\]. In: Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika (eds), XVIII. Magyar Számítógépes Nyelvészeti Konferencia. JATEPress, Szeged. 431–446. ``` @inproceedings{ligetinagy2022hulu, title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából}, author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.}, booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia}, year={2022}, editors = {Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika}, address = {Szeged}, publisher = {JATEPress}, pages = {431–446} } ``` and to: Levesque, Hector, Davis, Ernest, Morgenstern, Leora (2012) he winograd schema challenge. In: Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning. ``` @inproceedings{levesque2012winograd, title={The Winograd Schema Challenge}, author={Levesque, Hector and Davis, Ernest and Morgenstern, Leora}, booktitle={Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning}, year={2012}, organization={Citeseer} } ``` ### Contributions Thanks to [lnnoemi](https://github.com/lnnoemi) for adding this dataset.	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OmarN121/train	OmarN121	2022-01-03T18:49:44Z	256	0	[ "region:us" ]	null	2022-03-02T23:29:22Z	--- YAML tags: - copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.	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SebastianS/github-issues	SebastianS	2022-10-25T09:06:38Z	256	0	[ "task_categories:text-classification", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:unknown", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: [] language_creators: - crowdsourced language: - en-US license: [] multilinguality: - monolingual pretty_name: github-issues size_categories: - unknown source_datasets: [] task_categories: - text-classification task_ids: [] --- # Dataset Card for GitHub Issues ## Dataset Description this was an example dataset made from the huggingface course	[ -0.34555745124816895, -0.5482677221298218, -0.05583514645695686, -0.008164414204657078, -0.15970732271671295, 0.18913085758686066, 0.03851143643260002, -0.029495030641555786, 0.7941468358039856, 0.38963979482650757, -0.8254137635231018, -0.826818585395813, -0.20840862393379211, -0.2682878077030182, -0.47423940896987915, 1.8173534870147705, -0.11328620463609695, 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huggingartists/bill-wurtz	huggingartists	2022-10-25T09:24:40Z	256	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/bill-wurtz" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.262088 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/0d4b35ed37091d5f6fd59806810e14ca.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/bill-wurtz"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Bill Wurtz</div> <a href="https://genius.com/artists/bill-wurtz"> <div style="text-align: center; font-size: 14px;">@bill-wurtz</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/bill-wurtz). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/bill-wurtz") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|495\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/bill-wurtz") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/max-korzh	huggingartists	2022-10-25T09:37:53Z	256	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/max-korzh" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.289652 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/a1486b5b6f28eeec202b55e983e464c5.567x567x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/max-korzh"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Макс Корж (Max Korzh)</div> <a href="https://genius.com/artists/max-korzh"> <div style="text-align: center; font-size: 14px;">@max-korzh</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/max-korzh). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/max-korzh") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|91\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/max-korzh") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/tony-raut-and-garry-topor	huggingartists	2022-10-25T09:48:30Z	256	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/tony-raut-and-garry-topor" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.083901 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/7249d6785a5c87095850bd4048595e08.989x989x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/tony-raut-and-garry-topor"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Тони Раут (Tony Raut) & Гарри Топор (Garry Topor)</div> <a href="https://genius.com/artists/tony-raut-and-garry-topor"> <div style="text-align: center; font-size: 14px;">@tony-raut-and-garry-topor</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/tony-raut-and-garry-topor). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/tony-raut-and-garry-topor") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|15\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/tony-raut-and-garry-topor") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/v-x-v-prince	huggingartists	2022-10-25T09:49:21Z	256	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/v-x-v-prince" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.198634 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/08ad78acc3e91c45a426390e7524d4e9.853x853x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/v-x-v-prince"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">V $ X V PRiNCE</div> <a href="https://genius.com/artists/v-x-v-prince"> <div style="text-align: center; font-size: 14px;">@v-x-v-prince</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/v-x-v-prince). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/v-x-v-prince") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|77\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/v-x-v-prince") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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jimregan/clarinpl_sejmsenat	jimregan	2023-01-22T13:37:24Z	256	1	[ "task_categories:other", "task_categories:automatic-speech-recognition", "annotations_creators:expert-generated", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:pl", "license:other", "region:us" ]	[ "other", "automatic-speech-recognition" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language: - pl license: - other multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - other - automatic-speech-recognition task_ids: [] --- # Dataset Card for ClarinPL Sejm/Senat Speech Corpus ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: [CLARIN-PL mowa](https://mowa.clarin-pl.eu/) - Repository: [Needs More Information] - Paper: [System for Automatic Transcription of Sessions of the Polish Senate](https://acoustics.ippt.pan.pl/index.php/aa/article/view/327/pdf_32) - Leaderboard: [Paperswithcode Leaderboard][Needs More Information] - Point of Contact: [Needs More Information] ### Dataset Summary A collection of 97 hours of parliamentary speeches published on the ClarinPL website. ### Supported Tasks and Leaderboards [Needs More Information] ### Languages The audio is in Polish. ## Dataset Structure ### Data Instances A typical data point comprises the path to the audio file, usually called `file` and its transcription, called `text`. An example from the dataset is: ``` {'file': '/root/.cache/huggingface/datasets/downloads/extracted/4143b1d75559b10028c1c7e8800c9ccc05934ca5a8ea15f8f9a92770576a1ee3/SejmSenat/audio/AdamAbramowicz-20130410/file000.wav', 'id': 'AdamAbramowicz-20130410-file000', 'speaker_id': 'AdamAbramowicz', 'text': 'panie marszałku wysoka izbo panie ministrze próbuje się przedstawiać polskę jako zieloną wyspę kraj który się szybko rozwija tymczasem rzeczywistość jest zupełnie inna a widać ją także dzisiaj przed polskim parlamentem próbuje się rząd próbuje zagonić polaków do pracy aż do śmierci przedłużać wiek emerytalny czyliczyli sytuacja gospodarcza polski w tym wypadku jest przedstawiana już zupełnie inaczej pakiet klimatyczny i protokół z kioto jak się zgadzają fachowcy od gospodarki jest szkodliwy dla krajów które są na dorobku a polska właśnie jest takim krajem'} ``` ### Data Fields - file: A path to the downloaded audio file in .wav format. - text: the transcription of the audio file. - speaker_id: The ID of the speaker of the audio. ### Data Splits \| \| Train \| Test \| \| ----- \| ----- \| ---- \| \| dataset \| 6622 \| 130 \| ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information [Needs More Information] ### Citation Information [Needs More Information] ### Contributions [Needs More Information]	[ -0.5597473978996277, -0.685817539691925, 0.13973025977611542, 0.3095330595970154, -0.340449720621109, -0.14586864411830902, -0.6695137023925781, -0.3048229217529297, 0.595465898513794, 0.6028349995613098, -0.8592411279678345, -1.002943515777588, -0.6529377698898315, 0.2511429488658905, -0.36277127265930176, 0.8309634327888489, 0.3256494700908661, 0.16132785379886627, 0.16840609908103943, -0.13837723433971405, -0.49043944478034973, -0.48632457852363586, -0.4133895933628082, 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joelniklaus/mapa	joelniklaus	2022-10-25T16:17:09Z	256	4	[ "task_categories:token-classification", "task_ids:named-entity-recognition", "annotations_creators:other", "language_creators:found", "multilinguality:multilingual", "size_categories:1K<n<10K", "source_datasets:original", "language:multilingual", "language:bg", "language:cs", "language:da", "language:de", "language:el", "language:en", "language:es", "language:et", "language:fi", "language:fr", "language:ga", "language:hu", "language:it", "language:lt", "language:lv", "language:mt", "language:nl", "language:pt", "language:ro", "language:sk", "language:sv", "license:cc-by-4.0", "named-entity-recognition-and-classification", "region:us" ]	[ "token-classification" ]	2022-07-20T12:14:50Z	--- annotations_creators: - other language_creators: - found language: - multilingual - bg - cs - da - de - el - en - es - et - fi - fr - ga - hu - it - lt - lv - mt - nl - pt - ro - sk - sv license: - cc-by-4.0 multilinguality: - multilingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - token-classification task_ids: - named-entity-recognition pretty_name: Spanish Datasets for Sensitive Entity Detection in the Legal Domain tags: - named-entity-recognition-and-classification --- # Dataset Card for Multilingual European Datasets for Sensitive Entity Detection in the Legal Domain ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: [Spanish](https://elrc-share.eu/repository/browse/mapa-anonymization-package-spanish/b550e1a88a8311ec9c1a00155d026706687917f92f64482587c6382175dffd76/), [Most](https://elrc-share.eu/repository/search/?q=mfsp:3222a6048a8811ec9c1a00155d0267067eb521077db54d6684fb14ce8491a391), [German, Portuguese, Slovak, Slovenian, Swedish](https://elrc-share.eu/repository/search/?q=mfsp:833df1248a8811ec9c1a00155d0267067685dcdb77064822b51cc16ab7b81a36) - Paper: de Gibert Bonet, O., García Pablos, A., Cuadros, M., & Melero, M. (2022). Spanish Datasets for Sensitive Entity Detection in the Legal Domain. Proceedings of the Language Resources and Evaluation Conference, June, 3751–3760. http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.400.pdf - Leaderboard: - Point of Contact: [Joel Niklaus](mailto:[email protected]) ### Dataset Summary The dataset consists of 12 documents (9 for Spanish due to parsing errors) taken from EUR-Lex, a multilingual corpus of court decisions and legal dispositions in the 24 official languages of the European Union. The documents have been annotated for named entities following the guidelines of the [MAPA project]( https://mapa-project.eu/) which foresees two annotation level, a general and a more fine-grained one. The annotated corpus can be used for named entity recognition/classification. ### Supported Tasks and Leaderboards The dataset supports the task of Named Entity Recognition and Classification (NERC). ### Languages The following languages are supported: bg, cs, da, de, el, en, es, et, fi, fr, ga, hu, it, lt, lv, mt, nl, pt, ro, sk, sv ## Dataset Structure ### Data Instances The file format is jsonl and three data splits are present (train, validation and test). Named Entity annotations are non-overlapping. ### Data Fields For the annotation the documents have been split into sentences. The annotations has been done on the token level. The files contain the following data fields - `language`: language of the sentence - `type`: The document type of the sentence. Currently, only EUR-LEX is supported. - `file_name`: The document file name the sentence belongs to. - `sentence_number`: The number of the sentence inside its document. - `tokens`: The list of tokens in the sentence. - `coarse_grained`: The coarse-grained annotations for each token - `fine_grained`: The fine-grained annotations for each token As previously stated, the annotation has been conducted on a global and a more fine-grained level. The tagset used for the global and the fine-grained named entities is the following: - Address - Building - City - Country - Place - Postcode - Street - Territory - Amount - Unit - Value - Date - Year - Standard Abbreviation - Month - Day of the Week - Day - Calender Event - Person - Age - Email - Ethnic Category - Family Name - Financial - Given Name – Female - Given Name – Male - Health Insurance Number - ID Document Number - Initial Name - Marital Status - Medical Record Number - Nationality - Profession - Role - Social Security Number - Title - Url - Organisation - Time - Vehicle - Build Year - Colour - License Plate Number - Model - Type The final coarse grained tagset (in IOB notation) is the following: `['O', 'B-ORGANISATION', 'I-ORGANISATION', 'B-ADDRESS', 'I-ADDRESS', 'B-DATE', 'I-DATE', 'B-PERSON', 'I-PERSON', 'B-AMOUNT', 'I-AMOUNT', 'B-TIME', 'I-TIME']` The final fine grained tagset (in IOB notation) is the following: `[ 'O', 'B-BUILDING', 'I-BUILDING', 'B-CITY', 'I-CITY', 'B-COUNTRY', 'I-COUNTRY', 'B-PLACE', 'I-PLACE', 'B-TERRITORY', 'I-TERRITORY', 'I-UNIT', 'B-UNIT', 'B-VALUE', 'I-VALUE', 'B-YEAR', 'I-YEAR', 'B-STANDARD ABBREVIATION', 'I-STANDARD ABBREVIATION', 'B-MONTH', 'I-MONTH', 'B-DAY', 'I-DAY', 'B-AGE', 'I-AGE', 'B-ETHNIC CATEGORY', 'I-ETHNIC CATEGORY', 'B-FAMILY NAME', 'I-FAMILY NAME', 'B-INITIAL NAME', 'I-INITIAL NAME', 'B-MARITAL STATUS', 'I-MARITAL STATUS', 'B-PROFESSION', 'I-PROFESSION', 'B-ROLE', 'I-ROLE', 'B-NATIONALITY', 'I-NATIONALITY', 'B-TITLE', 'I-TITLE', 'B-URL', 'I-URL', 'B-TYPE', 'I-TYPE', ]` ### Data Splits Splits created by Joel Niklaus. \| language \| # train files \| # validation files \| # test files \| # train sentences \| # validation sentences \| # test sentences \| \|:-----------\|----------------:\|---------------------:\|---------------:\|--------------------:\|-------------------------:\|-------------------:\| \| bg \| 9 \| 1 \| 2 \| 1411 \| 166 \| 560 \| \| cs \| 9 \| 1 \| 2 \| 1464 \| 176 \| 563 \| \| da \| 9 \| 1 \| 2 \| 1455 \| 164 \| 550 \| \| de \| 9 \| 1 \| 2 \| 1457 \| 166 \| 558 \| \| el \| 9 \| 1 \| 2 \| 1529 \| 174 \| 584 \| \| en \| 9 \| 1 \| 2 \| 893 \| 98 \| 408 \| \| es \| 7 \| 1 \| 1 \| 806 \| 248 \| 155 \| \| et \| 9 \| 1 \| 2 \| 1391 \| 163 \| 516 \| \| fi \| 9 \| 1 \| 2 \| 1398 \| 187 \| 531 \| \| fr \| 9 \| 1 \| 2 \| 1297 \| 97 \| 490 \| \| ga \| 9 \| 1 \| 2 \| 1383 \| 165 \| 515 \| \| hu \| 9 \| 1 \| 2 \| 1390 \| 171 \| 525 \| \| it \| 9 \| 1 \| 2 \| 1411 \| 162 \| 550 \| \| lt \| 9 \| 1 \| 2 \| 1413 \| 173 \| 548 \| \| lv \| 9 \| 1 \| 2 \| 1383 \| 167 \| 553 \| \| mt \| 9 \| 1 \| 2 \| 937 \| 93 \| 442 \| \| nl \| 9 \| 1 \| 2 \| 1391 \| 164 \| 530 \| \| pt \| 9 \| 1 \| 2 \| 1086 \| 105 \| 390 \| \| ro \| 9 \| 1 \| 2 \| 1480 \| 175 \| 557 \| \| sk \| 9 \| 1 \| 2 \| 1395 \| 165 \| 526 \| \| sv \| 9 \| 1 \| 2 \| 1453 \| 175 \| 539 \| ## Dataset Creation ### Curation Rationale „[…] to our knowledge, there exist no open resources annotated for NERC [Named Entity Recognition and Classificatio] in Spanish in the legal domain. With the present contribution, we intend to fill this gap. With the release of the created resources for fine-tuning and evaluation of sensitive entities detection in the legal domain, we expect to encourage the development of domain-adapted anonymisation tools for Spanish in this field“ (de Gibert Bonet et al., 2022) ### Source Data #### Initial Data Collection and Normalization The dataset consists of documents taken from EUR-Lex corpus which is publicly available. No further information on the data collection process are given in de Gibert Bonet et al. (2022). #### Who are the source language producers? The source language producers are presumably lawyers. ### Annotations #### Annotation process "The annotation scheme consists of a complex two level hierarchy adapted to the legal domain, it follows the scheme described in (Gianola et al., 2020) […] Level 1 entities refer to general categories (PERSON, DATE, TIME, ADDRESS...) and level 2 entities refer to more fine-grained subcategories (given name, personal name, day, year, month...). Eur-Lex, CPP and DE have been annotated following this annotation scheme […] The manual annotation was performed using INCePTION (Klie et al., 2018) by a sole annotator following the guidelines provided by the MAPA consortium." (de Gibert Bonet et al., 2022) #### Who are the annotators? Only one annotator conducted the annotation. More information are not provdided in de Gibert Bonet et al. (2022). ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations Note that the dataset at hand presents only a small portion of a bigger corpus as described in de Gibert Bonet et al. (2022). At the time of writing only the annotated documents from the EUR-Lex corpus were available. Note that the information given in this dataset card refer to the dataset version as provided by Joel Niklaus and Veton Matoshi. The dataset at hand is intended to be part of a bigger benchmark dataset. Creating a benchmark dataset consisting of several other datasets from different sources requires postprocessing. Therefore, the structure of the dataset at hand, including the folder structure, may differ considerably from the original dataset. In addition to that, differences with regard to dataset statistics as give in the respective papers can be expected. The reader is advised to have a look at the conversion script ```convert_to_hf_dataset.py``` in order to retrace the steps for converting the original dataset into the present jsonl-format. For further information on the original dataset structure, we refer to the bibliographical references and the original Github repositories and/or web pages provided in this dataset card. ## Additional Information ### Dataset Curators The names of the original dataset curators and creators can be found in references given below, in the section Citation Information. Additional changes were made by Joel Niklaus ([Email](mailto:[email protected]) ; [Github](https://github.com/joelniklaus)) and Veton Matoshi ([Email](mailto:[email protected]) ; [Github](https://github.com/kapllan)). ### Licensing Information [Attribution 4.0 International (CC BY 4.0) ](https://creativecommons.org/licenses/by/4.0/) ### Citation Information ``` @article{DeGibertBonet2022, author = {{de Gibert Bonet}, Ona and {Garc{\'{i}}a Pablos}, Aitor and Cuadros, Montse and Melero, Maite}, journal = {Proceedings of the Language Resources and Evaluation Conference}, number = {June}, pages = {3751--3760}, title = {{Spanish Datasets for Sensitive Entity Detection in the Legal Domain}}, url = {https://aclanthology.org/2022.lrec-1.400}, year = {2022} } ``` ### Contributions Thanks to [@JoelNiklaus](https://github.com/joelniklaus) and [@kapllan](https://github.com/kapllan) for adding this dataset.	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LabHC/moji	LabHC	2023-09-28T09:12:22Z	256	0	[ "task_categories:text-classification", "language:en", "region:us" ]	[ "text-classification" ]	2023-09-10T10:47:11Z	--- task_categories: - text-classification language: - en dataset_info: features: - name: text dtype: string - name: label dtype: int64 - name: sa dtype: int64 splits: - name: train num_bytes: 128596235 num_examples: 1613790 - name: test num_bytes: 35731728 num_examples: 448276 - name: dev num_bytes: 14325121 num_examples: 179310 download_size: 93470968 dataset_size: 178653084 --- The Moji dataset (Blodgett et al., 2016) (http://slanglab.cs.umass.edu/TwitterAAE/) contains tweets used for sentiment analysis (either positive or negative sentiment), with additional information on the type of English used in the tweets which is a sensitive attribute considered in fairness-aware approaches (African-American English (AAE) or Standard-American English (SAE)). The type of language is determined thanks to a supervised model. Only the data where the sensitive attribute is predicted with a certainty rate above a given threshold are kept. Based on this principle we make available two versions of the Moji dataset, respectively with a threshold of 80% and of 90%. The dataset's distributions are presented below. ### Dataset with 80% threshold \| \| Positive sentiment \| Negative Sentiment \| Total \| \|---\|---\|---\|---\| AAE \| 73 013 \| 44 023 \| 117 036 \| SAE \| 1 471 427 \| 652 913 \| 2 124 340 \| Total \| 1 544 440 \| 696 936 \| 2 241 376 \| To load this dataset, use the following code : ```python dataset = load_dataset("LabHC/moji", revision='moji_conf_08') ``` or by default the version is the dataset with 80% threshold ```python dataset = load_dataset("LabHC/moji") ``` ### Dataset with 90% threshold \| \| Positive sentiment \| Negative Sentiment \| Total \| \|---\|---\|---\|---\| AAE \| 30 827 \| 18 409 \| 49 236 \| SAE \| 793 867 \| 351 600 \| 1 145 467 \| Total \| 824 694 \| 370 009 \| 1 194 703 \| To load this dataset, use the following code : ```python dataset = load_dataset("LabHC/moji", revision='moji_conf_09') ``` ---- [Demographic Dialectal Variation in Social Media: A Case Study of African-American 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Llamacha/monolingual-quechua-iic	Llamacha	2022-10-02T14:40:00Z	255	0	[ "task_categories:fill-mask", "task_ids:language-modeling", "task_ids:masked-language-modeling", "annotations_creators:no-annotation", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:1M<n<5M", "source_datasets:original", "language:qu", "license:apache-2.0", "region:us" ]	[ "fill-mask" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - crowdsourced language: - qu license: - apache-2.0 multilinguality: - monolingual size_categories: - 1M<n<5M source_datasets: - original task_categories: - fill-mask task_ids: - language-modeling - masked-language-modeling --- # Dataset Card for Monolingual-Quechua-IIC ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: [https://llamacha.pe](https://llamacha.pe) - Paper: [Introducing QuBERT: A Large Monolingual Corpus and BERT Model for Southern Quechua](https://aclanthology.org/2022.deeplo-1.1.pdf) - Point of Contact: [Rodolfo Zevallos](mailto:[email protected]) - Size of downloaded dataset files: 373.28 MB ### Dataset Summary We present Monolingual-Quechua-IIC, a monolingual corpus of Southern Quechua, which can be used to build language models using Transformers models. This corpus also includes the Wiki and OSCAR corpora. We used this corpus to build Llama-RoBERTa-Quechua, the first language model for Southern Quechua using Transformers. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages Southern Quechua ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information Apache-2.0 ### Citation Information ``` @inproceedings{zevallos2022introducing, title={Introducing QuBERT: A Large Monolingual Corpus and BERT Model for Southern Quechua}, author={Zevallos, Rodolfo and Ortega, John and Chen, William and Castro, Richard and Bel, Nuria and Toshio, Cesar and Venturas, Renzo and Aradiel, Hilario and Melgarejo, Nelsi}, booktitle={Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing}, pages={1--13}, year={2022} } ``` ### Contributions Thanks to [@rjzevallos](https://github.com/rjzevallos) for adding this dataset.	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NYTK/HuCoPA	NYTK	2023-03-27T09:54:02Z	255	0	[ "task_categories:other", "annotations_creators:found", "language_creators:found", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:extended\|other", "language:hu", "license:bsd-2-clause", "commonsense-reasoning", "region:us" ]	[ "other" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found - expert-generated language: - hu license: - bsd-2-clause multilinguality: - monolingual size_categories: - unknown source_datasets: - extended\|other task_categories: - other task_ids: [] pretty_name: HuCoPA tags: - commonsense-reasoning --- # Dataset Card for HuCoPA ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: [HuCoPA dataset](https://github.com/nytud/HuCoPA) - Paper: - Leaderboard: - Point of Contact: [lnnoemi](mailto:[email protected]) ### Dataset Summary This is the dataset card for the Hungarian Choice of Plausible Alternatives Corpus (HuCoPA), which is also part of the Hungarian Language Understanding Evaluation Benchmark Kit [HuLU](hulu.nlp.nytud.hu). The corpus was created by translating and re-annotating the original English CoPA corpus (Roemmele et al., 2011). ### Supported Tasks and Leaderboards 'commonsense reasoning' 'question answering' ### Languages The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU. ## Dataset Structure ### Data Instances For each instance, there is an id, a premise, a question ('cause' or 'effect'), two alternatives and a label (1 or 2). An example: ``` {"idx": "1", "question": "cause", "label": "1", "premise": "A testem árnyékot vetett a fűre.", "choice1": "Felkelt a nap.", "choice2": "A füvet lenyírták."} ``` ### Data Fields - id: unique id of the instances, an integer between 1 and 1000; - question: "cause" or "effect". It suggests what kind of causal relation are we looking for: in the case of "cause" we search for the more plausible alternative that may be a cause of the premise. In the case of "effect" we are looking for a plausible result of the premise; - premise: the premise, a sentence; - choice1: the first alternative, a sentence; - choice2: the second alternative, a sentence; - label: the number of the more plausible alternative (1 or 2). ### Data Splits HuCoPA has 3 splits: train, validation and test. \| Dataset split \| Number of instances in the split \| \|---------------\|----------------------------------\| \| train \| 400 \| \| validation \| 100 \| \| test \| 500 \| The test data is distributed without the labels. To evaluate your model, please [contact us](mailto:[email protected]), or check [HuLU's website](hulu.nlp.nytud.hu) for an automatic evaluation (this feature is under construction at the moment). ## Dataset Creation ### Source Data #### Initial Data Collection and Normalization The data is a translation of the content of the CoPA corpus. Each sentence was translated by a human translator. Each translation was manually checked and further refined by another annotator. ### Annotations #### Annotation process The instances initially inherited their original labels from the CoPA dataset. Each instance was annotated by a human annotator. If the original label and the human annotator's label did not match, we manually curated the instance and assigned a final label to that. This step was necessary to ensure that the causal realationship had not been changed or lost during the translation process. #### Who are the annotators? The translators were native Hungarian speakers with English proficiency. The annotators were university students with some linguistic background. ## Additional Information The human performance on the test set is 96% (accuracy). ### Licensing Information HuCoPA is released under the BSD 2-Clause License. Copyright (c) 2010, University of Southern California All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ### Citation Information If you use this resource or any part of its documentation, please refer to: Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. In: Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika (eds), XVIII. Magyar Számítógépes Nyelvészeti Konferencia. JATEPress, Szeged. 431–446. ``` @inproceedings{ligetinagy2022hulu, title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából}, author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.}, booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia}, year={2022}, editors = {Berend, Gábor and Gosztolya, Gábor and Vincze, Veronika}, address = {Szeged}, publisher = {JATEPress}, pages = {431–446} } ``` and to: Roemmele, M., Bejan, C., and Gordon, A. (2011) Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning. AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning, Stanford University, March 21-23, 2011. ``` @inproceedings{roemmele2011choice, title={Choice of plausible alternatives: An evaluation of commonsense causal reasoning}, author={Roemmele, Melissa and Bejan, Cosmin Adrian and Gordon, Andrew S}, booktitle={2011 AAAI Spring Symposium Series}, year={2011}, url={https://people.ict.usc.edu/~gordon/publications/AAAI-SPRING11A.PDF}, } ``` ### Contributions Thanks to [lnnoemi](https://github.com/lnnoemi) for adding this dataset.	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abhishek/autonlp-data-prodigy-10	abhishek	2022-10-25T09:07:06Z	255	0	[ "language:en", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en --- # AutoNLP Dataset for project: prodigy-10 ## Table of content - [Dataset Description](#dataset-description) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) ## Dataset Descritpion This dataset has been automatically processed by AutoNLP for project prodigy-10. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "tags": [ 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8 ], "tokens": [ "tory", "backing", "for", "i", "d", "cards", "the", "tories", "are", "to", "back", "controversial", "government", "plans", "to", "introduce", "i", "d", "cards", ".", " ", "the", "shadow", "cabinet", "revealed", "its", "support", "ahead", "of", "next", "week", "s", "commons", "vote", "on", "a", "bill", "to", "introduce", "compulsory", "i", "d.", "the", "decision", "follows", "a", " ", "tough", "meeting", " ", "where", "some", "senior", "tories", "argued", "vociferously", "against", "the", "move", " ", "party", "sources", "told", "the", "bbc", ".", "the", "bill", " ", "which", "ministers", "claim", "will", "tackle", "crime", " ", "terrorism", "and", "illegal", "immigration", " ", "is", "expected", "to", "be", "opposed", "by", "the", "liberal", "democrats", ".", " ", "they", "have", "said", "the", "scheme", "is", " ", "deeply", "flawed", " ", "and", "a", "waste", "of", "money", ".", "sources", "within", "the", "conservative", "party", "told", "the", "bbc", "michael", "howard", "has", "always", "been", "in", "favour", "of", "i", "d", "cards", " ", "and", "tried", "to", "introduce", "them", "when", "he", "was", "home", "secretary", ".", "the", "party", "has", "been", " ", "agnostic", " ", "on", "the", "issue", "until", "now", "but", "had", "now", "decided", "to", "come", "off", "the", "fence", " ", "the", "tory", "source", "said", ".", "despite", "giving", "their", "backing", "to", "i", "d", "cards", " ", "the", "conservatives", "insisted", "they", "would", "hold", "ministers", "to", "account", "over", "the", "precise", "purpose", "of", "the", "scheme", ".", " ", "they", "said", "they", "would", "also", "press", "labour", "over", "whether", "objectives", "could", "be", "met", "and", "whether", "the", "home", "office", "would", "deliver", "them", ".", "and", "they", "pledged", "to", "assess", "the", "cost", "effectiveness", "of", "i", "d", "cards", "and", "whether", "people", "s", "privacy", "would", "be", "properly", "protected", ".", " ", "it", "is", "important", "to", "remember", "that", "this", "bill", "will", "take", "a", "decade", "to", "come", "into", "full", "effect", " ", "a", "spokesman", "said", ".", " ", "it", "will", "do", "nothing", "to", "solve", "the", "immediate", "problems", "of", "rising", "crime", "and", "uncontrolled", "immigration", ".", " ", "lib", "dem", "home", "affairs", "spokesman", "mark", "oaten", "said", ":", " ", "this", "has", "all", "the", "signs", "of", "michael", "howard", "overruling", "colleagues", " ", "concerns", "over", "i", "d", "cards", ".", " ", "the", "tories", "should", "have", "the", "courage", "to", "try", "and", "change", "public", "opinion", "not", "follow", "it", ".", " ", "the", "new", "chairman", "of", "the", "bar", "council", " ", "guy", "mansfield", "qc", "warned", "there", "was", "a", "real", "risk", "that", "people", "on", "the", " ", "margins", "of", "society", " ", "would", "be", "driven", "into", "the", "hands", "of", "extremists", ".", " ", "what", "is", "going", "to", "happen", "to", "young", "asian", "men", "when", "there", "has", "been", "a", "bomb", "gone", "off", "somewhere", " ", "they", "are", "going", "to", "be", "stopped", ".", "if", "they", "haven", "t", "[", "i", "d", "cards", "]", "they", "are", "going", "to", "be", "detained", "." ] }, { "tags": [ 2, 6, 8, 8, 0, 8, 0, 8, 8, 8, 2, 6, 6, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 1, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 0, 8, 2, 6, 8, 2, 6, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 2, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 2, 6, 6, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 2, 6, 6, 8, 8, 8, 0, 8, 2, 6, 8, 8, 8, 8, 2, 6, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 8, 8, 8, 8, 8, 2, 6, 8, 8, 8, 8, 8, 8, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 6, 8, 8, 2, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 6, 8, 8, 0, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 6, 8, 8, 8, 8, 8, 8, 8, 2, 6, 8 ], "tokens": [ "o", "gara", "revels", "in", "ireland", "victory", "ireland", "fly", "-", "half", "ronan", "o", "gara", "hailed", "his", "side", "s", "19", "-", "13", "victory", "over", "england", "as", "a", " ", "special", " ", "win", ".", " ", "the", "munster", "number", "10", "kicked", "a", "total", "of", "14", "points", " ", "including", "two", "drop", "goals", " ", "to", "help", "keep", "alive", "their", "grand", "slam", "hopes", ".", "he", "told", "bbc", "sport", ":", " ", "we", "made", "hard", "work", "of", "it", "but", "it", "s", "still", "special", "to", "beat", "england", ".", " ", "i", "had", "three", "chances", "to", "win", "the", "game", "but", "didn", "t.", "we", "have", "work", "to", "do", "after", "this", "but", "we", "never", "take", "a", "victory", "over", "england", "lightly", ".", " ", "ireland", "hooker", "shane", "byrne", "echoed", "o", "gara", "s", "comments", "but", "admitted", "the", "game", "had", "been", "england", "s", "best", "outing", "in", "the", "six", "nations", ".", "byrne", "said", ":", " ", "it", "was", "a", "really", " ", "really", "hard", "game", "but", "from", "one", "to", "15", "in", "our", "team", "we", "worked", "really", " ", "really", "hard", ".", " ", "we", "just", "had", "to", "stick", "to", "our", "defensive", "pattern", " ", "trust", "ourselves", "and", "trust", "those", "around", "us", ".", "all", "round", "it", "was", "fantastic", ".", " ", "ireland", "captain", "brian", "o", "driscoll", " ", "who", "scored", "his", "side", "s", "only", "try", " ", "said", ":", " ", "we", "are", "delighted", " ", "we", "felt", "if", "we", "performed", "well", "then", "we", "would", "win", "but", "with", "england", "also", "having", "played", "very", "well", "it", "makes", "it", "all", "the", "sweeter", ".", " ", "we", "did", "get", "the", "bounce", "of", "the", "ball", "and", "some", "days", "that", "happens", "and", "you", "ve", "just", "got", "to", "jump", "on", "the", "back", "of", "it", ".", " ", "ireland", "coach", "eddie", "o", "sullivan", "was", "surprised", "that", "england", "coach", "andy", "robinson", "said", "he", "was", "certain", "mark", "cueto", "was", "onside", "for", "a", "disallowed", "try", "just", "before", "the", "break", ".", " ", "andy", "was", "sitting", "two", "yards", "from", "me", "and", "i", "couldn", "t", "see", "whether", "he", "was", "offside", "or", "not", "so", "i", "don", "t", "know", "how", "andy", "could", "have", "known", " ", "said", "o", "sullivan", ".", " ", "what", "i", "do", "know", "is", "that", "england", "played", "well", "and", "when", "that", "happens", "it", "makes", "a", "very", "good", "victory", "for", "us", ".", " ", "we", "had", "to", "defend", "for", "long", "periods", "and", "that", "is", "all", "good", "for", "the", "confidence", "of", "the", "team", ".", " ", "i", "think", "our", "try", "was", "very", "well", "worked", " ", "it", "was", "a", "gem", " ", "as", "good", "a", "try", "as", "we", "have", "scored", "for", "a", "while", ".", " ", "o", "sullivan", "also", "rejected", "robinson", "s", "contention", "england", "dominated", "the", "forward", "play", ".", " ", "i", "think", "we", "lost", "one", "lineout", "and", "they", "lost", "four", "or", "five", "so", "i", "don", "t", "know", "how", "that", "adds", "up", "to", "domination", " ", "he", "said", ".", "o", "driscoll", "also", "insisted", "ireland", "were", "happy", "to", "handle", "the", "pressure", "of", "being", "considered", "favourites", "to", "win", "the", "six", "nations", "title", ".", " ", "this", "season", "for", "the", "first", "time", "we", "have", "been", "able", "to", "play", "with", "the", "favourites", " ", "tag", " ", "he", "said", ".", " ", "hopefully", "we", "have", "proved", "that", "today", "and", "can", "continue", "to", "keep", "doing", "so", ".", " ", "as", "for", "my", "try", "it", "was", "a", "move", "we", "had", "worked", "on", "all", "week", ".", "there", "was", "a", "bit", "of", "magic", "from", "geordan", "murphy", "and", "it", "was", "a", "great", "break", "from", "denis", "hickie", "." ] } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "tags": "Sequence(feature=ClassLabel(num_classes=9, names=['B-LOCATION', 'B-ORG', 'B-PERSON', 'B-PRODUCT', 'I-LOCATION', 'I-ORG', 'I-PERSON', 'I-PRODUCT', 'O'], names_file=None, id=None), length=-1, id=None)", "tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 186 \| \| valid \| 58 \|	[ -0.6302216649055481, -0.24883762001991272, 0.4834219217300415, 0.4455035626888275, -0.43216463923454285, 0.40848255157470703, 0.15042828023433685, -0.15307800471782684, 0.8134179711341858, 0.727168083190918, -0.5909950137138367, -0.5653313994407654, -0.5908657908439636, 0.3363111615180969, -0.2808403968811035, 0.9286856055259705, 0.2145635485649109, 0.17109599709510803, 0.36554795503616333, 0.05579998344182968, -0.35044267773628235, 0.046979036182165146, -0.4110852777957916, -0.09051264077425003, 0.25689640641212463, 0.3843890130519867, 1.0633097887039185, 1.0064061880111694, 0.6239469051361084, 0.2948037087917328, -0.3502643406391144, 0.18247349560260773, -0.17230211198329926, -0.6288512349128723, -0.34403181076049805, -0.47672122716903687, -0.7170694470405579, 0.066558338701725, 0.4439834952354431, 0.8680292963981628, -0.10965971648693085, 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alperiox/autonlp-data-user-review-classification	alperiox	2022-10-25T09:07:13Z	255	0	[ "task_categories:text-classification", "language:en", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- language: - en task_categories: - text-classification --- # AutoNLP Dataset for project: user-review-classification ## Table of content - [Dataset Description](#dataset-description) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) ## Dataset Descritpion This dataset has been automatically processed by AutoNLP for project user-review-classification. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "text": "awful", "target": 3 }, { "text": "it says you can only read three stories a month and yet everything i clicked on was blank and now it[...]", "target": 2 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "target": "ClassLabel(num_classes=4, names=['CONTENT', 'INTERFACE', 'SUBSCRIPTION', 'USER_EXPERIENCE'], names_file=None, id=None)", "text": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. 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astarostap/autonlp-data-antisemitism-2	astarostap	2022-10-25T09:07:21Z	255	0	[ "task_categories:text-classification", "language:en", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- language: - en task_categories: - text-classification --- # AutoNLP Dataset for project: antisemitism-2 ## Table of content - [Dataset Description](#dataset-description) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) ## Dataset Descritpion This dataset has been automatically processed by AutoNLP for project antisemitism-2. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "target": 0, "text": "Jew pods" }, { "target": 1, "text": "@PotatoLaydee He's a Jew...." } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "target": "ClassLabel(num_classes=2, names=['0', '1'], names_file=None, id=None)", "text": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. 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huggingartists/kizaru	huggingartists	2022-10-25T09:33:52Z	255	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/kizaru" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.610792 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/8d81c49a2d84e2a69faf1a725343874b.434x434x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/kizaru"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">kizaru</div> <a href="https://genius.com/artists/kizaru"> <div style="text-align: center; font-size: 14px;">@kizaru</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/kizaru). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/kizaru") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|200\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/kizaru") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/kojey-radical	huggingartists	2022-10-25T09:34:00Z	255	1	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/kojey-radical" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.317423 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/69984b683bf9f7d43b1580896174bf9f.673x673x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/kojey-radical"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Kojey Radical</div> <a href="https://genius.com/artists/kojey-radical"> <div style="text-align: center; font-size: 14px;">@kojey-radical</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/kojey-radical). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/kojey-radical") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|138\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/kojey-radical") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/ot-rus	huggingartists	2022-10-25T09:40:40Z	255	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/ot-rus" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.419574 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/5b2286f88533601eda462ce44dd2ee56.776x776x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/ot-rus"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">O.T (RUS)</div> <a href="https://genius.com/artists/ot-rus"> <div style="text-align: center; font-size: 14px;">@ot-rus</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/ot-rus). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/ot-rus") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|117\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/ot-rus") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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huggingartists/van-morrison	huggingartists	2022-10-25T09:49:27Z	255	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/van-morrison" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 1.062718 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/2f97270cc1d1420867052a6c331d5820.1000x667x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/van-morrison"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Van Morrison</div> <a href="https://genius.com/artists/van-morrison"> <div style="text-align: center; font-size: 14px;">@van-morrison</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/van-morrison). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/van-morrison") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|929\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/van-morrison") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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millawell/wikipedia_field_of_science	millawell	2022-10-11T08:26:28Z	255	5	[ "license:cc-by-sa-3.0", "region:us" ]	null	2022-10-11T08:16:50Z	--- license: cc-by-sa-3.0 ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 0.7903715372085571, 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taesiri/imagenet-hard	taesiri	2023-06-16T18:50:51Z	255	7	[ "task_categories:image-classification", "size_categories:10K<n<100K", "language:en", "license:mit", "OOD", "ImageNet", "Out Of Distribution", "arxiv:2304.05538", "region:us" ]	[ "image-classification" ]	2023-03-31T05:48:23Z	--- dataset_info: features: - name: image dtype: image - name: label sequence: int64 - name: origin dtype: string - name: english_label sequence: string splits: - name: validation num_bytes: 1771418938.94 num_examples: 10980 download_size: 6380094503 dataset_size: 1771418938.94 license: mit task_categories: - image-classification language: - en tags: - OOD - ImageNet - Out Of Distribution pretty_name: ImageNet-Hard size_categories: - 10K<n<100K --- # Dataset Card for "ImageNet-Hard" [Project Page](https://taesiri.github.io/ZoomIsAllYouNeed/) - [ArXiv](https://arxiv.org/abs/2304.05538) - [Paper](https://huggingface.co/papers/2304.05538) - [Github](https://github.com/taesiri/ZoomIsAllYouNeed) - [Image Browser](https://huggingface.co/spaces/taesiri/ImageNet-Hard-Browser) ## Dataset Summary ImageNet-Hard is a new benchmark that comprises 10,980 images collected from various existing ImageNet-scale benchmarks (ImageNet, ImageNet-V2, ImageNet-Sketch, ImageNet-C, ImageNet-R, ImageNet-ReaL, ImageNet-A, and ObjectNet). This dataset poses a significant challenge to state-of-the-art vision models as merely zooming in often fails to improve their ability to classify images correctly. As a result, even the most advanced models, such as `CLIP-ViT-L/14@336px`, struggle to perform well on this dataset, achieving a mere `2.02%` accuracy. ImageNet-Hard-4K: For the 4K version please refere to [this dataset](https://huggingface.co/datasets/taesiri/imagenet-hard-4K). ### Dataset Distribution ![Dataset Distribution](https://taesiri.github.io/ZoomIsAllYouNeed/static/svg/imagenet_hard_distribution.svg) ### Classifiers Performance \| Model \| Accuracy \| \| ------------------- \| -------- \| \| AlexNet \| 7.34 \| \| VGG-16 \| 12.00 \| \| ResNet-18 \| 10.86 \| \| ResNet-50 \| 14.74 \| \| ViT-B/32 \| 18.52 \| \| EfficientNet-B0 \| 16.57 \| \| EfficientNet-B7 \| 23.20 \| \| EfficientNet-L2-Ns \| 39.00 \| \| CLIP-ViT-L/14@224px \| 1.86 \| \| CLIP-ViT-L/14@336px \| 2.02 \| \| OpenCLIP-ViT-bigG-14\| 15.93 \| \| OpenCLIP-ViT-L-14 \| 15.60 \| Evaluation Code * CLIP <a target="_blank" href="https://colab.research.google.com/github/taesiri/ZoomIsAllYouNeed/blob/main/src/ImageNet_Hard/Prompt_Engineering_for_ImageNet_Hard.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a> * [OpenCLIP](https://github.com/taesiri/ZoomIsAllYouNeed/blob/main/src/ImageNet_Hard/benchmark_openclip.py) * Other models <a target="_blank" href="https://colab.research.google.com/github/taesiri/ZoomIsAllYouNeed/blob/main/src/ImageNet_Hard/Benchmark_ImageNet_Hard.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a> ## Supported Tasks - `image-classification`: The objective of this task is to classify an image into one or more classes, selected from 1000 ImageNet categories (allowing for multiple ground-truth labels per image). ## Languages The `english_label` field in the dataset are in English. ## Dataset Structure Data Instances An example looks like this: ```python { 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=575x409 at 0x7F09456B53A0>, 'label': [0], 'origin': 'imagenet_sketch', 'english_label': ['tench'] } ``` ### Data Fields The data instances have the following fields: - image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0]. - label: A List[int] collection containing the ground-truth ids. - origin: A string containing source dataset. - english_label: A List[str] collection containg the english labels for the ground-truth classes. <details> <summary> Click here to see the full list of ImageNet class labels mapping: </summary> \|id\|Class\| \|--\|-----\| \|0 \| tench, Tinca tinca\| \|1 \| goldfish, Carassius auratus\| \|2 \| great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias\| \|3 \| tiger shark, Galeocerdo cuvieri\| \|4 \| hammerhead, hammerhead shark\| \|5 \| electric ray, crampfish, numbfish, torpedo\| \|6 \| stingray\| \|7 \| cock\| \|8 \| hen\| \|9 \| ostrich, Struthio camelus\| \|10 \| brambling, Fringilla montifringilla\| \|11 \| goldfinch, Carduelis carduelis\| \|12 \| house finch, linnet, Carpodacus mexicanus\| \|13 \| junco, snowbird\| \|14 \| indigo bunting, indigo finch, indigo bird, Passerina cyanea\| \|15 \| robin, American robin, Turdus migratorius\| \|16 \| bulbul\| \|17 \| jay\| \|18 \| magpie\| \|19 \| chickadee\| \|20 \| water ouzel, dipper\| \|21 \| kite\| \|22 \| bald eagle, American eagle, Haliaeetus leucocephalus\| \|23 \| vulture\| \|24 \| great grey owl, great gray owl, Strix nebulosa\| \|25 \| European fire salamander, Salamandra salamandra\| \|26 \| common newt, Triturus vulgaris\| \|27 \| eft\| \|28 \| spotted salamander, Ambystoma maculatum\| \|29 \| axolotl, mud puppy, Ambystoma mexicanum\| \|30 \| bullfrog, Rana catesbeiana\| \|31 \| tree frog, tree-frog\| \|32 \| tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui\| \|33 \| loggerhead, loggerhead turtle, Caretta caretta\| \|34 \| leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea\| \|35 \| mud turtle\| \|36 \| terrapin\| \|37 \| box turtle, box tortoise\| \|38 \| banded gecko\| \|39 \| common iguana, iguana, Iguana iguana\| \|40 \| American chameleon, anole, Anolis carolinensis\| \|41 \| whiptail, whiptail lizard\| \|42 \| agama\| \|43 \| frilled lizard, Chlamydosaurus kingi\| \|44 \| alligator lizard\| \|45 \| Gila monster, Heloderma suspectum\| \|46 \| green lizard, Lacerta viridis\| \|47 \| African chameleon, Chamaeleo chamaeleon\| \|48 \| Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis\| \|49 \| African crocodile, Nile crocodile, Crocodylus niloticus\| \|50 \| American alligator, Alligator mississipiensis\| \|51 \| triceratops\| \|52 \| thunder snake, worm snake, Carphophis amoenus\| \|53 \| ringneck snake, ring-necked snake, ring snake\| \|54 \| hognose snake, puff adder, sand viper\| \|55 \| green snake, grass snake\| \|56 \| king snake, kingsnake\| \|57 \| garter snake, grass snake\| \|58 \| water snake\| \|59 \| vine snake\| \|60 \| night snake, Hypsiglena torquata\| \|61 \| boa constrictor, Constrictor constrictor\| \|62 \| rock python, rock snake, Python sebae\| \|63 \| Indian cobra, Naja naja\| \|64 \| green mamba\| \|65 \| sea snake\| \|66 \| horned viper, cerastes, sand viper, horned asp, Cerastes cornutus\| \|67 \| diamondback, diamondback rattlesnake, Crotalus adamanteus\| \|68 \| sidewinder, horned rattlesnake, Crotalus cerastes\| \|69 \| trilobite\| \|70 \| harvestman, daddy longlegs, Phalangium opilio\| \|71 \| scorpion\| \|72 \| black and gold garden spider, Argiope aurantia\| \|73 \| barn spider, Araneus cavaticus\| \|74 \| garden spider, Aranea diademata\| \|75 \| black widow, Latrodectus mactans\| \|76 \| tarantula\| \|77 \| wolf spider, hunting spider\| \|78 \| tick\| \|79 \| centipede\| \|80 \| black grouse\| \|81 \| ptarmigan\| \|82 \| ruffed grouse, partridge, Bonasa umbellus\| \|83 \| prairie chicken, prairie grouse, prairie fowl\| \|84 \| peacock\| \|85 \| quail\| \|86 \| partridge\| \|87 \| African grey, African gray, Psittacus erithacus\| \|88 \| macaw\| \|89 \| sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita\| \|90 \| lorikeet\| \|91 \| coucal\| \|92 \| bee eater\| \|93 \| hornbill\| \|94 \| hummingbird\| \|95 \| jacamar\| \|96 \| toucan\| \|97 \| drake\| \|98 \| red-breasted merganser, Mergus serrator\| \|99 \| goose\| \|100 \| black swan, Cygnus atratus\| \|101 \| tusker\| \|102 \| echidna, spiny anteater, anteater\| \|103 \| platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus\| \|104 \| wallaby, brush kangaroo\| \|105 \| koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus\| \|106 \| wombat\| \|107 \| jellyfish\| \|108 \| sea anemone, anemone\| \|109 \| brain coral\| \|110 \| flatworm, platyhelminth\| \|111 \| nematode, nematode worm, roundworm\| \|112 \| conch\| \|113 \| snail\| \|114 \| slug\| \|115 \| sea slug, nudibranch\| \|116 \| chiton, coat-of-mail shell, sea cradle, polyplacophore\| \|117 \| chambered nautilus, pearly nautilus, nautilus\| \|118 \| Dungeness crab, Cancer magister\| \|119 \| rock crab, Cancer irroratus\| \|120 \| fiddler crab\| \|121 \| king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica\| \|122 \| American lobster, Northern lobster, Maine lobster, Homarus americanus\| \|123 \| spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish\| \|124 \| crayfish, crawfish, crawdad, crawdaddy\| \|125 \| hermit crab\| \|126 \| isopod\| \|127 \| white stork, Ciconia ciconia\| \|128 \| black stork, Ciconia nigra\| \|129 \| spoonbill\| \|130 \| flamingo\| \|131 \| little blue heron, Egretta caerulea\| \|132 \| American egret, great white heron, Egretta albus\| \|133 \| bittern\| \|134 \| crane\| \|135 \| limpkin, Aramus pictus\| \|136 \| European gallinule, Porphyrio porphyrio\| \|137 \| American coot, marsh hen, mud hen, water hen, Fulica americana\| \|138 \| bustard\| \|139 \| ruddy turnstone, Arenaria interpres\| \|140 \| red-backed sandpiper, dunlin, Erolia alpina\| \|141 \| redshank, Tringa totanus\| \|142 \| dowitcher\| \|143 \| oystercatcher, oyster catcher\| \|144 \| pelican\| \|145 \| king penguin, Aptenodytes patagonica\| \|146 \| albatross, mollymawk\| \|147 \| grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus\| \|148 \| killer whale, killer, orca, grampus, sea wolf, Orcinus orca\| \|149 \| dugong, Dugong dugon\| \|150 \| sea lion\| \|151 \| Chihuahua\| \|152 \| Japanese spaniel\| \|153 \| Maltese dog, Maltese terrier, Maltese\| \|154 \| Pekinese, Pekingese, Peke\| \|155 \| Shih-Tzu\| \|156 \| Blenheim spaniel\| \|157 \| papillon\| \|158 \| toy terrier\| \|159 \| Rhodesian ridgeback\| \|160 \| Afghan hound, Afghan\| \|161 \| basset, basset hound\| \|162 \| beagle\| \|163 \| bloodhound, sleuthhound\| \|164 \| bluetick\| \|165 \| black-and-tan coonhound\| \|166 \| Walker hound, Walker foxhound\| \|167 \| English foxhound\| \|168 \| redbone\| \|169 \| borzoi, Russian wolfhound\| \|170 \| Irish wolfhound\| \|171 \| Italian greyhound\| \|172 \| whippet\| \|173 \| Ibizan hound, Ibizan Podenco\| \|174 \| Norwegian elkhound, elkhound\| \|175 \| otterhound, otter hound\| \|176 \| Saluki, gazelle hound\| \|177 \| Scottish deerhound, deerhound\| \|178 \| Weimaraner\| \|179 \| Staffordshire bullterrier, Staffordshire bull terrier\| \|180 \| American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier\| \|181 \| Bedlington terrier\| \|182 \| Border terrier\| \|183 \| Kerry blue terrier\| \|184 \| Irish terrier\| \|185 \| Norfolk terrier\| \|186 \| Norwich terrier\| \|187 \| Yorkshire terrier\| \|188 \| wire-haired fox terrier\| \|189 \| Lakeland terrier\| \|190 \| Sealyham terrier, Sealyham\| \|191 \| Airedale, Airedale terrier\| \|192 \| cairn, cairn terrier\| \|193 \| Australian terrier\| \|194 \| Dandie Dinmont, Dandie Dinmont terrier\| \|195 \| Boston bull, Boston terrier\| \|196 \| miniature schnauzer\| \|197 \| giant schnauzer\| \|198 \| standard schnauzer\| \|199 \| Scotch terrier, Scottish terrier, Scottie\| \|200 \| Tibetan terrier, chrysanthemum dog\| \|201 \| silky terrier, Sydney silky\| \|202 \| soft-coated wheaten terrier\| \|203 \| West Highland white terrier\| \|204 \| Lhasa, Lhasa apso\| \|205 \| flat-coated retriever\| \|206 \| curly-coated retriever\| \|207 \| golden retriever\| \|208 \| Labrador retriever\| \|209 \| Chesapeake Bay retriever\| \|210 \| German short-haired pointer\| \|211 \| vizsla, Hungarian pointer\| \|212 \| English setter\| \|213 \| Irish setter, red setter\| \|214 \| Gordon setter\| \|215 \| Brittany spaniel\| \|216 \| clumber, clumber spaniel\| \|217 \| English springer, English springer spaniel\| \|218 \| Welsh springer spaniel\| \|219 \| cocker spaniel, English cocker spaniel, cocker\| \|220 \| Sussex spaniel\| \|221 \| Irish water spaniel\| \|222 \| kuvasz\| \|223 \| schipperke\| \|224 \| groenendael\| \|225 \| malinois\| \|226 \| briard\| \|227 \| kelpie\| \|228 \| komondor\| \|229 \| Old English sheepdog, bobtail\| \|230 \| Shetland sheepdog, Shetland sheep dog, Shetland\| \|231 \| collie\| \|232 \| Border collie\| \|233 \| Bouvier des Flandres, Bouviers des Flandres\| \|234 \| Rottweiler\| \|235 \| German shepherd, German shepherd dog, German police dog, alsatian\| \|236 \| Doberman, Doberman pinscher\| \|237 \| miniature pinscher\| \|238 \| Greater Swiss Mountain dog\| \|239 \| Bernese mountain dog\| \|240 \| Appenzeller\| \|241 \| EntleBucher\| \|242 \| boxer\| \|243 \| bull mastiff\| \|244 \| Tibetan mastiff\| \|245 \| French bulldog\| \|246 \| Great Dane\| \|247 \| Saint Bernard, St Bernard\| \|248 \| Eskimo dog, husky\| \|249 \| malamute, malemute, Alaskan malamute\| \|250 \| Siberian husky\| \|251 \| dalmatian, coach dog, carriage dog\| \|252 \| affenpinscher, monkey pinscher, monkey dog\| \|253 \| basenji\| \|254 \| pug, pug-dog\| \|255 \| Leonberg\| \|256 \| Newfoundland, Newfoundland dog\| \|257 \| Great Pyrenees\| \|258 \| Samoyed, Samoyede\| \|259 \| Pomeranian\| \|260 \| chow, chow chow\| \|261 \| keeshond\| \|262 \| Brabancon griffon\| \|263 \| Pembroke, Pembroke Welsh corgi\| \|264 \| Cardigan, Cardigan Welsh corgi\| \|265 \| toy poodle\| \|266 \| miniature poodle\| \|267 \| standard poodle\| \|268 \| Mexican hairless\| \|269 \| timber wolf, grey wolf, gray wolf, Canis lupus\| \|270 \| white wolf, Arctic wolf, Canis lupus tundrarum\| \|271 \| red wolf, maned wolf, Canis rufus, Canis niger\| \|272 \| coyote, prairie wolf, brush wolf, Canis latrans\| \|273 \| dingo, warrigal, warragal, Canis dingo\| \|274 \| dhole, Cuon alpinus\| \|275 \| African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus\| \|276 \| hyena, hyaena\| \|277 \| red fox, Vulpes vulpes\| \|278 \| kit fox, Vulpes macrotis\| \|279 \| Arctic fox, white fox, Alopex lagopus\| \|280 \| grey fox, gray fox, Urocyon cinereoargenteus\| \|281 \| tabby, tabby cat\| \|282 \| tiger cat\| \|283 \| Persian cat\| \|284 \| Siamese cat, Siamese\| \|285 \| Egyptian cat\| \|286 \| cougar, puma, catamount, mountain lion, painter, panther, Felis concolor\| \|287 \| lynx, catamount\| \|288 \| leopard, Panthera pardus\| \|289 \| snow leopard, ounce, Panthera uncia\| \|290 \| jaguar, panther, Panthera onca, Felis onca\| \|291 \| lion, king of beasts, Panthera leo\| \|292 \| tiger, Panthera tigris\| \|293 \| cheetah, chetah, Acinonyx jubatus\| \|294 \| brown bear, bruin, Ursus arctos\| \|295 \| American black bear, black bear, Ursus americanus, Euarctos americanus\| \|296 \| ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus\| \|297 \| sloth bear, Melursus ursinus, Ursus ursinus\| \|298 \| mongoose\| \|299 \| meerkat, mierkat\| \|300 \| tiger beetle\| \|301 \| ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle\| \|302 \| ground beetle, carabid beetle\| \|303 \| long-horned beetle, longicorn, longicorn beetle\| \|304 \| leaf beetle, chrysomelid\| \|305 \| dung beetle\| \|306 \| rhinoceros beetle\| \|307 \| weevil\| \|308 \| fly\| \|309 \| bee\| \|310 \| ant, emmet, pismire\| \|311 \| grasshopper, hopper\| \|312 \| cricket\| \|313 \| walking stick, walkingstick, stick insect\| \|314 \| cockroach, roach\| \|315 \| mantis, mantid\| \|316 \| cicada, cicala\| \|317 \| leafhopper\| \|318 \| lacewing, lacewing fly\| \|319 \| dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk\| \|320 \| damselfly\| \|321 \| admiral\| \|322 \| ringlet, ringlet butterfly\| \|323 \| monarch, monarch butterfly, milkweed butterfly, Danaus plexippus\| \|324 \| cabbage butterfly\| \|325 \| sulphur butterfly, sulfur butterfly\| \|326 \| lycaenid, lycaenid butterfly\| \|327 \| starfish, sea star\| \|328 \| sea urchin\| \|329 \| sea cucumber, holothurian\| \|330 \| wood rabbit, cottontail, cottontail rabbit\| \|331 \| hare\| \|332 \| Angora, Angora rabbit\| \|333 \| hamster\| \|334 \| porcupine, hedgehog\| \|335 \| fox squirrel, eastern fox squirrel, Sciurus niger\| \|336 \| marmot\| \|337 \| beaver\| \|338 \| guinea pig, Cavia cobaya\| \|339 \| sorrel\| \|340 \| zebra\| \|341 \| hog, pig, grunter, squealer, Sus scrofa\| \|342 \| wild boar, boar, Sus scrofa\| \|343 \| warthog\| \|344 \| hippopotamus, hippo, river horse, Hippopotamus amphibius\| \|345 \| ox\| \|346 \| water buffalo, water ox, Asiatic buffalo, Bubalus bubalis\| \|347 \| bison\| \|348 \| ram, tup\| \|349 \| bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis\| \|350 \| ibex, Capra ibex\| \|351 \| hartebeest\| \|352 \| impala, Aepyceros melampus\| \|353 \| gazelle\| \|354 \| Arabian camel, dromedary, Camelus dromedarius\| \|355 \| llama\| \|356 \| weasel\| \|357 \| mink\| \|358 \| polecat, fitch, foulmart, foumart, Mustela putorius\| \|359 \| black-footed ferret, ferret, Mustela nigripes\| \|360 \| otter\| \|361 \| skunk, polecat, wood pussy\| \|362 \| badger\| \|363 \| armadillo\| \|364 \| three-toed sloth, ai, Bradypus tridactylus\| \|365 \| orangutan, orang, orangutang, Pongo pygmaeus\| \|366 \| gorilla, Gorilla gorilla\| \|367 \| chimpanzee, chimp, Pan troglodytes\| \|368 \| gibbon, Hylobates lar\| \|369 \| siamang, Hylobates syndactylus, Symphalangus syndactylus\| \|370 \| guenon, guenon monkey\| \|371 \| patas, hussar monkey, Erythrocebus patas\| \|372 \| baboon\| \|373 \| macaque\| \|374 \| langur\| \|375 \| colobus, colobus monkey\| \|376 \| proboscis monkey, Nasalis larvatus\| \|377 \| marmoset\| \|378 \| capuchin, ringtail, Cebus capucinus\| \|379 \| howler monkey, howler\| \|380 \| titi, titi monkey\| \|381 \| spider monkey, Ateles geoffroyi\| \|382 \| squirrel monkey, Saimiri sciureus\| \|383 \| Madagascar cat, ring-tailed lemur, Lemur catta\| \|384 \| indri, indris, Indri indri, Indri brevicaudatus\| \|385 \| Indian elephant, Elephas maximus\| \|386 \| African elephant, Loxodonta africana\| \|387 \| lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens\| \|388 \| giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca\| \|389 \| barracouta, snoek\| \|390 \| eel\| \|391 \| coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch\| \|392 \| rock beauty, Holocanthus tricolor\| \|393 \| anemone fish\| \|394 \| sturgeon\| \|395 \| gar, garfish, garpike, billfish, Lepisosteus osseus\| \|396 \| lionfish\| \|397 \| puffer, pufferfish, blowfish, globefish\| \|398 \| abacus\| \|399 \| abaya\| \|400 \| academic gown, academic robe, judge's robe\| \|401 \| accordion, piano accordion, squeeze box\| \|402 \| acoustic guitar\| \|403 \| aircraft carrier, carrier, flattop, attack aircraft carrier\| \|404 \| airliner\| \|405 \| airship, dirigible\| \|406 \| altar\| \|407 \| ambulance\| \|408 \| amphibian, amphibious vehicle\| \|409 \| analog clock\| \|410 \| apiary, bee house\| \|411 \| apron\| \|412 \| ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin\| \|413 \| assault rifle, assault gun\| \|414 \| backpack, back pack, knapsack, packsack, rucksack, haversack\| \|415 \| bakery, bakeshop, bakehouse\| \|416 \| balance beam, beam\| \|417 \| balloon\| \|418 \| ballpoint, ballpoint pen, ballpen, Biro\| \|419 \| Band Aid\| \|420 \| banjo\| \|421 \| bannister, banister, balustrade, balusters, handrail\| \|422 \| barbell\| \|423 \| barber chair\| \|424 \| barbershop\| \|425 \| barn\| \|426 \| barometer\| \|427 \| barrel, cask\| \|428 \| barrow, garden cart, lawn cart, wheelbarrow\| \|429 \| baseball\| \|430 \| basketball\| \|431 \| bassinet\| \|432 \| bassoon\| \|433 \| bathing cap, swimming cap\| \|434 \| bath towel\| \|435 \| bathtub, bathing tub, bath, tub\| \|436 \| beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon\| \|437 \| beacon, lighthouse, beacon light, pharos\| \|438 \| beaker\| \|439 \| bearskin, busby, shako\| \|440 \| beer bottle\| \|441 \| beer glass\| \|442 \| bell cote, bell cot\| \|443 \| bib\| \|444 \| bicycle-built-for-two, tandem bicycle, tandem\| \|445 \| bikini, two-piece\| \|446 \| binder, ring-binder\| \|447 \| binoculars, field glasses, opera glasses\| \|448 \| birdhouse\| \|449 \| boathouse\| \|450 \| bobsled, bobsleigh, bob\| \|451 \| bolo tie, bolo, bola tie, bola\| \|452 \| bonnet, poke bonnet\| \|453 \| bookcase\| \|454 \| bookshop, bookstore, bookstall\| \|455 \| bottlecap\| \|456 \| bow\| \|457 \| bow tie, bow-tie, bowtie\| \|458 \| brass, memorial tablet, plaque\| \|459 \| brassiere, bra, bandeau\| \|460 \| breakwater, groin, groyne, mole, bulwark, seawall, jetty\| \|461 \| breastplate, aegis, egis\| \|462 \| broom\| \|463 \| bucket, pail\| \|464 \| buckle\| \|465 \| bulletproof vest\| \|466 \| bullet train, bullet\| \|467 \| butcher shop, meat market\| \|468 \| cab, hack, taxi, taxicab\| \|469 \| caldron, cauldron\| \|470 \| candle, taper, wax light\| \|471 \| cannon\| \|472 \| canoe\| \|473 \| can opener, tin opener\| \|474 \| cardigan\| \|475 \| car mirror\| \|476 \| carousel, carrousel, merry-go-round, roundabout, whirligig\| \|477 \| carpenter's kit, tool kit\| \|478 \| carton\| \|479 \| car wheel\| \|480 \| cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM\| \|481 \| cassette\| \|482 \| cassette player\| \|483 \| castle\| \|484 \| catamaran\| \|485 \| CD player\| \|486 \| cello, violoncello\| \|487 \| cellular telephone, cellular phone, cellphone, cell, mobile phone\| \|488 \| chain\| \|489 \| chainlink fence\| \|490 \| chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour\| \|491 \| chain saw, chainsaw\| \|492 \| chest\| \|493 \| chiffonier, commode\| \|494 \| chime, bell, gong\| \|495 \| china cabinet, china closet\| \|496 \| Christmas stocking\| \|497 \| church, church building\| \|498 \| cinema, movie theater, movie theatre, movie house, picture palace\| \|499 \| cleaver, meat cleaver, chopper\| \|500 \| cliff dwelling\| \|501 \| cloak\| \|502 \| clog, geta, patten, sabot\| \|503 \| cocktail shaker\| \|504 \| coffee mug\| \|505 \| coffeepot\| \|506 \| coil, spiral, volute, whorl, helix\| \|507 \| combination lock\| \|508 \| computer keyboard, keypad\| \|509 \| confectionery, confectionary, candy store\| \|510 \| container ship, containership, container vessel\| \|511 \| convertible\| \|512 \| corkscrew, bottle screw\| \|513 \| cornet, horn, trumpet, trump\| \|514 \| cowboy boot\| \|515 \| cowboy hat, ten-gallon hat\| \|516 \| cradle\| \|517 \| crane_1\| \|518 \| crash helmet\| \|519 \| crate\| \|520 \| crib, cot\| \|521 \| Crock Pot\| \|522 \| croquet ball\| \|523 \| crutch\| \|524 \| cuirass\| \|525 \| dam, dike, dyke\| \|526 \| desk\| \|527 \| desktop computer\| \|528 \| dial telephone, dial phone\| \|529 \| diaper, nappy, napkin\| \|530 \| digital clock\| \|531 \| digital watch\| \|532 \| dining table, board\| \|533 \| dishrag, dishcloth\| \|534 \| dishwasher, dish washer, dishwashing machine\| \|535 \| disk brake, disc brake\| \|536 \| dock, dockage, docking facility\| \|537 \| dogsled, dog sled, dog sleigh\| \|538 \| dome\| \|539 \| doormat, welcome mat\| \|540 \| drilling platform, offshore rig\| \|541 \| drum, membranophone, tympan\| \|542 \| drumstick\| \|543 \| dumbbell\| \|544 \| Dutch oven\| \|545 \| electric fan, blower\| \|546 \| electric guitar\| \|547 \| electric locomotive\| \|548 \| entertainment center\| \|549 \| envelope\| \|550 \| espresso maker\| \|551 \| face powder\| \|552 \| feather boa, boa\| \|553 \| file, file cabinet, filing cabinet\| \|554 \| fireboat\| \|555 \| fire engine, fire truck\| \|556 \| fire screen, fireguard\| \|557 \| flagpole, flagstaff\| \|558 \| flute, transverse flute\| \|559 \| folding chair\| \|560 \| football helmet\| \|561 \| forklift\| \|562 \| fountain\| \|563 \| fountain pen\| \|564 \| four-poster\| \|565 \| freight car\| \|566 \| French horn, horn\| \|567 \| frying pan, frypan, skillet\| \|568 \| fur coat\| \|569 \| garbage truck, dustcart\| \|570 \| gasmask, respirator, gas helmet\| \|571 \| gas pump, gasoline pump, petrol pump, island dispenser\| \|572 \| goblet\| \|573 \| go-kart\| \|574 \| golf ball\| \|575 \| golfcart, golf cart\| \|576 \| gondola\| \|577 \| gong, tam-tam\| \|578 \| gown\| \|579 \| grand piano, grand\| \|580 \| greenhouse, nursery, glasshouse\| \|581 \| grille, radiator grille\| \|582 \| grocery store, grocery, food market, market\| \|583 \| guillotine\| \|584 \| hair slide\| \|585 \| hair spray\| \|586 \| half track\| \|587 \| hammer\| \|588 \| hamper\| \|589 \| hand blower, blow dryer, blow drier, hair dryer, hair drier\| \|590 \| hand-held computer, hand-held microcomputer\| \|591 \| handkerchief, hankie, hanky, hankey\| \|592 \| hard disc, hard disk, fixed disk\| \|593 \| harmonica, mouth organ, harp, mouth harp\| \|594 \| harp\| \|595 \| harvester, reaper\| \|596 \| hatchet\| \|597 \| holster\| \|598 \| home theater, home theatre\| \|599 \| honeycomb\| \|600 \| hook, claw\| \|601 \| hoopskirt, crinoline\| \|602 \| horizontal bar, high bar\| \|603 \| horse cart, horse-cart\| \|604 \| hourglass\| \|605 \| iPod\| \|606 \| iron, smoothing iron\| \|607 \| jack-o'-lantern\| \|608 \| jean, blue jean, denim\| \|609 \| jeep, landrover\| \|610 \| jersey, T-shirt, tee shirt\| \|611 \| jigsaw puzzle\| \|612 \| jinrikisha, ricksha, rickshaw\| \|613 \| joystick\| \|614 \| kimono\| \|615 \| knee pad\| \|616 \| knot\| \|617 \| lab coat, laboratory coat\| \|618 \| ladle\| \|619 \| lampshade, lamp shade\| \|620 \| laptop, laptop computer\| \|621 \| lawn mower, mower\| \|622 \| lens cap, lens cover\| \|623 \| letter opener, paper knife, paperknife\| \|624 \| library\| \|625 \| lifeboat\| \|626 \| lighter, light, igniter, ignitor\| \|627 \| limousine, limo\| \|628 \| liner, ocean liner\| \|629 \| lipstick, lip rouge\| \|630 \| Loafer\| \|631 \| lotion\| \|632 \| loudspeaker, speaker, speaker unit, loudspeaker system, speaker system\| \|633 \| loupe, jeweler's loupe\| \|634 \| lumbermill, sawmill\| \|635 \| magnetic compass\| \|636 \| mailbag, postbag\| \|637 \| mailbox, letter box\| \|638 \| maillot\| \|639 \| maillot, tank suit\| \|640 \| manhole cover\| \|641 \| maraca\| \|642 \| marimba, xylophone\| \|643 \| mask\| \|644 \| matchstick\| \|645 \| maypole\| \|646 \| maze, labyrinth\| \|647 \| measuring cup\| \|648 \| medicine chest, medicine cabinet\| \|649 \| megalith, megalithic structure\| \|650 \| microphone, mike\| \|651 \| microwave, microwave oven\| \|652 \| military uniform\| \|653 \| milk can\| \|654 \| minibus\| \|655 \| miniskirt, mini\| \|656 \| minivan\| \|657 \| missile\| \|658 \| mitten\| \|659 \| mixing bowl\| \|660 \| mobile home, manufactured home\| \|661 \| Model T\| \|662 \| modem\| \|663 \| monastery\| \|664 \| monitor\| \|665 \| moped\| \|666 \| mortar\| \|667 \| mortarboard\| \|668 \| mosque\| \|669 \| mosquito net\| \|670 \| motor scooter, scooter\| \|671 \| mountain bike, all-terrain bike, off-roader\| \|672 \| mountain tent\| \|673 \| mouse, computer mouse\| \|674 \| mousetrap\| \|675 \| moving van\| \|676 \| muzzle\| \|677 \| nail\| \|678 \| neck brace\| \|679 \| necklace\| \|680 \| nipple\| \|681 \| notebook, notebook computer\| \|682 \| obelisk\| \|683 \| oboe, hautboy, hautbois\| \|684 \| ocarina, sweet potato\| \|685 \| odometer, hodometer, mileometer, milometer\| \|686 \| oil filter\| \|687 \| organ, pipe organ\| \|688 \| oscilloscope, scope, cathode-ray oscilloscope, CRO\| \|689 \| overskirt\| \|690 \| oxcart\| \|691 \| oxygen mask\| \|692 \| packet\| \|693 \| paddle, boat paddle\| \|694 \| paddlewheel, paddle wheel\| \|695 \| padlock\| \|696 \| paintbrush\| \|697 \| pajama, pyjama, pj's, jammies\| \|698 \| palace\| \|699 \| panpipe, pandean pipe, syrinx\| \|700 \| paper towel\| \|701 \| parachute, chute\| \|702 \| parallel bars, bars\| \|703 \| park bench\| \|704 \| parking meter\| \|705 \| passenger car, coach, carriage\| \|706 \| patio, terrace\| \|707 \| pay-phone, pay-station\| \|708 \| pedestal, plinth, footstall\| \|709 \| pencil box, pencil case\| \|710 \| pencil sharpener\| \|711 \| perfume, essence\| \|712 \| Petri dish\| \|713 \| photocopier\| \|714 \| pick, plectrum, plectron\| \|715 \| pickelhaube\| \|716 \| picket fence, paling\| \|717 \| pickup, pickup truck\| \|718 \| pier\| \|719 \| piggy bank, penny bank\| \|720 \| pill bottle\| \|721 \| pillow\| \|722 \| ping-pong ball\| \|723 \| pinwheel\| \|724 \| pirate, pirate ship\| \|725 \| pitcher, ewer\| \|726 \| plane, carpenter's plane, woodworking plane\| \|727 \| planetarium\| \|728 \| plastic bag\| \|729 \| plate rack\| \|730 \| plow, plough\| \|731 \| plunger, plumber's helper\| \|732 \| Polaroid camera, Polaroid Land camera\| \|733 \| pole\| \|734 \| police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria\| \|735 \| poncho\| \|736 \| pool table, billiard table, snooker table\| \|737 \| pop bottle, soda bottle\| \|738 \| pot, flowerpot\| \|739 \| potter's wheel\| \|740 \| power drill\| \|741 \| prayer rug, prayer mat\| \|742 \| printer\| \|743 \| prison, prison house\| \|744 \| projectile, missile\| \|745 \| projector\| \|746 \| puck, hockey puck\| \|747 \| punching bag, punch bag, punching ball, punchball\| \|748 \| purse\| \|749 \| quill, quill pen\| \|750 \| quilt, comforter, comfort, puff\| \|751 \| racer, race car, racing car\| \|752 \| racket, racquet\| \|753 \| radiator\| \|754 \| radio, wireless\| \|755 \| radio telescope, radio reflector\| \|756 \| rain barrel\| \|757 \| recreational vehicle, RV, R.V.\| \|758 \| reel\| \|759 \| reflex camera\| \|760 \| refrigerator, icebox\| \|761 \| remote control, remote\| \|762 \| restaurant, eating house, eating place, eatery\| \|763 \| revolver, six-gun, six-shooter\| \|764 \| rifle\| \|765 \| rocking chair, rocker\| \|766 \| rotisserie\| \|767 \| rubber eraser, rubber, pencil eraser\| \|768 \| rugby ball\| \|769 \| rule, ruler\| \|770 \| running shoe\| \|771 \| safe\| \|772 \| safety pin\| \|773 \| saltshaker, salt shaker\| \|774 \| sandal\| \|775 \| sarong\| \|776 \| sax, saxophone\| \|777 \| scabbard\| \|778 \| scale, weighing machine\| \|779 \| school bus\| \|780 \| schooner\| \|781 \| scoreboard\| \|782 \| screen, CRT screen\| \|783 \| screw\| \|784 \| screwdriver\| \|785 \| seat belt, seatbelt\| \|786 \| sewing machine\| \|787 \| shield, buckler\| \|788 \| shoe shop, shoe-shop, shoe store\| \|789 \| shoji\| \|790 \| shopping basket\| \|791 \| shopping cart\| \|792 \| shovel\| \|793 \| shower cap\| \|794 \| shower curtain\| \|795 \| ski\| \|796 \| ski mask\| \|797 \| sleeping bag\| \|798 \| slide rule, slipstick\| \|799 \| sliding door\| \|800 \| slot, one-armed bandit\| \|801 \| snorkel\| \|802 \| snowmobile\| \|803 \| snowplow, snowplough\| \|804 \| soap dispenser\| \|805 \| soccer ball\| \|806 \| sock\| \|807 \| solar dish, solar collector, solar furnace\| \|808 \| sombrero\| \|809 \| soup bowl\| \|810 \| space bar\| \|811 \| space heater\| \|812 \| space shuttle\| \|813 \| spatula\| \|814 \| speedboat\| \|815 \| spider web, spider's web\| \|816 \| spindle\| \|817 \| sports car, sport car\| \|818 \| spotlight, spot\| \|819 \| stage\| \|820 \| steam locomotive\| \|821 \| steel arch bridge\| \|822 \| steel drum\| \|823 \| stethoscope\| \|824 \| stole\| \|825 \| stone wall\| \|826 \| stopwatch, stop watch\| \|827 \| stove\| \|828 \| strainer\| \|829 \| streetcar, tram, tramcar, trolley, trolley car\| \|830 \| stretcher\| \|831 \| studio couch, day bed\| \|832 \| stupa, tope\| \|833 \| submarine, pigboat, sub, U-boat\| \|834 \| suit, suit of clothes\| \|835 \| sundial\| \|836 \| sunglass\| \|837 \| sunglasses, dark glasses, shades\| \|838 \| sunscreen, sunblock, sun blocker\| \|839 \| suspension bridge\| \|840 \| swab, swob, mop\| \|841 \| sweatshirt\| \|842 \| swimming trunks, bathing trunks\| \|843 \| swing\| \|844 \| switch, electric switch, electrical switch\| \|845 \| syringe\| \|846 \| table lamp\| \|847 \| tank, army tank, armored combat vehicle, armoured combat vehicle\| \|848 \| tape player\| \|849 \| teapot\| \|850 \| teddy, teddy bear\| \|851 \| television, television system\| \|852 \| tennis ball\| \|853 \| thatch, thatched roof\| \|854 \| theater curtain, theatre curtain\| \|855 \| thimble\| \|856 \| thresher, thrasher, threshing machine\| \|857 \| throne\| \|858 \| tile roof\| \|859 \| toaster\| \|860 \| tobacco shop, tobacconist shop, tobacconist\| \|861 \| toilet seat\| \|862 \| torch\| \|863 \| totem pole\| \|864 \| tow truck, tow car, wrecker\| \|865 \| toyshop\| \|866 \| tractor\| \|867 \| trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi\| \|868 \| tray\| \|869 \| trench coat\| \|870 \| tricycle, trike, velocipede\| \|871 \| trimaran\| \|872 \| tripod\| \|873 \| triumphal arch\| \|874 \| trolleybus, trolley coach, trackless trolley\| \|875 \| trombone\| \|876 \| tub, vat\| \|877 \| turnstile\| \|878 \| typewriter keyboard\| \|879 \| umbrella\| \|880 \| unicycle, monocycle\| \|881 \| upright, upright piano\| \|882 \| vacuum, vacuum cleaner\| \|883 \| vase\| \|884 \| vault\| \|885 \| velvet\| \|886 \| vending machine\| \|887 \| vestment\| \|888 \| viaduct\| \|889 \| violin, fiddle\| \|890 \| volleyball\| \|891 \| waffle iron\| \|892 \| wall clock\| \|893 \| wallet, billfold, notecase, pocketbook\| \|894 \| wardrobe, closet, press\| \|895 \| warplane, military plane\| \|896 \| washbasin, handbasin, washbowl, lavabo, wash-hand basin\| \|897 \| washer, automatic washer, washing machine\| \|898 \| water bottle\| \|899 \| water jug\| \|900 \| water tower\| \|901 \| whiskey jug\| \|902 \| whistle\| \|903 \| wig\| \|904 \| window screen\| \|905 \| window shade\| \|906 \| Windsor tie\| \|907 \| wine bottle\| \|908 \| wing\| \|909 \| wok\| \|910 \| wooden spoon\| \|911 \| wool, woolen, woollen\| \|912 \| worm fence, snake fence, snake-rail fence, Virginia fence\| \|913 \| wreck\| \|914 \| yawl\| \|915 \| yurt\| \|916 \| web site, website, internet site, site\| \|917 \| comic book\| \|918 \| crossword puzzle, crossword\| \|919 \| street sign\| \|920 \| traffic light, traffic signal, stoplight\| \|921 \| book jacket, dust cover, dust jacket, dust wrapper\| \|922 \| menu\| \|923 \| plate\| \|924 \| guacamole\| \|925 \| consomme\| \|926 \| hot pot, hotpot\| \|927 \| trifle\| \|928 \| ice cream, icecream\| \|929 \| ice lolly, lolly, lollipop, popsicle\| \|930 \| French loaf\| \|931 \| bagel, beigel\| \|932 \| pretzel\| \|933 \| cheeseburger\| \|934 \| hotdog, hot dog, red hot\| \|935 \| mashed potato\| \|936 \| head cabbage\| \|937 \| broccoli\| \|938 \| cauliflower\| \|939 \| zucchini, courgette\| \|940 \| spaghetti squash\| \|941 \| acorn squash\| \|942 \| butternut squash\| \|943 \| cucumber, cuke\| \|944 \| artichoke, globe artichoke\| \|945 \| bell pepper\| \|946 \| cardoon\| \|947 \| mushroom\| \|948 \| Granny Smith\| \|949 \| strawberry\| \|950 \| orange\| \|951 \| lemon\| \|952 \| fig\| \|953 \| pineapple, ananas\| \|954 \| banana\| \|955 \| jackfruit, jak, jack\| \|956 \| custard apple\| \|957 \| pomegranate\| \|958 \| hay\| \|959 \| carbonara\| \|960 \| chocolate sauce, chocolate syrup\| \|961 \| dough\| \|962 \| meat loaf, meatloaf\| \|963 \| pizza, pizza pie\| \|964 \| potpie\| \|965 \| burrito\| \|966 \| red wine\| \|967 \| espresso\| \|968 \| cup\| \|969 \| eggnog\| \|970 \| alp\| \|971 \| bubble\| \|972 \| cliff, drop, drop-off\| \|973 \| coral reef\| \|974 \| geyser\| \|975 \| lakeside, lakeshore\| \|976 \| promontory, headland, head, foreland\| \|977 \| sandbar, sand bar\| \|978 \| seashore, coast, seacoast, sea-coast\| \|979 \| valley, vale\| \|980 \| volcano\| \|981 \| ballplayer, baseball player\| \|982 \| groom, bridegroom\| \|983 \| scuba diver\| \|984 \| rapeseed\| \|985 \| daisy\| \|986 \| yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum\| \|987 \| corn\| \|988 \| acorn\| \|989 \| hip, rose hip, rosehip\| \|990 \| buckeye, horse chestnut, conker\| \|991 \| coral fungus\| \|992 \| agaric\| \|993 \| gyromitra\| \|994 \| stinkhorn, carrion fungus\| \|995 \| earthstar\| \|996 \| hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa\| \|997 \| bolete\| \|998 \| ear, spike, capitulum\| \|999 \| toilet tissue, toilet paper, bathroom tissue\| </details> ### Data Splits This dataset is a validation-only set. ## Dataset Creation ### Source Data This dataset is sourced from ImageNet, ImageNet-ReaL, ImageNet-V2, ImageNet-A, ImageNet-C, ImageNet-R, ImageNet-Sketch, and ObjectNet. ## Citation Information ``` @article{taesiri2023zoom, title={ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification}, author={Taesiri, Mohammad Reza and Nguyen, Giang and Habchi, Sarra and Bezemer, Cor-Paul and Nguyen, Anh}, journal={arXiv preprint arXiv:2304.05538}, year={2023} } ```	[ -0.7212684154510498, -0.31194546818733215, -0.2615276277065277, 0.04576675221323967, -0.06828109174966812, 0.026099322363734245, 0.003598230890929699, -0.4605828821659088, 0.6607921123504639, 0.1807488054037094, -0.32680457830429077, -0.6760146617889404, -0.6887556314468384, 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reciprocate/number-pairs	reciprocate	2023-11-20T14:36:37Z	255	0	[ "region:us" ]	null	2023-05-03T15:16:41Z	--- dataset_info: features: - name: prompt dtype: string - name: selected dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 30931 num_examples: 900 - name: test num_bytes: 3436 num_examples: 100 download_size: 5098 dataset_size: 34367 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "autocrit-testing-numbers" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.6603014469146729, -0.3200773596763611, 0.04006931558251381, 0.2656821608543396, -0.24892061948776245, 0.12015415728092194, 0.3458818793296814, -0.10836964100599289, 0.6857935190200806, 0.2547573447227478, -0.728866457939148, -0.45336711406707764, -0.5018501281738281, 0.017208844423294067, -0.5968854427337646, 1.168872356414795, 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d0rj/samsum-ru	d0rj	2023-05-13T06:44:23Z	255	3	[ "task_categories:summarization", "annotations_creators:expert-generated", "language_creators:translated", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:samsum", "language:ru", "license:cc-by-nc-nd-4.0", "conversations-summarization", "arxiv:1911.12237", "region:us" ]	[ "summarization" ]	2023-05-08T08:57:36Z	--- annotations_creators: - expert-generated language_creators: - translated language: - ru license: - cc-by-nc-nd-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - samsum task_categories: - summarization task_ids: [] pretty_name: SAMSum Corpus (ru) tags: - conversations-summarization dataset_info: features: - name: id dtype: string - name: dialogue dtype: string - name: summary dtype: string splits: - name: train num_bytes: 8598724 num_examples: 14731 - name: validation num_bytes: 471632 num_examples: 818 - name: test num_bytes: 483686 num_examples: 819 dataset_size: 9554042 train-eval-index: - config: samsum task: summarization task_id: summarization splits: eval_split: test col_mapping: dialogue: text summary: target --- # Dataset Card for SAMSum Corpus (ru) ## Dataset Description Translated [samsum](https://huggingface.co/datasets/samsum) dataset to russian language. ### Notes > Row with ID 13828807 was deleted. ### Links - Homepage: hhttps://arxiv.org/abs/1911.12237v2 - Repository: https://arxiv.org/abs/1911.12237v2 - Paper: https://arxiv.org/abs/1911.12237v2 ### Languages Russian (translated from English [samsum](https://huggingface.co/datasets/samsum) using Google Translator) ## Dataset Structure ### Data Fields - dialogue: text of dialogue. - summary: human written summary of the dialogue. - id: unique file id of an example. ### Data Splits - train: 14731 - val: 818 - test: 819 ## Licensing Information non-commercial licence: CC BY-NC-ND 4.0 ## Citation Information ``` @inproceedings{gliwa-etal-2019-samsum, title = "{SAMS}um Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization", author = "Gliwa, Bogdan and Mochol, Iwona and Biesek, Maciej and Wawer, Aleksander", booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/D19-5409", doi = "10.18653/v1/D19-5409", pages = "70--79" } ```	[ -0.14780493080615997, -0.472480833530426, 0.12146741896867752, 0.12443617731332779, -0.5924937129020691, -0.042724162340164185, -0.27295348048210144, -0.13880251348018646, 0.5213713049888611, 0.3945130705833435, -0.6489240527153015, -0.928986132144928, -0.4737769663333893, 0.3153054714202881, -0.24300193786621094, 1.531212568283081, 0.13621613383293152, 0.1798332780599594, -0.6437199711799622, -0.2079373151063919, 0.1131138727068901, -0.3757818341255188, -0.4678393006324768, -0.012631393037736416, 0.2262328565120697, 0.4577922523021698, 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ArmelR/the-pile-splitted	ArmelR	2023-09-06T09:53:16Z	255	4	[ "arxiv:2101.00027", "arxiv:2201.07311", "region:us" ]	null	2023-07-30T14:21:26Z	--- configs: - config_name: all data_files: - split: train path: - "data/ArXiv/train/.arrow" - "data/BookCorpus2/train/.arrow" - "data/Books3/train/.arrow" - "data/DM Mathematics/train/.arrow" - "data/Enron Emails/train/.arrow" - "data/EuroParl/train/.arrow" - "data/FreeLaw/train/.arrow" - "data/Github/train/.arrow" - "data/Gutenberg (PG-19)/train/.arrow" - "data/HackerNews/train/.arrow" - "data/NIH ExPorter/train/.arrow" - "data/OpenSubtitles/train/.arrow" - "data/OpenWebText2/train/.arrow" - "data/PhilPapers/train/.arrow" - "data/Pile-CC/train/.arrow" - "data/PubMed Abstracts/train/.arrow" - "data/PubMed Central/train/.arrow" - "data/StackExchange/train/.arrow" - "data/UPSTO Backgrounds/train/.arrow" - "data/Ubuntu IRC/train/.arrow" - "data/Wikipedia (en)/train/.arrow" - "data/YoutubeSubtitles/train/.arrow" - split: test path: - "data/ArXiv/test/.arrow" - "data/BookCorpus2/test/.arrow" - "data/Books3/test/.arrow" - "data/DM Mathematics/test/.arrow" - "data/Enron Emails/test/.arrow" - "data/EuroParl/test/.arrow" - "data/FreeLaw/test/.arrow" - "data/Github/test/.arrow" - "data/Gutenberg (PG-19)/test/.arrow" - "data/HackerNews/test/.arrow" - "data/NIH ExPorter/test/.arrow" - "data/OpenSubtitles/test/.arrow" - "data/OpenWebText2/test/.arrow" - "data/PhilPapers/test/.arrow" - "data/Pile-CC/test/.arrow" - "data/PubMed Abstracts/test/.arrow" - "data/PubMed Central/test/.arrow" - "data/StackExchange/test/.arrow" - "data/UPSTO Backgrounds/test/.arrow" - "data/Ubuntu IRC/test/.arrow" - "data/Wikipedia (en)/test/.arrow" - "data/YoutubeSubtitles/test/.arrow" default: true - config_name: ArXiv data_files: - split: train path: "data/ArXiv/train/.arrow" - split: test path: "data/ArXiv/test/.arrow" - config_name: BookCorpus2 data_files: - split: train path: "data/BookCorpus2/train/.arrow" - split: test path: "data/BookCorpus2/test/.arrow" - config_name: Books3 data_files: - split: train path: "data/Books3/train/.arrow" - split: test path: "data/Books3/test/.arrow" - config_name: DM Mathematics data_files: - split: train path: "data/DM Mathematics/train/.arrow" - split: test path: "data/DM Mathematics/test/.arrow" - config_name: Enron Emails data_files: - split: train path: "data/Enron Emails/train/.arrow" - split: test path: "data/Enron Emails/test/.arrow" - config_name: EuroParl data_files: - split: train path: "data/EuroParl/train/.arrow" - split: test path: "data/EuroParl/test/.arrow" - config_name: FreeLaw data_files: - split: train path: "data/FreeLaw/train/.arrow" - split: test path: "data/FreeLaw/test/.arrow" - config_name: Github data_files: - split: train path: "data/Github/train/.arrow" - split: test path: "data/Github/test/.arrow" - config_name: Gutenberg (PG-19) data_files: - split: train path: "data/Gutenberg (PG-19)/train/.arrow" - split: test path: "data/Gutenberg (PG-19)/test/.arrow" - config_name: HackerNews data_files: - split: train path: "data/HackerNews/train/.arrow" - split: test path: "data/HackerNews/test/.arrow" - config_name: NIH ExPorter data_files: - split: train path: "data/NIH ExPorter/train/.arrow" - split: test path: "data/NIH ExPorter/test/.arrow" - config_name: OpenSubtitles data_files: - split: train path: "data/OpenSubtitles/train/.arrow" - split: test path: "data/OpenSubtitles/test/.arrow" - config_name: OpenWebText2 data_files: - split: train path: "data/OpenWebText2/train/.arrow" - split: test path: "data/OpenWebText2/test/.arrow" - config_name: PhilPapers data_files: - split: train path: "data/PhilPapers/train/.arrow" - split: test path: "data/PhilPapers/test/.arrow" - config_name: Pile-CC data_files: - split: train path: "data/Pile-CC/train/.arrow" - split: test path: "data/Pile-CC/test/.arrow" - config_name: PubMed Abstracts data_files: - split: train path: "data/PubMed Abstracts/train/.arrow" - split: test path: "data/PubMed Abstracts/test/.arrow" - config_name: PubMed Central data_files: - split: train path: "data/PubMed Central/train/.arrow" - split: test path: "data/PubMed Central/test/.arrow" - config_name: StackExchange data_files: - split: train path: "data/StackExchange/train/.arrow" - split: test path: "data/StackExchange/test/.arrow" - config_name: UPSTO Backgrounds data_files: - split: train path: "data/UPSTO Backgrounds/train/.arrow" - split: test path: "data/UPSTO Backgrounds/test/.arrow" - config_name: Ubuntu IRC data_files: - split: train path: "data/Ubuntu IRC/train/.arrow" - split: test path: "data/Ubuntu IRC/test/.arrow" - config_name: Wikipedia (en) data_files: - split: train path: "data/Wikipedia (en)/train/.arrow" - split: test path: "data/Wikipedia (en)/test/.arrow" - config_name: YoutubeSubtitles data_files: - split: train path: "data/YoutubeSubtitles/train/.arrow" - split: test path: "data/YoutubeSubtitles/test/.arrow" --- # Dataset description [The pile](https://arxiv.org/abs/2101.00027) is an 800GB dataset of english text designed by EleutherAI to train large-scale language models. The original version of the dataset can be found [here](https://huggingface.co/datasets/EleutherAI/pile). The dataset is divided into 22 smaller high-quality datasets. For more information each of them, please refer to [the datasheet for the pile](https://arxiv.org/abs/2201.07311). However, the current version of the dataset, available on the Hub, is not splitted accordingly. We had to solve this problem in order to improve the user experience when it comes to deal with the pile via the hub. Here is an instance of the pile ``` { 'meta': {'pile_set_name': 'Pile-CC'}, 'text': 'It is done, and submitted. You can play “Survival of the Tastiest” on Android, and on the web. Playing on...' } ``` We used the `meta` column to properly divide the dataset in subsets. Each instance `example` belongs to the subset `domain` and `domain = example['meta']['pile_set_name']`. By doing this, we were able to create a [new version of the pile](https://huggingface.co/datasets/ArmelR/sharded-pile) that is properly divided, each instance having a new column `domain`. We further splitted each subset in train/test (97%/3%) to build the current dataset which the following structure ``` data ArXiv train test BookCorpus2 train test Books3 train test ``` # Usage ```python from datasets import load_dataset dataset = load_dataset( "ArmelR/the-pile-splitted", subset_of_interest, num_proc=8 ) ``` Using `subset_of_interest = "default"` will load the whole dataset.	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open-llm-leaderboard/details_quantumaikr__open_llama_7b_hf	open-llm-leaderboard	2023-08-27T12:26:13Z	255	0	[ "region:us" ]	null	2023-08-18T00:01:02Z	--- pretty_name: Evaluation run of quantumaikr/open_llama_7b_hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [quantumaikr/open_llama_7b_hf](https://huggingface.co/quantumaikr/open_llama_7b_hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_quantumaikr__open_llama_7b_hf\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-07-19T17:01:48.631436](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__open_llama_7b_hf/blob/main/results_2023-07-19T17%3A01%3A48.631436.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2648279332452004,\n\ \ \"acc_stderr\": 0.03195749858994142,\n \"acc_norm\": 0.26548960439125074,\n\ \ \"acc_norm_stderr\": 0.03196726632461042,\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862661,\n \"mc2\": 0.4954484536663258,\n\ \ \"mc2_stderr\": 0.016312743256662564\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.23293515358361774,\n \"acc_stderr\": 0.012352507042617391,\n\ \ \"acc_norm\": 0.2645051194539249,\n \"acc_norm_stderr\": 0.012889272949313366\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.26199960167297354,\n\ \ \"acc_stderr\": 0.004388237557526716,\n \"acc_norm\": 0.26946823341963755,\n\ \ \"acc_norm_stderr\": 0.004427767996301633\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.31851851851851853,\n\ \ \"acc_stderr\": 0.040247784019771096,\n \"acc_norm\": 0.31851851851851853,\n\ \ \"acc_norm_stderr\": 0.040247784019771096\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.2894736842105263,\n \"acc_stderr\": 0.036906779861372814,\n\ \ \"acc_norm\": 0.2894736842105263,\n \"acc_norm_stderr\": 0.036906779861372814\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.21,\n\ \ \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n \ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.2490566037735849,\n \"acc_stderr\": 0.026616482980501704,\n\ \ \"acc_norm\": 0.2490566037735849,\n \"acc_norm_stderr\": 0.026616482980501704\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2708333333333333,\n\ \ \"acc_stderr\": 0.03716177437566016,\n \"acc_norm\": 0.2708333333333333,\n\ \ \"acc_norm_stderr\": 0.03716177437566016\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695236\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \"acc_norm\": 0.27,\n\ \ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768079,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768079\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.23699421965317918,\n\ \ \"acc_stderr\": 0.03242414757483098,\n \"acc_norm\": 0.23699421965317918,\n\ \ \"acc_norm_stderr\": 0.03242414757483098\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.16,\n \"acc_stderr\": 0.03684529491774708,\n \"acc_norm\": 0.16,\n\ \ \"acc_norm_stderr\": 0.03684529491774708\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.2425531914893617,\n \"acc_stderr\": 0.028020226271200214,\n\ \ \"acc_norm\": 0.2425531914893617,\n \"acc_norm_stderr\": 0.028020226271200214\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2807017543859649,\n\ \ \"acc_stderr\": 0.042270544512322,\n \"acc_norm\": 0.2807017543859649,\n\ \ \"acc_norm_stderr\": 0.042270544512322\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.23448275862068965,\n \"acc_stderr\": 0.035306258743465914,\n\ \ \"acc_norm\": 0.23448275862068965,\n \"acc_norm_stderr\": 0.035306258743465914\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643898,\n \"\ acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643898\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2222222222222222,\n\ \ \"acc_stderr\": 0.037184890068181146,\n \"acc_norm\": 0.2222222222222222,\n\ \ \"acc_norm_stderr\": 0.037184890068181146\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.3161290322580645,\n \"acc_stderr\": 0.02645087448904277,\n \"\ acc_norm\": 0.3161290322580645,\n \"acc_norm_stderr\": 0.02645087448904277\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.31527093596059114,\n \"acc_stderr\": 0.03269080871970186,\n \"\ acc_norm\": 0.31527093596059114,\n \"acc_norm_stderr\": 0.03269080871970186\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\"\ : 0.23,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.24848484848484848,\n \"acc_stderr\": 0.03374402644139405,\n\ \ \"acc_norm\": 0.24848484848484848,\n \"acc_norm_stderr\": 0.03374402644139405\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.31313131313131315,\n \"acc_stderr\": 0.033042050878136525,\n \"\ acc_norm\": 0.31313131313131315,\n \"acc_norm_stderr\": 0.033042050878136525\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.3005181347150259,\n \"acc_stderr\": 0.0330881859441575,\n\ \ \"acc_norm\": 0.3005181347150259,\n \"acc_norm_stderr\": 0.0330881859441575\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.2128205128205128,\n \"acc_stderr\": 0.020752423722128013,\n\ \ \"acc_norm\": 0.2128205128205128,\n \"acc_norm_stderr\": 0.020752423722128013\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.25555555555555554,\n \"acc_stderr\": 0.02659393910184408,\n \ \ \"acc_norm\": 0.25555555555555554,\n \"acc_norm_stderr\": 0.02659393910184408\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.3277310924369748,\n \"acc_stderr\": 0.030489911417673227,\n\ \ \"acc_norm\": 0.3277310924369748,\n \"acc_norm_stderr\": 0.030489911417673227\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.28440366972477066,\n \"acc_stderr\": 0.019342036587702588,\n \"\ acc_norm\": 0.28440366972477066,\n \"acc_norm_stderr\": 0.019342036587702588\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4074074074074074,\n \"acc_stderr\": 0.03350991604696042,\n \"\ acc_norm\": 0.4074074074074074,\n \"acc_norm_stderr\": 0.03350991604696042\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25980392156862747,\n \"acc_stderr\": 0.030778554678693254,\n \"\ acc_norm\": 0.25980392156862747,\n \"acc_norm_stderr\": 0.030778554678693254\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.189873417721519,\n \"acc_stderr\": 0.025530100460233497,\n \ \ \"acc_norm\": 0.189873417721519,\n \"acc_norm_stderr\": 0.025530100460233497\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.18834080717488788,\n\ \ \"acc_stderr\": 0.026241132996407273,\n \"acc_norm\": 0.18834080717488788,\n\ \ \"acc_norm_stderr\": 0.026241132996407273\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.22900763358778625,\n \"acc_stderr\": 0.036853466317118506,\n\ \ \"acc_norm\": 0.22900763358778625,\n \"acc_norm_stderr\": 0.036853466317118506\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.19008264462809918,\n \"acc_stderr\": 0.03581796951709282,\n \"\ acc_norm\": 0.19008264462809918,\n \"acc_norm_stderr\": 0.03581796951709282\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.21296296296296297,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.21296296296296297,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.22699386503067484,\n \"acc_stderr\": 0.032910995786157686,\n\ \ \"acc_norm\": 0.22699386503067484,\n \"acc_norm_stderr\": 0.032910995786157686\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.23214285714285715,\n\ \ \"acc_stderr\": 0.04007341809755806,\n \"acc_norm\": 0.23214285714285715,\n\ \ \"acc_norm_stderr\": 0.04007341809755806\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.3592233009708738,\n \"acc_stderr\": 0.04750458399041692,\n\ \ \"acc_norm\": 0.3592233009708738,\n \"acc_norm_stderr\": 0.04750458399041692\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.20085470085470086,\n\ \ \"acc_stderr\": 0.026246772946890477,\n \"acc_norm\": 0.20085470085470086,\n\ \ \"acc_norm_stderr\": 0.026246772946890477\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.2656449553001277,\n\ \ \"acc_stderr\": 0.01579430248788873,\n \"acc_norm\": 0.2656449553001277,\n\ \ \"acc_norm_stderr\": 0.01579430248788873\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.2138728323699422,\n \"acc_stderr\": 0.022075709251757183,\n\ \ \"acc_norm\": 0.2138728323699422,\n \"acc_norm_stderr\": 0.022075709251757183\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24916201117318434,\n\ \ \"acc_stderr\": 0.01446589382985993,\n \"acc_norm\": 0.24916201117318434,\n\ \ \"acc_norm_stderr\": 0.01446589382985993\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.27450980392156865,\n \"acc_stderr\": 0.025553169991826514,\n\ \ \"acc_norm\": 0.27450980392156865,\n \"acc_norm_stderr\": 0.025553169991826514\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2861736334405145,\n\ \ \"acc_stderr\": 0.025670259242188943,\n \"acc_norm\": 0.2861736334405145,\n\ \ \"acc_norm_stderr\": 0.025670259242188943\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2623456790123457,\n \"acc_stderr\": 0.024477222856135104,\n\ \ \"acc_norm\": 0.2623456790123457,\n \"acc_norm_stderr\": 0.024477222856135104\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.25886524822695034,\n \"acc_stderr\": 0.026129572527180844,\n \ \ \"acc_norm\": 0.25886524822695034,\n \"acc_norm_stderr\": 0.026129572527180844\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2438070404172099,\n\ \ \"acc_stderr\": 0.010966507972178479,\n \"acc_norm\": 0.2438070404172099,\n\ \ \"acc_norm_stderr\": 0.010966507972178479\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4485294117647059,\n \"acc_stderr\": 0.030211479609121593,\n\ \ \"acc_norm\": 0.4485294117647059,\n \"acc_norm_stderr\": 0.030211479609121593\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.24673202614379086,\n \"acc_stderr\": 0.0174408203674025,\n \ \ \"acc_norm\": 0.24673202614379086,\n \"acc_norm_stderr\": 0.0174408203674025\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.24545454545454545,\n\ \ \"acc_stderr\": 0.041220665028782834,\n \"acc_norm\": 0.24545454545454545,\n\ \ \"acc_norm_stderr\": 0.041220665028782834\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.2938775510204082,\n \"acc_stderr\": 0.029162738410249762,\n\ \ \"acc_norm\": 0.2938775510204082,\n \"acc_norm_stderr\": 0.029162738410249762\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.23383084577114427,\n\ \ \"acc_stderr\": 0.029929415408348405,\n \"acc_norm\": 0.23383084577114427,\n\ \ \"acc_norm_stderr\": 0.029929415408348405\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542127,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542127\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.15060240963855423,\n\ \ \"acc_stderr\": 0.02784386378726433,\n \"acc_norm\": 0.15060240963855423,\n\ \ \"acc_norm_stderr\": 0.02784386378726433\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.23976608187134502,\n \"acc_stderr\": 0.03274485211946956,\n\ \ \"acc_norm\": 0.23976608187134502,\n \"acc_norm_stderr\": 0.03274485211946956\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862661,\n \"mc2\": 0.4954484536663258,\n\ \ \"mc2_stderr\": 0.016312743256662564\n }\n}\n```" repo_url: https://huggingface.co/quantumaikr/open_llama_7b_hf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|arc:challenge\|25_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hellaswag\|10_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T17:01:48.631436.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T17:01:48.631436.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T17_01_48.631436 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T17:01:48.631436.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T17:01:48.631436.parquet' - config_name: results data_files: - split: 2023_07_19T17_01_48.631436 path: - results_2023-07-19T17:01:48.631436.parquet - split: latest path: - results_2023-07-19T17:01:48.631436.parquet --- # Dataset Card for Evaluation run of quantumaikr/open_llama_7b_hf ## Dataset Description - Homepage: - Repository: https://huggingface.co/quantumaikr/open_llama_7b_hf - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [quantumaikr/open_llama_7b_hf](https://huggingface.co/quantumaikr/open_llama_7b_hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_quantumaikr__open_llama_7b_hf", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-07-19T17:01:48.631436](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__open_llama_7b_hf/blob/main/results_2023-07-19T17%3A01%3A48.631436.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2648279332452004, "acc_stderr": 0.03195749858994142, "acc_norm": 0.26548960439125074, "acc_norm_stderr": 0.03196726632461042, "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862661, "mc2": 0.4954484536663258, "mc2_stderr": 0.016312743256662564 }, "harness\|arc:challenge\|25": { "acc": 0.23293515358361774, "acc_stderr": 0.012352507042617391, "acc_norm": 0.2645051194539249, "acc_norm_stderr": 0.012889272949313366 }, "harness\|hellaswag\|10": { "acc": 0.26199960167297354, "acc_stderr": 0.004388237557526716, "acc_norm": 0.26946823341963755, "acc_norm_stderr": 0.004427767996301633 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.31851851851851853, "acc_stderr": 0.040247784019771096, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.040247784019771096 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.2894736842105263, "acc_stderr": 0.036906779861372814, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.036906779861372814 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.2490566037735849, "acc_stderr": 0.026616482980501704, "acc_norm": 0.2490566037735849, "acc_norm_stderr": 0.026616482980501704 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2708333333333333, "acc_stderr": 0.03716177437566016, "acc_norm": 0.2708333333333333, "acc_norm_stderr": 0.03716177437566016 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.23699421965317918, "acc_stderr": 0.03242414757483098, "acc_norm": 0.23699421965317918, "acc_norm_stderr": 0.03242414757483098 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.16, "acc_stderr": 0.03684529491774708, "acc_norm": 0.16, "acc_norm_stderr": 0.03684529491774708 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.2425531914893617, "acc_stderr": 0.028020226271200214, "acc_norm": 0.2425531914893617, "acc_norm_stderr": 0.028020226271200214 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.23448275862068965, "acc_stderr": 0.035306258743465914, "acc_norm": 0.23448275862068965, "acc_norm_stderr": 0.035306258743465914 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.25132275132275134, "acc_stderr": 0.022340482339643898, "acc_norm": 0.25132275132275134, "acc_norm_stderr": 0.022340482339643898 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.037184890068181146, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.037184890068181146 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.3161290322580645, "acc_stderr": 0.02645087448904277, "acc_norm": 0.3161290322580645, "acc_norm_stderr": 0.02645087448904277 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.31527093596059114, "acc_stderr": 0.03269080871970186, "acc_norm": 0.31527093596059114, "acc_norm_stderr": 0.03269080871970186 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.24848484848484848, "acc_stderr": 0.03374402644139405, "acc_norm": 0.24848484848484848, "acc_norm_stderr": 0.03374402644139405 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.31313131313131315, "acc_stderr": 0.033042050878136525, "acc_norm": 0.31313131313131315, "acc_norm_stderr": 0.033042050878136525 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.3005181347150259, "acc_stderr": 0.0330881859441575, "acc_norm": 0.3005181347150259, "acc_norm_stderr": 0.0330881859441575 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.2128205128205128, "acc_stderr": 0.020752423722128013, "acc_norm": 0.2128205128205128, "acc_norm_stderr": 0.020752423722128013 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.25555555555555554, "acc_stderr": 0.02659393910184408, "acc_norm": 0.25555555555555554, "acc_norm_stderr": 0.02659393910184408 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.3277310924369748, "acc_stderr": 0.030489911417673227, "acc_norm": 0.3277310924369748, "acc_norm_stderr": 0.030489911417673227 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.28440366972477066, "acc_stderr": 0.019342036587702588, "acc_norm": 0.28440366972477066, "acc_norm_stderr": 0.019342036587702588 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4074074074074074, "acc_stderr": 0.03350991604696042, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.03350991604696042 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25980392156862747, "acc_stderr": 0.030778554678693254, "acc_norm": 0.25980392156862747, "acc_norm_stderr": 0.030778554678693254 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.189873417721519, "acc_stderr": 0.025530100460233497, "acc_norm": 0.189873417721519, "acc_norm_stderr": 0.025530100460233497 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.18834080717488788, "acc_stderr": 0.026241132996407273, "acc_norm": 0.18834080717488788, "acc_norm_stderr": 0.026241132996407273 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.22900763358778625, "acc_stderr": 0.036853466317118506, "acc_norm": 0.22900763358778625, "acc_norm_stderr": 0.036853466317118506 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.19008264462809918, "acc_stderr": 0.03581796951709282, "acc_norm": 0.19008264462809918, "acc_norm_stderr": 0.03581796951709282 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.21296296296296297, "acc_stderr": 0.0395783547198098, "acc_norm": 0.21296296296296297, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.22699386503067484, "acc_stderr": 0.032910995786157686, "acc_norm": 0.22699386503067484, "acc_norm_stderr": 0.032910995786157686 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.23214285714285715, "acc_stderr": 0.04007341809755806, "acc_norm": 0.23214285714285715, "acc_norm_stderr": 0.04007341809755806 }, "harness\|hendrycksTest-management\|5": { "acc": 0.3592233009708738, "acc_stderr": 0.04750458399041692, "acc_norm": 0.3592233009708738, "acc_norm_stderr": 0.04750458399041692 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.20085470085470086, "acc_stderr": 0.026246772946890477, "acc_norm": 0.20085470085470086, "acc_norm_stderr": 0.026246772946890477 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.2656449553001277, "acc_stderr": 0.01579430248788873, "acc_norm": 0.2656449553001277, "acc_norm_stderr": 0.01579430248788873 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.2138728323699422, "acc_stderr": 0.022075709251757183, "acc_norm": 0.2138728323699422, "acc_norm_stderr": 0.022075709251757183 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.24916201117318434, "acc_stderr": 0.01446589382985993, "acc_norm": 0.24916201117318434, "acc_norm_stderr": 0.01446589382985993 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.27450980392156865, "acc_stderr": 0.025553169991826514, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.025553169991826514 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.2861736334405145, "acc_stderr": 0.025670259242188943, "acc_norm": 0.2861736334405145, "acc_norm_stderr": 0.025670259242188943 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2623456790123457, "acc_stderr": 0.024477222856135104, "acc_norm": 0.2623456790123457, "acc_norm_stderr": 0.024477222856135104 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.25886524822695034, "acc_stderr": 0.026129572527180844, "acc_norm": 0.25886524822695034, "acc_norm_stderr": 0.026129572527180844 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2438070404172099, "acc_stderr": 0.010966507972178479, "acc_norm": 0.2438070404172099, "acc_norm_stderr": 0.010966507972178479 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4485294117647059, "acc_stderr": 0.030211479609121593, "acc_norm": 0.4485294117647059, "acc_norm_stderr": 0.030211479609121593 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.24673202614379086, "acc_stderr": 0.0174408203674025, "acc_norm": 0.24673202614379086, "acc_norm_stderr": 0.0174408203674025 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.24545454545454545, "acc_stderr": 0.041220665028782834, "acc_norm": 0.24545454545454545, "acc_norm_stderr": 0.041220665028782834 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.2938775510204082, "acc_stderr": 0.029162738410249762, "acc_norm": 0.2938775510204082, "acc_norm_stderr": 0.029162738410249762 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.23383084577114427, "acc_stderr": 0.029929415408348405, "acc_norm": 0.23383084577114427, "acc_norm_stderr": 0.029929415408348405 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.15060240963855423, "acc_stderr": 0.02784386378726433, "acc_norm": 0.15060240963855423, "acc_norm_stderr": 0.02784386378726433 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.23976608187134502, "acc_stderr": 0.03274485211946956, "acc_norm": 0.23976608187134502, "acc_norm_stderr": 0.03274485211946956 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862661, "mc2": 0.4954484536663258, "mc2_stderr": 0.016312743256662564 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7012141346931458, -0.863899290561676, 0.2847556471824646, 0.15615148842334747, -0.1956108957529068, -0.012524503283202648, 0.06373583525419235, -0.19044683873653412, 0.5750389099121094, -0.07822232693433762, -0.4525921046733856, -0.677760660648346, -0.42687085270881653, 0.2549850344657898, -0.023382849991321564, 0.7994232773780823, -0.1928790956735611, -0.1355481743812561, 0.09305844455957413, -0.01874825358390808, -0.22888688743114471, -0.3015958368778229, -0.4683307111263275, 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open-llm-leaderboard/details_KoboldAI__GPT-J-6B-Skein	open-llm-leaderboard	2023-10-18T23:06:45Z	255	0	[ "region:us" ]	null	2023-08-18T11:48:13Z	--- pretty_name: Evaluation run of KoboldAI/GPT-J-6B-Skein dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [KoboldAI/GPT-J-6B-Skein](https://huggingface.co/KoboldAI/GPT-J-6B-Skein) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_KoboldAI__GPT-J-6B-Skein\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-18T23:06:33.699776](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__GPT-J-6B-Skein/blob/main/results_2023-10-18T23-06-33.699776.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0008389261744966443,\n\ \ \"em_stderr\": 0.0002964962989801232,\n \"f1\": 0.04856333892617463,\n\ \ \"f1_stderr\": 0.0012019515785831486,\n \"acc\": 0.32646051605668597,\n\ \ \"acc_stderr\": 0.008392267793964117\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0008389261744966443,\n \"em_stderr\": 0.0002964962989801232,\n\ \ \"f1\": 0.04856333892617463,\n \"f1_stderr\": 0.0012019515785831486\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.014404852160727824,\n \ \ \"acc_stderr\": 0.0032820559171369505\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6385161799526441,\n \"acc_stderr\": 0.013502479670791283\n\ \ }\n}\n```" repo_url: https://huggingface.co/KoboldAI/GPT-J-6B-Skein leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|arc:challenge\|25_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T15:49:07.734333.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_18T23_06_33.699776 path: - '/details_harness\|drop\|3_2023-10-18T23-06-33.699776.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-18T23-06-33.699776.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_18T23_06_33.699776 path: - '/details_harness\|gsm8k\|5_2023-10-18T23-06-33.699776.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-18T23-06-33.699776.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hellaswag\|10_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:49:07.734333.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:49:07.734333.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T15_49_07.734333 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T15:49:07.734333.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T15:49:07.734333.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_18T23_06_33.699776 path: - '/details_harness\|winogrande\|5_2023-10-18T23-06-33.699776.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-18T23-06-33.699776.parquet' - config_name: results data_files: - split: 2023_07_19T15_49_07.734333 path: - results_2023-07-19T15:49:07.734333.parquet - split: 2023_10_18T23_06_33.699776 path: - results_2023-10-18T23-06-33.699776.parquet - split: latest path: - results_2023-10-18T23-06-33.699776.parquet --- # Dataset Card for Evaluation run of KoboldAI/GPT-J-6B-Skein ## Dataset Description - Homepage: - Repository: https://huggingface.co/KoboldAI/GPT-J-6B-Skein - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [KoboldAI/GPT-J-6B-Skein](https://huggingface.co/KoboldAI/GPT-J-6B-Skein) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_KoboldAI__GPT-J-6B-Skein", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-18T23:06:33.699776](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__GPT-J-6B-Skein/blob/main/results_2023-10-18T23-06-33.699776.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0008389261744966443, "em_stderr": 0.0002964962989801232, "f1": 0.04856333892617463, "f1_stderr": 0.0012019515785831486, "acc": 0.32646051605668597, "acc_stderr": 0.008392267793964117 }, "harness\|drop\|3": { "em": 0.0008389261744966443, "em_stderr": 0.0002964962989801232, "f1": 0.04856333892617463, "f1_stderr": 0.0012019515785831486 }, "harness\|gsm8k\|5": { "acc": 0.014404852160727824, "acc_stderr": 0.0032820559171369505 }, "harness\|winogrande\|5": { "acc": 0.6385161799526441, "acc_stderr": 0.013502479670791283 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.42452239990234375, -0.6810726523399353, 0.2546009421348572, 0.1478416919708252, -0.2572280168533325, 0.046879906207323074, -0.4203130900859833, -0.20658572018146515, 0.3344079256057739, 0.5898637175559998, -0.6457902789115906, -0.8799936175346375, -0.7045885920524597, 0.15149913728237152, -0.07631395757198334, 1.2213613986968994, -0.17203347384929657, -0.239420548081398, 0.13150054216384888, -0.2966464161872864, -0.3368694484233856, -0.4330359995365143, -0.5323896408081055, 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open-llm-leaderboard/details_codellama__CodeLlama-13b-Python-hf	open-llm-leaderboard	2023-09-23T16:36:32Z	255	0	[ "region:us" ]	null	2023-08-25T16:41:40Z	--- pretty_name: Evaluation run of codellama/CodeLlama-13b-Python-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [codellama/CodeLlama-13b-Python-hf](https://huggingface.co/codellama/CodeLlama-13b-Python-hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_codellama__CodeLlama-13b-Python-hf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T16:36:19.562140](https://huggingface.co/datasets/open-llm-leaderboard/details_codellama__CodeLlama-13b-Python-hf/blob/main/results_2023-09-23T16-36-19.562140.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0012583892617449664,\n\ \ \"em_stderr\": 0.00036305608931190423,\n \"f1\": 0.04866296140939616,\n\ \ \"f1_stderr\": 0.001201832323988023,\n \"acc\": 0.36839214132827663,\n\ \ \"acc_stderr\": 0.010571059008977151\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0012583892617449664,\n \"em_stderr\": 0.00036305608931190423,\n\ \ \"f1\": 0.04866296140939616,\n \"f1_stderr\": 0.001201832323988023\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08642911296436695,\n \ \ \"acc_stderr\": 0.007740044337103802\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6503551696921863,\n \"acc_stderr\": 0.0134020736808505\n\ \ }\n}\n```" repo_url: https://huggingface.co/codellama/CodeLlama-13b-Python-hf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|arc:challenge\|25_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|arc:challenge\|25_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-26T05:23:55.023532.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T16_36_19.562140 path: - '/details_harness\|drop\|3_2023-09-23T16-36-19.562140.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-23T16-36-19.562140.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T16_36_19.562140 path: - '/details_harness\|gsm8k\|5_2023-09-23T16-36-19.562140.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-23T16-36-19.562140.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hellaswag\|10_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hellaswag\|10_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-25T16:41:17.923081.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T05:23:55.023532.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T05:23:55.023532.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_25T16_41_17.923081 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-25T16:41:17.923081.parquet' - split: 2023_08_26T05_23_55.023532 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-26T05:23:55.023532.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-26T05:23:55.023532.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T16_36_19.562140 path: - '/details_harness\|winogrande\|5_2023-09-23T16-36-19.562140.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-23T16-36-19.562140.parquet' - config_name: results data_files: - split: 2023_08_25T16_41_17.923081 path: - results_2023-08-25T16:41:17.923081.parquet - split: 2023_08_26T05_23_55.023532 path: - results_2023-08-26T05:23:55.023532.parquet - split: 2023_09_23T16_36_19.562140 path: - results_2023-09-23T16-36-19.562140.parquet - split: latest path: - results_2023-09-23T16-36-19.562140.parquet --- # Dataset Card for Evaluation run of codellama/CodeLlama-13b-Python-hf ## Dataset Description - Homepage: - Repository: https://huggingface.co/codellama/CodeLlama-13b-Python-hf - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [codellama/CodeLlama-13b-Python-hf](https://huggingface.co/codellama/CodeLlama-13b-Python-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_codellama__CodeLlama-13b-Python-hf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T16:36:19.562140](https://huggingface.co/datasets/open-llm-leaderboard/details_codellama__CodeLlama-13b-Python-hf/blob/main/results_2023-09-23T16-36-19.562140.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190423, "f1": 0.04866296140939616, "f1_stderr": 0.001201832323988023, "acc": 0.36839214132827663, "acc_stderr": 0.010571059008977151 }, "harness\|drop\|3": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190423, "f1": 0.04866296140939616, "f1_stderr": 0.001201832323988023 }, "harness\|gsm8k\|5": { "acc": 0.08642911296436695, "acc_stderr": 0.007740044337103802 }, "harness\|winogrande\|5": { "acc": 0.6503551696921863, "acc_stderr": 0.0134020736808505 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.40833815932273865, -0.6665675044059753, 0.21926069259643555, 0.3229171335697174, -0.05057523027062416, 0.1441216766834259, -0.4672550559043884, -0.16972705721855164, 0.3932577669620514, 0.5296080112457275, -0.6558715105056763, -0.9392716884613037, -0.6058803796768188, 0.1817651093006134, -0.19946496188640594, 1.1364145278930664, -0.2485603243112564, -0.2447485625743866, -0.03626515343785286, -0.2505817413330078, -0.2989402711391449, -0.4495689570903778, -0.37212127447128296, 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distil-whisper/librispeech_asr-prompted	distil-whisper	2023-09-19T09:31:43Z	255	0	[ "region:us" ]	null	2023-09-19T08:45:04Z	--- dataset_info: config_name: all features: - name: file dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: speaker_id dtype: int64 - name: chapter_id dtype: int64 - name: id dtype: string - name: whisper_transcript_unprompted dtype: string - name: whisper_transcript dtype: string splits: - name: train.clean.100 num_bytes: 6641615051.062 num_examples: 28539 - name: train.clean.360 num_bytes: 23977966959.828 num_examples: 104014 - name: train.other.500 num_bytes: 31918849882.584 num_examples: 148688 - name: validation.clean num_bytes: 361026354.966 num_examples: 2703 - name: validation.other num_bytes: 338707588.648 num_examples: 2864 - name: test.clean num_bytes: 369123744.42 num_examples: 2620 - name: test.other num_bytes: 353861942.154 num_examples: 2939 download_size: 61926395211 dataset_size: 63961151523.662 configs: - config_name: all data_files: - split: train.clean.100 path: all/train.clean.100-* - split: train.clean.360 path: all/train.clean.360-* - split: train.other.500 path: all/train.other.500-* - split: validation.clean path: all/validation.clean-* - split: validation.other path: all/validation.other-* - split: test.clean path: all/test.clean-* - split: test.other path: all/test.other-* --- # Dataset Card for "librispeech_asr-prompted" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.5870044231414795, -0.2610858976840973, 0.09652170538902283, 0.31823158264160156, -0.20171725749969482, -0.11276346445083618, 0.14466898143291473, -0.1711641550064087, 0.8571920990943909, 0.40276893973350525, -0.9202967286109924, -0.5156440734863281, -0.4871358275413513, -0.2567831575870514, -0.6118707060813904, 1.3020005226135254, 0.11700199544429779, 0.2287520170211792, -0.30972525477409363, -0.27435585856437683, 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punwaiw/DiffusionJockey	punwaiw	2023-12-04T01:15:04Z	255	0	[ "region:us" ]	null	2023-11-17T21:55:52Z	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 13316574561.25 num_examples: 17110 download_size: 13312875795 dataset_size: 13316574561.25 --- # Dataset Card for "DiffusionJockey" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.4506036937236786, -0.5972162485122681, 0.3370514512062073, 0.32410815358161926, -0.17538723349571228, 0.1141558438539505, 0.47050902247428894, -0.1650947630405426, 1.0070685148239136, 0.3445186913013458, -0.7421624064445496, -0.9004316926002502, -0.8639001250267029, -0.5150688290596008, -0.3253266513347626, 1.2031913995742798, 0.013429502956569195, 0.11616169661283493, -0.5036596059799194, -0.11616535484790802, -0.463919073343277, -0.25208351016044617, -0.9780925512313843, -0.7705655694007874, 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Graphcore/vqa-lxmert	Graphcore	2022-10-25T08:59:34Z	254	0	[ "language:en", "license:cc-by-4.0", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en license: - cc-by-4.0 ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 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anukaver/EstQA	anukaver	2021-04-29T15:34:29Z	254	0	[ "language:et", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: et --- # Estonian Question Answering dataset * Dataset for extractive question answering in Estonian. It is based on Wikipedia articles, pre-filtered via PageRank. Annotation was done by one person. * Train set includes 776 context-question-answer triplets. There are several possible answers per question, each in a separate triplet. Number of different questions is 512. * Test set includes 603 samples. Each sample contains one or more golden answers. Altogether there are 892 golden ansewrs. ### Change log Test set v1.1 adds some more golden answers. ### Reference If you use this dataset for research, please cite the following paper: ``` @mastersthesis{mastersthesis, author = {Anu Käver}, title = {Extractive Question Answering for Estonian Language}, school = {Tallinn University of Technology (TalTech)}, year = 2021 } ```	[ -0.5153180956840515, -0.9591299891471863, 0.3626801073551178, -0.032444924116134644, -0.20086918771266937, -0.1995934545993805, 0.06300164014101028, -0.3216390907764435, 0.28748688101768494, 0.5316095948219299, -0.6872811317443848, -0.3607088327407837, -0.4653971791267395, 0.6036630868911743, -0.41309282183647156, 0.9796571731567383, -0.0638568252325058, 0.32728493213653564, -0.08757773041725159, -0.15602374076843262, -0.7532784938812256, -0.3344421684741974, -0.5704665780067444, 0.4280172884464264, 0.4774947762489319, 1.0705316066741943, 0.325234055519104, 0.4557364583015442, 0.48039719462394714, 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clarin-pl/2021-punctuation-restoration	clarin-pl	2022-08-29T16:39:18Z	254	1	[ "task_categories:automatic-speech-recognition", "annotations_creators:crowdsourced", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:n<1K", "language:pl", "region:us" ]	[ "automatic-speech-recognition" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language: - pl language_creators: - crowdsourced license: [] multilinguality: - monolingual pretty_name: 2021-punctuation-restoration size_categories: - n<1K source_datasets: [] tags: [] task_categories: - automatic-speech-recognition task_ids: [] --- # Punctuation restoration from read text Restore punctuation marks from the output of an ASR system. ## Motivation Speech transcripts generated by Automatic Speech Recognition (ASR) systems typically do not contain any punctuation or capitalization. In longer stretches of automatically recognized speech, the lack of punctuation affects the general clarity of the output text [1]. The primary purpose of punctuation (PR) and capitalization restoration (CR) as a distinct natural language processing (NLP) task is to improve the legibility of ASR-generated text, and possibly other types of texts without punctuation. Aside from their intrinsic value, PR and CR may improve the performance of other NLP aspects such as Named Entity Recognition (NER), part-of-speech (POS) and semantic parsing or spoken dialog segmentation [2, 3]. As useful as it seems, It is hard to systematically evaluate PR on transcripts of conversational language; mainly because punctuation rules can be ambiguous even for originally written texts, and the very nature of naturally-occurring spoken language makes it difficult to identify clear phrase and sentence boundaries [4,5]. Given these requirements and limitations, a PR task based on a redistributable corpus of read speech was suggested. 1200 texts included in this collection (totaling over 240,000 words) were selected from two distinct sources: WikiNews and WikiTalks. Punctuation found in these sources should be approached with some reservation when used for evaluation: these are original texts and may contain some user-induced errors and bias. The texts were read out by over a hundred different speakers. Original texts with punctuation were forced-aligned with recordings and used as the ideal ASR output. The goal of the task is to provide a solution for restoring punctuation in the test set collated for this task. The test set consists of time-aligned ASR transcriptions of read texts from the two sources. Participants are encouraged to use both text-based and speech-derived features to identify punctuation symbols (e.g. multimodal framework [6]). In addition, the train set is accompanied by reference text corpora of WikiNews and WikiTalks data that can be used in training and fine-tuning punctuation models. ## Task description The purpose of this task is to restore punctuation in the ASR recognition of texts read out loud. ![](https://poleval.github.io/2021-punctuation-restoration/img/image001.png) Input ('tokens' column): sequence of tokens Output ('tags' column): sequence of tags Measurements: F1-score (seqeval) Example: Input: `['selekcjoner', 'szosowej', 'kadry', 'elity', 'mężczyzn', 'piotr', 'wadecki', 'ogłosił', '27', 'marca', '2008', 'r', 'szeroki', 'skład', 'zawodników', 'którzy', 'będą', 'rywalizować', 'o', 'miejsce', 'w', 'reprezentacji', 'na', 'tour', 'de', 'pologne', 'lista', 'liczy', '22', 'nazwiska', 'zawodników', 'zarówno', 'z', 'zagranicznych', 'jaki', 'i', 'polskich', 'ekip', 'spośród', '22', 'wybrańców', 'selekcjonera', 'do', 'składu', 'dostanie', 'się', 'tylko', 'ośmiu', 'kolarzy', 'którzy', 'we', 'wrześniu', 'będą', 'rywalizować', 'z', 'najlepszymi', 'grupami', 'kolarskimi', 'na', 'świecie', 'w', 'kręgu', 'zainteresowania', 'wadeckiego', 'znajduje', 'się', 'także', 'pięciu', 'innych', 'zawodników', 'ale', 'oni', 'prawdopodobnie', 'wystartują', 'w', 'polskim', 'tourze', 'w', 'szeregach', 'swoich', 'ekip', 'szeroka', 'kadra', 'na', 'tour', 'de', 'pologne', 'dariusz', 'baranowski', 'łukasz', 'bodnar', 'bartosz', 'huzarski', 'błażej', 'janiaczyk', 'tomasz', 'kiendyś', 'mateusz', 'komar', 'tomasz', 'lisowicz', 'piotr', 'mazur', 'jacek', 'morajko', 'przemysław', 'niemiec', 'marek', 'rutkiewicz', 'krzysztof', 'szczawiński', 'mateusz', 'taciak', 'adam', 'wadecki', 'mariusz', 'witecki', 'piotr', 'zaradny', 'piotr', 'zieliński', 'mateusz', 'mróz', 'marek', 'wesoły', 'jarosław', 'rębiewski', 'robert', 'radosz', 'jarosław', 'dąbrowski']` Input (translated by DeepL): `the selector of the men's elite road cycling team piotr wadecki announced on march 27, 2008 a wide line-up of riders who will compete for a place in the national team for the tour de pologne the list includes 22 names of riders both from foreign and Polish teams out of the 22 selected by the selector only eight riders will get into the line-up who in September will compete with the best cycling groups in the world wadecki's circle of interest also includes five other cyclists, but they will probably compete in the Polish tour in the ranks of their teams wide cadre for the tour de pologne dariusz baranowski łukasz bodnar bartosz huzarski błażej janiaczyk tomasz kiendyś mateusz komar tomasz lisowicz piotr mazur jacek morajko przemysław german marek rutkiewicz krzysztof szczawiński mateusz taciak adam wadecki mariusz witecki piotr zaradny piotr zieliński mateusz mróz marek wesoły jarosław rębiewski robert radosz jarosław dąbrowski` Output: `['O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-.', 'O', 'O', 'B-,', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-.', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-,', 'O', 'O', 'O', 'B-.', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-,', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-.', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-,', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-.', 'O', 'O', 'O', 'O', 'O', 'B-:', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O']` ## Dataset – WikiPunct WikiPunct is a crowdsourced text and audio data set of Polish Wikipedia pages read out loud by Polish lectors. The dataset is divided into two parts:conversational(WikiTalks)and information (WikiNews). Over a hundred people were involved in the production of the audio component. The total length of audio data reaches almost thirty-six hours, including the test set. Steps were taken to balance the male-to-female ratio. WikiPuncthas over thirty-two thousand texts and 1200 audio files, one thousand in the training set and two hundred in the test set. There is a transcript of automatically recognized speech and force-aligned text for each text. The details behind the data format and evaluation metrics are presented below in the respective sections. Statistics: - Text: - ver thirty-two thousand texts; WikiNews ca. 15,000, WikiTalks ca. 17,000; - Audio: - Selection procedure: - randomly selected WikiNews (80% that is equal 800 entries for the training set) with the word count above 150 words and smaller than 300 words; - randomly selected WikiTalks (20%) with word the count above 150 words but smaller than 300 words and at least one question mark - Data set split - Training data: 1000 recordings - Test data: at 274 recordings - Speakers: - Polish male: 51 speakers, 16.7 hours of speech - Polish female: 54 speakers, 19 hours of speech Data splits \| Subset \| Cardinality (texts) \| \| ----------- \| ----------------------: \| \| train \| 800 \| \| dev \| 0 \| \| test \| 200 \| Class distribution (without "O") \| Class \| train \| validation \| test \| \|:--------\|--------:\|-------------:\|-------:\| \| B-. \| 0.419 \| - \| 0.416 \| \| B-, \| 0.406 \| - \| 0.403 \| \| B-- \| 0.097 \| - \| 0.099 \| \| B-: \| 0.037 \| - \| 0.052 \| \| B-? \| 0.032 \| - \| 0.024 \| \| B-! \| 0.005 \| - \| 0.004 \| \| B-; \| 0.004 \| - \| 0.002 \| Punctuation for raw text: \| \| symbol \| mean \| median \| max \| sum \| included \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| fullstop \| . \| 12.44 \| 7.0 \| 1129.0 \| 404 378 \| yes \| \| comma \| , \| 10.97 \| 5.0 \| 1283.0 \| 356 678 \| yes \| \| question\_mark \| ? \| 0.83 \| 0.0 \| 130.0 \| 26 879 \| yes \| \| exclamation\_mark \| ! \| 0.22 \| 0.0 \| 55.0 \| 7 164 \| yes \| \| hyphen \| - \| 2.64 \| 1.0 \| 363.0 \| 81 190 \| yes \| \| colon \| : \| 1.49 \| 0.0 \| 202.0 \| 44 995 \| yes \| \| ellipsis \| ... \| 0.27 \| 0.0 \| 60.0 \| 8 882 \| yes \| \| semicolon \| ; \| 0.13 \| 0.0 \| 51.0 \| 4 270 \| no \| \| quote \| " \| 3.64 \| 0.0 \| 346.0 \| 116 874 \| no \| \| words \| \| 169.50 \| 89.0 \| 17252.0 \| 5 452 032 \| - \| The dataset is divided into two parts: conversational (WikiTalks) and information (WikiNews). Part 1. WikiTalks Data scraped from Polish Wikipedia Talk pages. Talk pages, also known as discussion pages, are administration pages with editorial details and discussions for Wikipedia articles.. Talk pages were scrapped from the web using a list of article titles shared alongside Wikipedia dump archives. Wikipedia Talk pages serve as conversational data. Here, users communicate with each other by writing comments. Vocabulary and punctuation errors are expected. This data set covers 20% of the spoken data. Example: - wikitalks001948: Cóż za bzdury tu powypisywane! Fra Diavolo starał się nie dopuścić do upadku Republiki Partenopejskiej? Kto to wymyślił?! Człowiek ten był jednym z najżarliwszych wrogów francuskiej okupacji, a za zasługi w wypędzeniu Francuzów został mianowany pułkownikiem w królewskiej armii z prawdziwie królewską pensją. Bez niego wyzwolenie, nazywać to tak czy też nie, północnej części królestwa byłoby dużo trudniejsze, bo dysponował siłą kilku tysięcy sprawnych w boju i umiejętnie wziętych w karby rzezimieszków. Toteż armia Burbonów nie pokonywała go, jak to się twierdzi w artykule, lecz ściśle współpracowała. Redaktorów zachęcam do jak najszybszej korekty artykułu, bo aktualnie jest obrazą dla ambicji Wikipedii. 91.199.250.17 - wikitalks008902: Stare wątki w dyskusji przeniosłem do archiwum. Od prawie roku dyskusja w nich nie była kontynuowana. Sławek Borewicz Part 2. WikiNews Wikinews is a free-content news wiki and a project of the Wikimedia Foundation. The site works through collaborative journalism. The data was scraped directly from wikinews dump archive. The overall text quality is high, but vocabulary and punctuation errors may occur. This data set covers 80% of the spoken data. Example: - wikinews222361: Misja STS-127 promu kosmicznego Endeavour do Międzynarodowej Stacji Kosmicznej została przełożona ze względu na wyciek wodoru. Podczas procesu napełniania zewnętrznego zbiornika paliwem, część ciekłego wodoru przemieniła się w gaz i przedostała się do systemu odpowietrzania. System ten jest używany do bezpiecznego odprowadzania nadmiaru wodoru z platformy startowej 39A do Centrum Lotów Kosmicznych imienia Johna F. Kennedy'ego. Początek misji miał mieć miejsce dzisiaj, o godzinie 13:17. Ze względu jednak na awarię, najbliższa możliwa data startu wahadłowca to środa 17 czerwca, jednak na ten dzień NASA na Przylądku Canaveral zaplanowana wystrzelenie sondy kosmicznej Lunar Reconnaissance Orbiter. Misja może być zatem opóźniona do 20 czerwca, który jest ostatnią możliwą datą startu w tym miesiącu. W niedzielę odbędzie się spotkanie specjalistów NASA, na którym zostanie ustalona nowa data startu i dalszy plan misji STS-127. ## Data format Input is a TSV file with two columns: 1. Text ID (to be used when handling forced-aligned transcriptions and WAV files if needed) 2. Input text - in lower-case letter without punctuation marks The output should have the same number of lines as the input file, in each line the text with punctuation marks should be given. ### Forced-aligned transcriptions We use force-aligned transcriptions of the original texts to approximate ASR output. Files in the _.clntmstmp_ format contain forced-alignment of the original text together with the audio file read out by a group of volunteers. The files may contain errors resulting from incorrect reading of the text (skipping fragments, adding words missing from the original text) and alignment errors resulting from the configuration of the alignment tool for text and audio files. The configuration targeted Polish; names from foreign languages may be poorly recognised, with the word duration equal to zero (start and end timestamps are equal). Data is given in the following format: (timestamp\_start,timestamp\_end) word ... \</s\> where \</s\> is a symbol of the end of recognition. Example: (990,1200) Rosja (1230,1500) zaczyna (1590,1950) powracać (1980,2040) do (2070,2400) praktyk (2430,2490) z (2520,2760) czasów (2820,3090) zimnej (3180,3180) wojny. (3960,4290) Rosjanie (4380,4770) wznowili (4860,5070) bowiem (5100,5160) na (5220,5430) stałe (5520,5670) loty (5760,6030) swoich (6120,6600) bombowców (6630,7230) strategicznych (7350,7530) poza (7590,7890) granice (8010,8010) kraju. (8880,9300) Prezydent (9360,9810) Władimir (9930,10200) Putin (10650,10650) wyjaśnił, (10830,10920) iż (10980,11130) jest (11160,11190) to (11220,11520) odpowiedź (11550,11640) na (11670,12120) zagrożenie (12240,12300) ze (12330,12570) strony (12660,12870) innych (13140,13140) państw. \</s\> ## Evaluation procedure Baseline results will be provided in final evaluation. ### Punctuation During the task the following punctuation marks will be evaluated: \| Punctuation mark \| symbol \| \| --- \| --- \| \| fullstop \| . \| \| comma \| , \| \| question mark \| ? \| \| exclamation mark \| ! \| \| hyphen \| - \| \| colon \| : \| \| ellipsis \| ... \| \| blank (no punctuation) \| \| Note that semi-colon (`;`) is disregarded here. ### Submission format The output to be evaluated is just the text with punctuation marks added. ### Metrics Final results are evaluated in terms of precision, recall, and F1 scores for predicting each punctuation mark separately. Submissions are compared with respect to the weighted average of F1 scores for each punctuation mark. ##### Per-document score: ![](https://poleval.github.io/2021-punctuation-restoration/img/image003.png) ##### Global score per punctuation mark _p_: ![](https://poleval.github.io/2021-punctuation-restoration/img/image005.png) Final scoring metric calculated as weighted average of global scores per ![](https://poleval.github.io/2021-punctuation-restoration/img/image007.png) We would like to invite participants to discussion about evaluation metrics, taking into account such factors as: - ASR and Forced-Alignment errors, - inconsistencies among annotators, - impact of only slight displacement of punctuation, - assigning different weights to different types of errors. ### Video introduction [![Video instruction](http://img.youtube.com/vi/yEh-RiFGN94/0.jpg)](http://www.youtube.com/watch?v=yEh-RiFGN94 "Video instruction") ### Downloads Data has been published in the following repository: https://github.com/poleval/2021-punctuation-restoration Training data is provided in train/\*.tsv. Additional data can be downloaded from Google Drive. Below is a list of file names along with a description of what they contain. - [poleval\_fa.train.tar.gz](https://drive.google.com/file/d/1oBFjZPb5Hk4r_VW4G0HrVnGy7A7zmTpa/view?usp=sharing) - archive contains forced-alignment of the original text together with the audio file - [poleval\_wav.train.tar.gz](https://drive.google.com/file/d/1b6MyyqgA9D1U7DX3Vtgda7f9ppkxjCXJ/view?usp=sharing) - archive contains training audio files - [poleval\_wav.validation.tar.gz](https://drive.google.com/file/d/1gwQRvrUtFqz3xGnmEN8znAzkBwC12Czu/view?usp=sharing) - archive contains test audio files - [poleval\_text.rest.tar.gz](https://drive.google.com/file/d/10SdpLHPLXVfhJsq1okgC5fcxbFzCGoR5/view?usp=sharing) - archive contains additional text provided in JSON formatand CSV for which no audio files were provided (can be used for training purposes) ### Challenge stage The competition in September 2021. Now the challenge is in the after-competition stage. You can submit solutions, but they will be marked with a different color. ### License Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ### References 1. Yi, J., Tao, J., Bai, Y., Tian, Z., & Fan, C. (2020). Adversarial transfer learning for punctuation restoration. _arXiv preprint arXiv:2004.00248_. 2. Nguyen, Thai Binh, et al. "Improving Vietnamese Named Entity Recognition from Speech Using Word Capitalization and Punctuation Recovery Models." _Proc. Interspeech 2020_ (2020): 4263-4267. 3. Hlubík, Pavel, et al. "Inserting Punctuation to ASR Output in a Real-Time Production Environment." _International Conference on Text, Speech, and Dialogue_. Springer, Cham, 2020. 4. Sirts, Kairit, and Kairit Peekman. "Evaluating Sentence Segmentation and Word Tokenization Systems on Estonian Web Texts." _Human Language Technologies–The Baltic Perspective: Proceedings of the Ninth International Conference Baltic HLT 2020_. Vol. 328. IOS Press, 2020. 5. Wang, Xueyujie. "Analysis of Sentence Boundary of the Host's Spoken Language Based on Semantic Orientation Pointwise Mutual Information Algorithm." _2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)_. IEEE, 2020. 6. Sunkara, Monica, et al. "Multimodal Semi-supervised Learning Framework for Punctuation Prediction in Conversational Speech." _arXiv preprint arXiv:2008.00702_ (2020).	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comodoro/vystadial2016_asr	comodoro	2022-09-02T08:41:16Z	254	1	[ "license:cc-by-nc-3.0", "region:us" ]	null	2022-03-02T23:29:22Z	--- license: cc-by-nc-3.0 ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 0.7903715372085571, 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tasksource/babi_nli	tasksource	2023-06-05T09:05:59Z	254	1	[ "task_categories:text-classification", "task_ids:natural-language-inference", "annotations_creators:expert-generated", "language_creators:crowdsourced", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "license:bsd", "logical reasoning", "nli", "natural-language-inference", "reasoning", "logic", "region:us" ]	[ "text-classification" ]	2023-01-01T14:39:33Z	--- annotations_creators: - expert-generated language_creators: - crowdsourced language: - en license: bsd multilinguality: - monolingual pretty_name: babi_nli size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - natural-language-inference tags: - logical reasoning - nli - natural-language-inference - reasoning - logic --- # bAbi_nli bAbI tasks recasted as natural language inference. https://github.com/facebookarchive/bAbI-tasks tasksource recasting code: https://colab.research.google.com/drive/1J_RqDSw9iPxJSBvCJu-VRbjXnrEjKVvr?usp=sharing ```bibtex @article{weston2015towards, title={Towards ai-complete question answering: A set of prerequisite toy tasks}, author={Weston, Jason and Bordes, Antoine and Chopra, Sumit and Rush, Alexander M and Van Merri{\"e}nboer, Bart and Joulin, Armand and Mikolov, Tomas}, journal={arXiv preprint arXiv:1502.05698}, year={2015} } ```	[ -0.26362305879592896, -0.9980901479721069, 0.47946521639823914, 0.23444055020809174, 0.13639715313911438, 0.20607730746269226, -0.1601722538471222, -0.5388911962509155, 0.29921647906303406, 0.6415143609046936, -1.0541001558303833, -0.05169001594185829, -0.27978089451789856, 0.24922113120555878, -0.3781951069831848, 1.1834551095962524, 0.14582692086696625, -0.4026789963245392, -0.5585212707519531, 0.24258272349834442, -0.507036566734314, -0.0025368137285113335, -0.6768761277198792, -0.2972294092178345, 0.5008897185325623, 0.3426842987537384, 0.5054143071174622, 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RicardoRei/wmt-mqm-human-evaluation	RicardoRei	2023-02-16T18:29:11Z	254	0	[ "size_categories:100K<n<1M", "language:en", "language:de", "language:ru", "language:zh", "license:apache-2.0", "mt-evaluation", "WMT", "region:us" ]	null	2023-02-16T17:14:16Z	--- license: apache-2.0 language: - en - de - ru - zh tags: - mt-evaluation - WMT size_categories: - 100K<n<1M --- # Dataset Summary This dataset contains all MQM human annotations from previous [WMT Metrics shared tasks](https://wmt-metrics-task.github.io/) and the MQM annotations from [Experts, Errors, and Context](https://aclanthology.org/2021.tacl-1.87/). The data is organised into 8 columns: - lp: language pair - src: input text - mt: translation - ref: reference translation - score: MQM score - system: MT Engine that produced the translation - annotators: number of annotators - domain: domain of the input text (e.g. news) - year: collection year You can also find the original data [here](https://github.com/google/wmt-mqm-human-evaluation). We recommend using the original repo if you are interested in annotation spans and not just the final score. ## Python usage: ```python from datasets import load_dataset dataset = load_dataset("RicardoRei/wmt-mqm-human-evaluation", split="train") ``` There is no standard train/test split for this dataset but you can easily split it according to year, language pair or domain. E.g. : ```python # split by year data = dataset.filter(lambda example: example["year"] == 2022) # split by LP data = dataset.filter(lambda example: example["lp"] == "en-de") # split by domain data = dataset.filter(lambda example: example["domain"] == "ted") ``` ## Citation Information If you use this data please cite the following works: - [Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://aclanthology.org/2021.tacl-1.87/) - [Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain](https://aclanthology.org/2021.wmt-1.73/) - [Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust](https://aclanthology.org/2022.wmt-1.2/)	[ -0.4633139371871948, -0.4196746349334717, 0.3094450533390045, 0.16671492159366608, -0.16214463114738464, 0.13480551540851593, -0.3634679615497589, -0.3467930853366852, 0.3011779189109802, 0.5389572381973267, 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humarin/chatgpt-paraphrases	humarin	2023-04-05T16:27:16Z	254	32	[ "task_categories:text2text-generation", "size_categories:100K<n<1M", "language:en", "license:openrail", "region:us" ]	[ "text2text-generation" ]	2023-03-15T20:12:24Z	--- license: openrail task_categories: - text2text-generation language: - en size_categories: - 100K<n<1M --- This is a dataset of paraphrases created by ChatGPT. Model based on this dataset is avaible: [model](https://huggingface.co/humarin/chatgpt_paraphraser_on_T5_base) ## We used this prompt to generate paraphrases Generate 5 similar paraphrases for this question, show it like a numbered list without commentaries: {text} This dataset is based on the [Quora paraphrase question](https://www.kaggle.com/competitions/quora-question-pairs), texts from the [SQUAD 2.0](https://huggingface.co/datasets/squad_v2) and the [CNN news dataset](https://huggingface.co/datasets/cnn_dailymail). We generated 5 paraphrases for each sample, totally this dataset has about 420k data rows. You can make 30 rows from a row from each sample. In this way you can make 12.6 millions train pairs (420k rows with 5 paraphrases -> 6x5x420000 = 12.6 millions of bidirected or 6x5x420000/2 = 6.3 millions of unique pairs). ## We used - 247138 questions from the Quora dataset - 91983 texts from the Squad 2.0 dataset - 80076 texts from the CNN news dataset ## Structure of the dataset - text column - an original sentence or question from the datasets - paraphrases - a list of 5 paraphrases - category - question / sentence - source - quora / squad_2 / cnn_news ## Legal disclaimer Data is based on OpenAI’s gpt-3.5-turbo, whose [terms of use](https://openai.com/policies/terms-of-use) prohibit developing models that compete with OpenAI. So if you use this dataset to train a model, don't compete with OpenAI. ### BibTeX entry and citation info ```bibtex @inproceedings{chatgpt_paraphrases_dataset, author={Vladimir Vorobev, Maxim Kuznetsov}, title={ChatGPT paraphrases dataset}, year={2023} } ```	[ -0.11757876724004745, -0.621245265007019, 0.33077773451805115, 0.12484388053417206, -0.46925443410873413, -0.4673665165901184, 0.05615576356649399, -0.054453667253255844, 0.086714006960392, 0.7124344110488892, -0.5494261980056763, -0.34050655364990234, -0.2907228469848633, 0.1765969693660736, -0.5635216236114502, 1.457809567451477, 0.029446372762322426, 0.10013607889413834, -0.26282328367233276, -0.4138675630092621, -0.18396371603012085, -0.5000719428062439, -0.3846825659275055, -0.06412293761968613, 0.513576865196228, 0.46751168370246887, 0.8127602934837341, 0.4123108983039856, 0.5016114711761475, 0.1797829419374466, -0.15198101103305817, -0.03666720166802406, -0.5755713582038879, -0.09233780205249786, 0.07232017070055008, 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GATE-engine/aircraft_bbcrop	GATE-engine	2023-06-04T22:22:54Z	254	0	[ "region:us" ]	null	2023-06-04T22:22:30Z	--- dataset_info: features: - name: image dtype: image - name: label dtype: int64 splits: - name: train num_bytes: 253644684.5 num_examples: 3500 - name: validation num_bytes: 70984494.0 num_examples: 1000 - name: test num_bytes: 80183818.5 num_examples: 1100 download_size: 404802117 dataset_size: 404812997.0 --- # Dataset Card for "aircraft_bbcrop" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.713071346282959, -0.057459618896245956, 0.08887303620576859, 0.2600243389606476, -0.4146072268486023, 0.20382970571517944, 0.2805939018726349, -0.15653568506240845, 0.6632794141769409, 0.35710808634757996, -0.773887574672699, -0.6788221001625061, -0.5595593452453613, -0.2877641022205353, -0.4054294228553772, 1.1954107284545898, 0.11199875921010971, 0.026946017518639565, -0.2615886628627777, 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Sp1786/multiclass-sentiment-analysis-dataset	Sp1786	2023-06-25T08:01:27Z	254	1	[ "task_categories:text-classification", "task_categories:translation", "size_categories:10K<n<100K", "language:en", "license:apache-2.0", "code", "region:us" ]	[ "text-classification", "translation" ]	2023-06-21T11:21:31Z	--- license: apache-2.0 task_categories: - text-classification - translation language: - en tags: - code pretty_name: multiclass-sentiment-analysis-dataset size_categories: - 10K<n<100K --- # Dataset Card for Dataset Name ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.5456171631813049, -0.42588159441947937, -0.05128554254770279, 0.3873923122882843, -0.46201014518737793, 0.054228708148002625, -0.24659399688243866, -0.2884674072265625, 0.6999505162239075, 0.5781942009925842, -0.9070091843605042, -1.151341199874878, -0.756676435470581, 0.029052024707198143, -0.1616567075252533, 1.3297250270843506, -0.09467329829931259, -0.2637445628643036, -0.29706019163131714, -0.4286412298679352, -0.4010111093521118, -0.5148692727088928, -0.5024060010910034, 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open-llm-leaderboard/details_OpenAssistant__pythia-12b-pre-v8-12.5k-steps	open-llm-leaderboard	2023-12-01T14:11:05Z	254	0	[ "region:us" ]	null	2023-08-18T11:13:02Z	--- pretty_name: Evaluation run of OpenAssistant/pythia-12b-pre-v8-12.5k-steps dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [OpenAssistant/pythia-12b-pre-v8-12.5k-steps](https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_OpenAssistant__pythia-12b-pre-v8-12.5k-steps_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-06T18:06:29.606076](https://huggingface.co/datasets/open-llm-leaderboard/details_OpenAssistant__pythia-12b-pre-v8-12.5k-steps_public/blob/main/results_2023-11-06T18-06-29.606076.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0007340604026845638,\n\ \ \"em_stderr\": 0.00027736144573356703,\n \"f1\": 0.04888842281879203,\n\ \ \"f1_stderr\": 0.001200028057735833,\n \"acc\": 0.3646480645630345,\n\ \ \"acc_stderr\": 0.010352737065601407\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0007340604026845638,\n \"em_stderr\": 0.00027736144573356703,\n\ \ \"f1\": 0.04888842281879203,\n \"f1_stderr\": 0.001200028057735833\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.07657316148597422,\n \ \ \"acc_stderr\": 0.007324564881451574\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6527229676400947,\n \"acc_stderr\": 0.013380909249751239\n\ \ }\n}\n```" repo_url: https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_drop_3 data_files: - split: 2023_11_05T00_35_27.872152 path: - '/details_harness\|drop\|3_2023-11-05T00-35-27.872152.parquet' - split: 2023_11_06T18_06_29.606076 path: - '/details_harness\|drop\|3_2023-11-06T18-06-29.606076.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-06T18-06-29.606076.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_05T00_35_27.872152 path: - '/details_harness\|gsm8k\|5_2023-11-05T00-35-27.872152.parquet' - split: 2023_11_06T18_06_29.606076 path: - '/details_harness\|gsm8k\|5_2023-11-06T18-06-29.606076.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-06T18-06-29.606076.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_05T00_35_27.872152 path: - '/details_harness\|winogrande\|5_2023-11-05T00-35-27.872152.parquet' - split: 2023_11_06T18_06_29.606076 path: - '/details_harness\|winogrande\|5_2023-11-06T18-06-29.606076.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-06T18-06-29.606076.parquet' - config_name: results data_files: - split: 2023_11_05T00_35_27.872152 path: - results_2023-11-05T00-35-27.872152.parquet - split: 2023_11_06T18_06_29.606076 path: - results_2023-11-06T18-06-29.606076.parquet - split: latest path: - results_2023-11-06T18-06-29.606076.parquet --- # Dataset Card for Evaluation run of OpenAssistant/pythia-12b-pre-v8-12.5k-steps ## Dataset Description - Homepage: - Repository: https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [OpenAssistant/pythia-12b-pre-v8-12.5k-steps](https://huggingface.co/OpenAssistant/pythia-12b-pre-v8-12.5k-steps) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_OpenAssistant__pythia-12b-pre-v8-12.5k-steps_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-06T18:06:29.606076](https://huggingface.co/datasets/open-llm-leaderboard/details_OpenAssistant__pythia-12b-pre-v8-12.5k-steps_public/blob/main/results_2023-11-06T18-06-29.606076.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0007340604026845638, "em_stderr": 0.00027736144573356703, "f1": 0.04888842281879203, "f1_stderr": 0.001200028057735833, "acc": 0.3646480645630345, "acc_stderr": 0.010352737065601407 }, "harness\|drop\|3": { "em": 0.0007340604026845638, "em_stderr": 0.00027736144573356703, "f1": 0.04888842281879203, "f1_stderr": 0.001200028057735833 }, "harness\|gsm8k\|5": { "acc": 0.07657316148597422, "acc_stderr": 0.007324564881451574 }, "harness\|winogrande\|5": { "acc": 0.6527229676400947, "acc_stderr": 0.013380909249751239 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.32547473907470703, -0.6554842591285706, 0.1856391578912735, 0.16838382184505463, -0.1365794837474823, 0.0819166973233223, -0.33027058839797974, -0.1349869668483734, 0.336799293756485, 0.4453689157962799, -0.6872501969337463, -0.935133159160614, -0.6287690997123718, 0.09784258157014847, -0.16136322915554047, 1.0996102094650269, -0.4083039462566376, -0.1500711441040039, 0.11958982050418854, -0.23813685774803162, -0.2987262010574341, -0.36498183012008667, -0.3446921408176422, 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open-llm-leaderboard/details_Devio__test-1400	open-llm-leaderboard	2023-09-03T06:26:32Z	254	0	[ "region:us" ]	null	2023-09-03T06:25:35Z	--- pretty_name: Evaluation run of Devio/test-1400 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Devio/test-1400](https://huggingface.co/Devio/test-1400) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Devio__test-1400\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-03T06:25:15.872451](https://huggingface.co/datasets/open-llm-leaderboard/details_Devio__test-1400/blob/main/results_2023-09-03T06%3A25%3A15.872451.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.29066385939253414,\n\ \ \"acc_stderr\": 0.032634153881095015,\n \"acc_norm\": 0.2942628467289629,\n\ \ \"acc_norm_stderr\": 0.03263364427629342,\n \"mc1\": 0.22766217870257038,\n\ \ \"mc1_stderr\": 0.01467925503211107,\n \"mc2\": 0.3686966632375142,\n\ \ \"mc2_stderr\": 0.014163025545486835\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.35238907849829354,\n \"acc_stderr\": 0.013960142600598685,\n\ \ \"acc_norm\": 0.38139931740614336,\n \"acc_norm_stderr\": 0.014194389086685263\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4785899223262298,\n\ \ \"acc_stderr\": 0.004985204766555062,\n \"acc_norm\": 0.6619199362676758,\n\ \ \"acc_norm_stderr\": 0.004720891597174716\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909283\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.22962962962962963,\n\ \ \"acc_stderr\": 0.036333844140734636,\n \"acc_norm\": 0.22962962962962963,\n\ \ \"acc_norm_stderr\": 0.036333844140734636\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.3684210526315789,\n \"acc_stderr\": 0.03925523381052932,\n\ \ \"acc_norm\": 0.3684210526315789,\n \"acc_norm_stderr\": 0.03925523381052932\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.21,\n\ \ \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n \ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.3169811320754717,\n \"acc_stderr\": 0.028637235639800935,\n\ \ \"acc_norm\": 0.3169811320754717,\n \"acc_norm_stderr\": 0.028637235639800935\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.24305555555555555,\n\ \ \"acc_stderr\": 0.03586879280080343,\n \"acc_norm\": 0.24305555555555555,\n\ \ \"acc_norm_stderr\": 0.03586879280080343\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \"acc_norm\"\ : 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3063583815028902,\n\ \ \"acc_stderr\": 0.03514942551267439,\n \"acc_norm\": 0.3063583815028902,\n\ \ \"acc_norm_stderr\": 0.03514942551267439\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.28431372549019607,\n \"acc_stderr\": 0.04488482852329017,\n\ \ \"acc_norm\": 0.28431372549019607,\n \"acc_norm_stderr\": 0.04488482852329017\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.3446808510638298,\n \"acc_stderr\": 0.03106898596312215,\n\ \ \"acc_norm\": 0.3446808510638298,\n \"acc_norm_stderr\": 0.03106898596312215\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813344,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813344\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2620689655172414,\n \"acc_stderr\": 0.036646663372252565,\n\ \ \"acc_norm\": 0.2620689655172414,\n \"acc_norm_stderr\": 0.036646663372252565\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2857142857142857,\n \"acc_stderr\": 0.023266512213730564,\n \"\ acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.023266512213730564\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.31746031746031744,\n\ \ \"acc_stderr\": 0.04163453031302859,\n \"acc_norm\": 0.31746031746031744,\n\ \ \"acc_norm_stderr\": 0.04163453031302859\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695236\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.3225806451612903,\n\ \ \"acc_stderr\": 0.026593084516572274,\n \"acc_norm\": 0.3225806451612903,\n\ \ \"acc_norm_stderr\": 0.026593084516572274\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.2857142857142857,\n \"acc_stderr\": 0.0317852971064275,\n\ \ \"acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.0317852971064275\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.19,\n \"acc_stderr\": 0.03942772444036624,\n \"acc_norm\"\ : 0.19,\n \"acc_norm_stderr\": 0.03942772444036624\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.2606060606060606,\n \"acc_stderr\": 0.034277431758165236,\n\ \ \"acc_norm\": 0.2606060606060606,\n \"acc_norm_stderr\": 0.034277431758165236\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.3686868686868687,\n \"acc_stderr\": 0.034373055019806184,\n \"\ acc_norm\": 0.3686868686868687,\n \"acc_norm_stderr\": 0.034373055019806184\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.35233160621761656,\n \"acc_stderr\": 0.03447478286414359,\n\ \ \"acc_norm\": 0.35233160621761656,\n \"acc_norm_stderr\": 0.03447478286414359\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.36153846153846153,\n \"acc_stderr\": 0.02435958146539698,\n\ \ \"acc_norm\": 0.36153846153846153,\n \"acc_norm_stderr\": 0.02435958146539698\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275805,\n \ \ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275805\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.33613445378151263,\n \"acc_stderr\": 0.03068473711513536,\n\ \ \"acc_norm\": 0.33613445378151263,\n \"acc_norm_stderr\": 0.03068473711513536\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658754,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658754\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.3376146788990826,\n \"acc_stderr\": 0.0202752659866389,\n \"acc_norm\"\ : 0.3376146788990826,\n \"acc_norm_stderr\": 0.0202752659866389\n },\n\ \ \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\": 0.4074074074074074,\n\ \ \"acc_stderr\": 0.03350991604696043,\n \"acc_norm\": 0.4074074074074074,\n\ \ \"acc_norm_stderr\": 0.03350991604696043\n },\n \"harness\|hendrycksTest-high_school_us_history\|5\"\ : {\n \"acc\": 0.25980392156862747,\n \"acc_stderr\": 0.03077855467869326,\n\ \ \"acc_norm\": 0.25980392156862747,\n \"acc_norm_stderr\": 0.03077855467869326\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.19831223628691982,\n \"acc_stderr\": 0.025955020841621115,\n \ \ \"acc_norm\": 0.19831223628691982,\n \"acc_norm_stderr\": 0.025955020841621115\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.26905829596412556,\n\ \ \"acc_stderr\": 0.029763779406874972,\n \"acc_norm\": 0.26905829596412556,\n\ \ \"acc_norm_stderr\": 0.029763779406874972\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.31297709923664124,\n \"acc_stderr\": 0.04066962905677697,\n\ \ \"acc_norm\": 0.31297709923664124,\n \"acc_norm_stderr\": 0.04066962905677697\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.1322314049586777,\n \"acc_stderr\": 0.030922788320445784,\n \"\ acc_norm\": 0.1322314049586777,\n \"acc_norm_stderr\": 0.030922788320445784\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.2085889570552147,\n \"acc_stderr\": 0.03192193448934722,\n\ \ \"acc_norm\": 0.2085889570552147,\n \"acc_norm_stderr\": 0.03192193448934722\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.16071428571428573,\n\ \ \"acc_stderr\": 0.03485946096475741,\n \"acc_norm\": 0.16071428571428573,\n\ \ \"acc_norm_stderr\": 0.03485946096475741\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.4077669902912621,\n \"acc_stderr\": 0.048657775704107696,\n\ \ \"acc_norm\": 0.4077669902912621,\n \"acc_norm_stderr\": 0.048657775704107696\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.23504273504273504,\n\ \ \"acc_stderr\": 0.02777883590493543,\n \"acc_norm\": 0.23504273504273504,\n\ \ \"acc_norm_stderr\": 0.02777883590493543\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.24521072796934865,\n\ \ \"acc_stderr\": 0.015384352284543932,\n \"acc_norm\": 0.24521072796934865,\n\ \ \"acc_norm_stderr\": 0.015384352284543932\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.2745664739884393,\n \"acc_stderr\": 0.024027745155265023,\n\ \ \"acc_norm\": 0.2745664739884393,\n \"acc_norm_stderr\": 0.024027745155265023\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2536312849162011,\n\ \ \"acc_stderr\": 0.014551553659369922,\n \"acc_norm\": 0.2536312849162011,\n\ \ \"acc_norm_stderr\": 0.014551553659369922\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.3104575163398693,\n \"acc_stderr\": 0.0264930332251459,\n\ \ \"acc_norm\": 0.3104575163398693,\n \"acc_norm_stderr\": 0.0264930332251459\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.29260450160771706,\n\ \ \"acc_stderr\": 0.02583989833487798,\n \"acc_norm\": 0.29260450160771706,\n\ \ \"acc_norm_stderr\": 0.02583989833487798\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.25617283950617287,\n \"acc_stderr\": 0.0242885336377261,\n\ \ \"acc_norm\": 0.25617283950617287,\n \"acc_norm_stderr\": 0.0242885336377261\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.28368794326241137,\n \"acc_stderr\": 0.026891709428343957,\n \ \ \"acc_norm\": 0.28368794326241137,\n \"acc_norm_stderr\": 0.026891709428343957\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2438070404172099,\n\ \ \"acc_stderr\": 0.010966507972178479,\n \"acc_norm\": 0.2438070404172099,\n\ \ \"acc_norm_stderr\": 0.010966507972178479\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4227941176470588,\n \"acc_stderr\": 0.03000856284500347,\n\ \ \"acc_norm\": 0.4227941176470588,\n \"acc_norm_stderr\": 0.03000856284500347\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.23529411764705882,\n \"acc_stderr\": 0.01716058723504635,\n \ \ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.01716058723504635\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.2818181818181818,\n\ \ \"acc_stderr\": 0.043091187099464585,\n \"acc_norm\": 0.2818181818181818,\n\ \ \"acc_norm_stderr\": 0.043091187099464585\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.031362502409358936,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.031362502409358936\n \ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.03333333333333335,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.03333333333333335\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.25301204819277107,\n\ \ \"acc_stderr\": 0.03384429155233136,\n \"acc_norm\": 0.25301204819277107,\n\ \ \"acc_norm_stderr\": 0.03384429155233136\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.23391812865497075,\n \"acc_stderr\": 0.03246721765117826,\n\ \ \"acc_norm\": 0.23391812865497075,\n \"acc_norm_stderr\": 0.03246721765117826\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.22766217870257038,\n\ \ \"mc1_stderr\": 0.01467925503211107,\n \"mc2\": 0.3686966632375142,\n\ \ \"mc2_stderr\": 0.014163025545486835\n }\n}\n```" repo_url: https://huggingface.co/Devio/test-1400 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|arc:challenge\|25_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hellaswag\|10_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T06:25:15.872451.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T06:25:15.872451.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_03T06_25_15.872451 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-03T06:25:15.872451.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-03T06:25:15.872451.parquet' - config_name: results data_files: - split: 2023_09_03T06_25_15.872451 path: - results_2023-09-03T06:25:15.872451.parquet - split: latest path: - results_2023-09-03T06:25:15.872451.parquet --- # Dataset Card for Evaluation run of Devio/test-1400 ## Dataset Description - Homepage: - Repository: https://huggingface.co/Devio/test-1400 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [Devio/test-1400](https://huggingface.co/Devio/test-1400) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Devio__test-1400", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-03T06:25:15.872451](https://huggingface.co/datasets/open-llm-leaderboard/details_Devio__test-1400/blob/main/results_2023-09-03T06%3A25%3A15.872451.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.29066385939253414, "acc_stderr": 0.032634153881095015, "acc_norm": 0.2942628467289629, "acc_norm_stderr": 0.03263364427629342, "mc1": 0.22766217870257038, "mc1_stderr": 0.01467925503211107, "mc2": 0.3686966632375142, "mc2_stderr": 0.014163025545486835 }, "harness\|arc:challenge\|25": { "acc": 0.35238907849829354, "acc_stderr": 0.013960142600598685, "acc_norm": 0.38139931740614336, "acc_norm_stderr": 0.014194389086685263 }, "harness\|hellaswag\|10": { "acc": 0.4785899223262298, "acc_stderr": 0.004985204766555062, "acc_norm": 0.6619199362676758, "acc_norm_stderr": 0.004720891597174716 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.22962962962962963, "acc_stderr": 0.036333844140734636, "acc_norm": 0.22962962962962963, "acc_norm_stderr": 0.036333844140734636 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.3684210526315789, "acc_stderr": 0.03925523381052932, "acc_norm": 0.3684210526315789, "acc_norm_stderr": 0.03925523381052932 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.3169811320754717, "acc_stderr": 0.028637235639800935, "acc_norm": 0.3169811320754717, "acc_norm_stderr": 0.028637235639800935 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.24305555555555555, "acc_stderr": 0.03586879280080343, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.03586879280080343 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3063583815028902, "acc_stderr": 0.03514942551267439, "acc_norm": 0.3063583815028902, "acc_norm_stderr": 0.03514942551267439 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3446808510638298, "acc_stderr": 0.03106898596312215, "acc_norm": 0.3446808510638298, "acc_norm_stderr": 0.03106898596312215 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813344, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813344 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2620689655172414, "acc_stderr": 0.036646663372252565, "acc_norm": 0.2620689655172414, "acc_norm_stderr": 0.036646663372252565 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.023266512213730564, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.023266512213730564 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.3225806451612903, "acc_stderr": 0.026593084516572274, "acc_norm": 0.3225806451612903, "acc_norm_stderr": 0.026593084516572274 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.0317852971064275, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.0317852971064275 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.19, "acc_stderr": 0.03942772444036624, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036624 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.2606060606060606, "acc_stderr": 0.034277431758165236, "acc_norm": 0.2606060606060606, "acc_norm_stderr": 0.034277431758165236 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.3686868686868687, "acc_stderr": 0.034373055019806184, "acc_norm": 0.3686868686868687, "acc_norm_stderr": 0.034373055019806184 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.35233160621761656, "acc_stderr": 0.03447478286414359, "acc_norm": 0.35233160621761656, "acc_norm_stderr": 0.03447478286414359 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.36153846153846153, "acc_stderr": 0.02435958146539698, "acc_norm": 0.36153846153846153, "acc_norm_stderr": 0.02435958146539698 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.24074074074074073, "acc_stderr": 0.026067159222275805, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.026067159222275805 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.33613445378151263, "acc_stderr": 0.03068473711513536, "acc_norm": 0.33613445378151263, "acc_norm_stderr": 0.03068473711513536 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658754, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658754 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.3376146788990826, "acc_stderr": 0.0202752659866389, "acc_norm": 0.3376146788990826, "acc_norm_stderr": 0.0202752659866389 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4074074074074074, "acc_stderr": 0.03350991604696043, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.03350991604696043 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25980392156862747, "acc_stderr": 0.03077855467869326, "acc_norm": 0.25980392156862747, "acc_norm_stderr": 0.03077855467869326 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.19831223628691982, "acc_stderr": 0.025955020841621115, "acc_norm": 0.19831223628691982, "acc_norm_stderr": 0.025955020841621115 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.26905829596412556, "acc_stderr": 0.029763779406874972, "acc_norm": 0.26905829596412556, "acc_norm_stderr": 0.029763779406874972 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.31297709923664124, "acc_stderr": 0.04066962905677697, "acc_norm": 0.31297709923664124, "acc_norm_stderr": 0.04066962905677697 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.1322314049586777, "acc_stderr": 0.030922788320445784, "acc_norm": 0.1322314049586777, "acc_norm_stderr": 0.030922788320445784 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.2085889570552147, "acc_stderr": 0.03192193448934722, "acc_norm": 0.2085889570552147, "acc_norm_stderr": 0.03192193448934722 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.16071428571428573, "acc_stderr": 0.03485946096475741, "acc_norm": 0.16071428571428573, "acc_norm_stderr": 0.03485946096475741 }, "harness\|hendrycksTest-management\|5": { "acc": 0.4077669902912621, "acc_stderr": 0.048657775704107696, "acc_norm": 0.4077669902912621, "acc_norm_stderr": 0.048657775704107696 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.23504273504273504, "acc_stderr": 0.02777883590493543, "acc_norm": 0.23504273504273504, "acc_norm_stderr": 0.02777883590493543 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.24521072796934865, "acc_stderr": 0.015384352284543932, "acc_norm": 0.24521072796934865, "acc_norm_stderr": 0.015384352284543932 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.2745664739884393, "acc_stderr": 0.024027745155265023, "acc_norm": 0.2745664739884393, "acc_norm_stderr": 0.024027745155265023 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2536312849162011, "acc_stderr": 0.014551553659369922, "acc_norm": 0.2536312849162011, "acc_norm_stderr": 0.014551553659369922 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.3104575163398693, "acc_stderr": 0.0264930332251459, "acc_norm": 0.3104575163398693, "acc_norm_stderr": 0.0264930332251459 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.29260450160771706, "acc_stderr": 0.02583989833487798, "acc_norm": 0.29260450160771706, "acc_norm_stderr": 0.02583989833487798 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.25617283950617287, "acc_stderr": 0.0242885336377261, "acc_norm": 0.25617283950617287, "acc_norm_stderr": 0.0242885336377261 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.28368794326241137, "acc_stderr": 0.026891709428343957, "acc_norm": 0.28368794326241137, "acc_norm_stderr": 0.026891709428343957 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2438070404172099, "acc_stderr": 0.010966507972178479, "acc_norm": 0.2438070404172099, "acc_norm_stderr": 0.010966507972178479 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4227941176470588, "acc_stderr": 0.03000856284500347, "acc_norm": 0.4227941176470588, "acc_norm_stderr": 0.03000856284500347 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.23529411764705882, "acc_stderr": 0.01716058723504635, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.01716058723504635 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.2818181818181818, "acc_stderr": 0.043091187099464585, "acc_norm": 0.2818181818181818, "acc_norm_stderr": 0.043091187099464585 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.4, "acc_stderr": 0.031362502409358936, "acc_norm": 0.4, "acc_norm_stderr": 0.031362502409358936 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.03333333333333335, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.03333333333333335 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.25301204819277107, "acc_stderr": 0.03384429155233136, "acc_norm": 0.25301204819277107, "acc_norm_stderr": 0.03384429155233136 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.23391812865497075, "acc_stderr": 0.03246721765117826, "acc_norm": 0.23391812865497075, "acc_norm_stderr": 0.03246721765117826 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.22766217870257038, "mc1_stderr": 0.01467925503211107, "mc2": 0.3686966632375142, "mc2_stderr": 0.014163025545486835 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7311246395111084, -0.8236830830574036, 0.25865644216537476, 0.24609394371509552, -0.12903450429439545, -0.07740434259176254, 0.036624666303396225, -0.21220454573631287, 0.5912962555885315, -0.06937767565250397, -0.49518635869026184, -0.674248218536377, -0.46268728375434875, 0.2768057584762573, -0.017428956925868988, 0.805552065372467, -0.17934411764144897, -0.09962645173072815, 0.0810818001627922, -0.005900741554796696, -0.2500677704811096, -0.3296542167663574, -0.4896976053714752, 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open-llm-leaderboard/details_microsoft__phi-1_5	open-llm-leaderboard	2023-12-01T14:38:12Z	254	1	[ "region:us" ]	null	2023-09-12T08:08:37Z	--- pretty_name: Evaluation run of microsoft/phi-1_5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_microsoft__phi-1_5_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-06T13:16:44.433412](https://huggingface.co/datasets/open-llm-leaderboard/details_microsoft__phi-1_5_public/blob/main/results_2023-11-06T13-16-44.433412.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0025167785234899327,\n\ \ \"em_stderr\": 0.0005131152834514706,\n \"f1\": 0.050449874161074076,\n\ \ \"f1_stderr\": 0.0013066024783407934,\n \"acc\": 0.4232574963812843,\n\ \ \"acc_stderr\": 0.01083889957295003\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0025167785234899327,\n \"em_stderr\": 0.0005131152834514706,\n\ \ \"f1\": 0.050449874161074076,\n \"f1_stderr\": 0.0013066024783407934\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.1243366186504928,\n \ \ \"acc_stderr\": 0.009088880962028463\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7221783741120757,\n \"acc_stderr\": 0.0125889181838716\n\ \ }\n}\n```" repo_url: https://huggingface.co/microsoft/phi-1_5 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_drop_3 data_files: - split: 2023_11_06T13_16_44.433412 path: - '/details_harness\|drop\|3_2023-11-06T13-16-44.433412.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-06T13-16-44.433412.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_06T13_16_44.433412 path: - '/details_harness\|gsm8k\|5_2023-11-06T13-16-44.433412.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-06T13-16-44.433412.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_06T13_16_44.433412 path: - '/details_harness\|winogrande\|5_2023-11-06T13-16-44.433412.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-06T13-16-44.433412.parquet' - config_name: results data_files: - split: 2023_11_06T13_16_44.433412 path: - results_2023-11-06T13-16-44.433412.parquet - split: latest path: - results_2023-11-06T13-16-44.433412.parquet --- # Dataset Card for Evaluation run of microsoft/phi-1_5 ## Dataset Description - Homepage: - Repository: https://huggingface.co/microsoft/phi-1_5 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_microsoft__phi-1_5_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-06T13:16:44.433412](https://huggingface.co/datasets/open-llm-leaderboard/details_microsoft__phi-1_5_public/blob/main/results_2023-11-06T13-16-44.433412.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0025167785234899327, "em_stderr": 0.0005131152834514706, "f1": 0.050449874161074076, "f1_stderr": 0.0013066024783407934, "acc": 0.4232574963812843, "acc_stderr": 0.01083889957295003 }, "harness\|drop\|3": { "em": 0.0025167785234899327, "em_stderr": 0.0005131152834514706, "f1": 0.050449874161074076, "f1_stderr": 0.0013066024783407934 }, "harness\|gsm8k\|5": { "acc": 0.1243366186504928, "acc_stderr": 0.009088880962028463 }, "harness\|winogrande\|5": { "acc": 0.7221783741120757, "acc_stderr": 0.0125889181838716 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.38813358545303345, -0.6391561627388, 0.14939118921756744, 0.316577672958374, -0.16228404641151428, 0.05697297677397728, -0.22861309349536896, -0.18991659581661224, 0.38191837072372437, 0.46277135610580444, -0.8249051570892334, -0.9618419408798218, -0.6732637286186218, 0.17308002710342407, -0.19019339978694916, 1.1017441749572754, -0.21243241429328918, -0.26894861459732056, 0.06686823815107346, -0.2830866575241089, -0.21382494270801544, -0.5034564733505249, -0.42780324816703796, 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open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2	open-llm-leaderboard	2023-09-14T19:16:11Z	254	0	[ "region:us" ]	null	2023-09-14T19:15:01Z	--- pretty_name: Evaluation run of aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2](https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-14T19:14:45.418998](https://huggingface.co/datasets/open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2/blob/main/results_2023-09-14T19-14-45.418998.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.4945007463965186,\n\ \ \"acc_stderr\": 0.03527731102256181,\n \"acc_norm\": 0.49711825981073476,\n\ \ \"acc_norm_stderr\": 0.035276035393914426,\n \"mc1\": 0.32558139534883723,\n\ \ \"mc1_stderr\": 0.016403989469907825,\n \"mc2\": 0.5188093512935639,\n\ \ \"mc2_stderr\": 0.016351300657386426\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.4351535836177474,\n \"acc_stderr\": 0.014487986197186043,\n\ \ \"acc_norm\": 0.4453924914675768,\n \"acc_norm_stderr\": 0.01452398763834409\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4660426209918343,\n\ \ \"acc_stderr\": 0.004978260641742204,\n \"acc_norm\": 0.6102370045807608,\n\ \ \"acc_norm_stderr\": 0.004866997110388195\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4740740740740741,\n\ \ \"acc_stderr\": 0.04313531696750574,\n \"acc_norm\": 0.4740740740740741,\n\ \ \"acc_norm_stderr\": 0.04313531696750574\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.47368421052631576,\n \"acc_stderr\": 0.04063302731486671,\n\ \ \"acc_norm\": 0.47368421052631576,\n \"acc_norm_stderr\": 0.04063302731486671\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.53,\n\ \ \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5320754716981132,\n \"acc_stderr\": 0.030709486992556538,\n\ \ \"acc_norm\": 0.5320754716981132,\n \"acc_norm_stderr\": 0.030709486992556538\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.5277777777777778,\n\ \ \"acc_stderr\": 0.04174752578923185,\n \"acc_norm\": 0.5277777777777778,\n\ \ \"acc_norm_stderr\": 0.04174752578923185\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\"\ : 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.4797687861271676,\n\ \ \"acc_stderr\": 0.03809342081273957,\n \"acc_norm\": 0.4797687861271676,\n\ \ \"acc_norm_stderr\": 0.03809342081273957\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.2647058823529412,\n \"acc_stderr\": 0.04389869956808778,\n\ \ \"acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.04389869956808778\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \"acc_norm\": 0.67,\n\ \ \"acc_norm_stderr\": 0.04725815626252609\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.425531914893617,\n \"acc_stderr\": 0.032321469162244695,\n\ \ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.032321469162244695\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4206896551724138,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.4206896551724138,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2857142857142857,\n \"acc_stderr\": 0.02326651221373057,\n \"\ acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.02326651221373057\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3412698412698413,\n\ \ \"acc_stderr\": 0.04240799327574924,\n \"acc_norm\": 0.3412698412698413,\n\ \ \"acc_norm_stderr\": 0.04240799327574924\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.535483870967742,\n\ \ \"acc_stderr\": 0.028372287797962935,\n \"acc_norm\": 0.535483870967742,\n\ \ \"acc_norm_stderr\": 0.028372287797962935\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.3842364532019704,\n \"acc_stderr\": 0.03422398565657551,\n\ \ \"acc_norm\": 0.3842364532019704,\n \"acc_norm_stderr\": 0.03422398565657551\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.56,\n \"acc_stderr\": 0.049888765156985884,\n \"acc_norm\"\ : 0.56,\n \"acc_norm_stderr\": 0.049888765156985884\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6363636363636364,\n \"acc_stderr\": 0.03756335775187896,\n\ \ \"acc_norm\": 0.6363636363636364,\n \"acc_norm_stderr\": 0.03756335775187896\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.6515151515151515,\n \"acc_stderr\": 0.033948539651564025,\n \"\ acc_norm\": 0.6515151515151515,\n \"acc_norm_stderr\": 0.033948539651564025\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7461139896373057,\n \"acc_stderr\": 0.0314102478056532,\n\ \ \"acc_norm\": 0.7461139896373057,\n \"acc_norm_stderr\": 0.0314102478056532\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5153846153846153,\n \"acc_stderr\": 0.025339003010106515,\n\ \ \"acc_norm\": 0.5153846153846153,\n \"acc_norm_stderr\": 0.025339003010106515\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.02752859921034049,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.02752859921034049\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.47058823529411764,\n \"acc_stderr\": 0.03242225027115006,\n\ \ \"acc_norm\": 0.47058823529411764,\n \"acc_norm_stderr\": 0.03242225027115006\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.038227469376587525,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.038227469376587525\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.6495412844036698,\n \"acc_stderr\": 0.020456077599824467,\n \"\ acc_norm\": 0.6495412844036698,\n \"acc_norm_stderr\": 0.020456077599824467\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.28703703703703703,\n \"acc_stderr\": 0.030851992993257013,\n \"\ acc_norm\": 0.28703703703703703,\n \"acc_norm_stderr\": 0.030851992993257013\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.5784313725490197,\n \"acc_stderr\": 0.03465868196380762,\n \"\ acc_norm\": 0.5784313725490197,\n \"acc_norm_stderr\": 0.03465868196380762\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.6582278481012658,\n \"acc_stderr\": 0.030874537537553617,\n \ \ \"acc_norm\": 0.6582278481012658,\n \"acc_norm_stderr\": 0.030874537537553617\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.5739910313901345,\n\ \ \"acc_stderr\": 0.033188332862172806,\n \"acc_norm\": 0.5739910313901345,\n\ \ \"acc_norm_stderr\": 0.033188332862172806\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5572519083969466,\n \"acc_stderr\": 0.0435644720266507,\n\ \ \"acc_norm\": 0.5572519083969466,\n \"acc_norm_stderr\": 0.0435644720266507\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.6033057851239669,\n \"acc_stderr\": 0.04465869780531009,\n \"\ acc_norm\": 0.6033057851239669,\n \"acc_norm_stderr\": 0.04465869780531009\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.5648148148148148,\n\ \ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.5648148148148148,\n\ \ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.5705521472392638,\n \"acc_stderr\": 0.03889066619112723,\n\ \ \"acc_norm\": 0.5705521472392638,\n \"acc_norm_stderr\": 0.03889066619112723\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.047268355537191,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.047268355537191\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.6699029126213593,\n \"acc_stderr\": 0.0465614711001235,\n\ \ \"acc_norm\": 0.6699029126213593,\n \"acc_norm_stderr\": 0.0465614711001235\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.7863247863247863,\n\ \ \"acc_stderr\": 0.026853450377009157,\n \"acc_norm\": 0.7863247863247863,\n\ \ \"acc_norm_stderr\": 0.026853450377009157\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.6730523627075351,\n\ \ \"acc_stderr\": 0.016774908180131467,\n \"acc_norm\": 0.6730523627075351,\n\ \ \"acc_norm_stderr\": 0.016774908180131467\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.5144508670520231,\n \"acc_stderr\": 0.02690784985628254,\n\ \ \"acc_norm\": 0.5144508670520231,\n \"acc_norm_stderr\": 0.02690784985628254\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.41564245810055866,\n\ \ \"acc_stderr\": 0.016482782187500662,\n \"acc_norm\": 0.41564245810055866,\n\ \ \"acc_norm_stderr\": 0.016482782187500662\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5163398692810458,\n \"acc_stderr\": 0.028614624752805427,\n\ \ \"acc_norm\": 0.5163398692810458,\n \"acc_norm_stderr\": 0.028614624752805427\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.5209003215434084,\n\ \ \"acc_stderr\": 0.02837327096106942,\n \"acc_norm\": 0.5209003215434084,\n\ \ \"acc_norm_stderr\": 0.02837327096106942\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.5185185185185185,\n \"acc_stderr\": 0.027801656212323674,\n\ \ \"acc_norm\": 0.5185185185185185,\n \"acc_norm_stderr\": 0.027801656212323674\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.38652482269503546,\n \"acc_stderr\": 0.029049190342543465,\n \ \ \"acc_norm\": 0.38652482269503546,\n \"acc_norm_stderr\": 0.029049190342543465\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3728813559322034,\n\ \ \"acc_stderr\": 0.012350630058333353,\n \"acc_norm\": 0.3728813559322034,\n\ \ \"acc_norm_stderr\": 0.012350630058333353\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.40441176470588236,\n \"acc_stderr\": 0.029812630701569743,\n\ \ \"acc_norm\": 0.40441176470588236,\n \"acc_norm_stderr\": 0.029812630701569743\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.45588235294117646,\n \"acc_stderr\": 0.020148939420415738,\n \ \ \"acc_norm\": 0.45588235294117646,\n \"acc_norm_stderr\": 0.020148939420415738\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.5909090909090909,\n\ \ \"acc_stderr\": 0.04709306978661896,\n \"acc_norm\": 0.5909090909090909,\n\ \ \"acc_norm_stderr\": 0.04709306978661896\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.5306122448979592,\n \"acc_stderr\": 0.031949171367580624,\n\ \ \"acc_norm\": 0.5306122448979592,\n \"acc_norm_stderr\": 0.031949171367580624\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.572139303482587,\n\ \ \"acc_stderr\": 0.03498541988407795,\n \"acc_norm\": 0.572139303482587,\n\ \ \"acc_norm_stderr\": 0.03498541988407795\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.65,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.65,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.39759036144578314,\n\ \ \"acc_stderr\": 0.038099730845402184,\n \"acc_norm\": 0.39759036144578314,\n\ \ \"acc_norm_stderr\": 0.038099730845402184\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7017543859649122,\n \"acc_stderr\": 0.03508771929824563,\n\ \ \"acc_norm\": 0.7017543859649122,\n \"acc_norm_stderr\": 0.03508771929824563\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.32558139534883723,\n\ \ \"mc1_stderr\": 0.016403989469907825,\n \"mc2\": 0.5188093512935639,\n\ \ \"mc2_stderr\": 0.016351300657386426\n }\n}\n```" repo_url: https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|arc:challenge\|25_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hellaswag\|10_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-14T19-14-45.418998.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-14T19-14-45.418998.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_14T19_14_45.418998 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-14T19-14-45.418998.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-14T19-14-45.418998.parquet' - config_name: results data_files: - split: 2023_09_14T19_14_45.418998 path: - results_2023-09-14T19-14-45.418998.parquet - split: latest path: - results_2023-09-14T19-14-45.418998.parquet --- # Dataset Card for Evaluation run of aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2 ## Dataset Description - Homepage: - Repository: https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2](https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-14T19:14:45.418998](https://huggingface.co/datasets/open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2/blob/main/results_2023-09-14T19-14-45.418998.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.4945007463965186, "acc_stderr": 0.03527731102256181, "acc_norm": 0.49711825981073476, "acc_norm_stderr": 0.035276035393914426, "mc1": 0.32558139534883723, "mc1_stderr": 0.016403989469907825, "mc2": 0.5188093512935639, "mc2_stderr": 0.016351300657386426 }, "harness\|arc:challenge\|25": { "acc": 0.4351535836177474, "acc_stderr": 0.014487986197186043, "acc_norm": 0.4453924914675768, "acc_norm_stderr": 0.01452398763834409 }, "harness\|hellaswag\|10": { "acc": 0.4660426209918343, "acc_stderr": 0.004978260641742204, "acc_norm": 0.6102370045807608, "acc_norm_stderr": 0.004866997110388195 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.47368421052631576, "acc_stderr": 0.04063302731486671, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.04063302731486671 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5320754716981132, "acc_stderr": 0.030709486992556538, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.030709486992556538 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.5277777777777778, "acc_stderr": 0.04174752578923185, "acc_norm": 0.5277777777777778, "acc_norm_stderr": 0.04174752578923185 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.4797687861271676, "acc_stderr": 0.03809342081273957, "acc_norm": 0.4797687861271676, "acc_norm_stderr": 0.03809342081273957 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.2647058823529412, "acc_stderr": 0.04389869956808778, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.04389869956808778 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.425531914893617, "acc_stderr": 0.032321469162244695, "acc_norm": 0.425531914893617, "acc_norm_stderr": 0.032321469162244695 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4206896551724138, "acc_stderr": 0.0411391498118926, "acc_norm": 0.4206896551724138, "acc_norm_stderr": 0.0411391498118926 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.02326651221373057, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.02326651221373057 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3412698412698413, "acc_stderr": 0.04240799327574924, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.04240799327574924 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.535483870967742, "acc_stderr": 0.028372287797962935, "acc_norm": 0.535483870967742, "acc_norm_stderr": 0.028372287797962935 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3842364532019704, "acc_stderr": 0.03422398565657551, "acc_norm": 0.3842364532019704, "acc_norm_stderr": 0.03422398565657551 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.56, "acc_stderr": 0.049888765156985884, "acc_norm": 0.56, "acc_norm_stderr": 0.049888765156985884 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6363636363636364, "acc_stderr": 0.03756335775187896, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.03756335775187896 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.6515151515151515, "acc_stderr": 0.033948539651564025, "acc_norm": 0.6515151515151515, "acc_norm_stderr": 0.033948539651564025 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7461139896373057, "acc_stderr": 0.0314102478056532, "acc_norm": 0.7461139896373057, "acc_norm_stderr": 0.0314102478056532 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5153846153846153, "acc_stderr": 0.025339003010106515, "acc_norm": 0.5153846153846153, "acc_norm_stderr": 0.025339003010106515 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2851851851851852, "acc_stderr": 0.02752859921034049, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.02752859921034049 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.47058823529411764, "acc_stderr": 0.03242225027115006, "acc_norm": 0.47058823529411764, "acc_norm_stderr": 0.03242225027115006 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.32450331125827814, "acc_stderr": 0.038227469376587525, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.038227469376587525 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.6495412844036698, "acc_stderr": 0.020456077599824467, "acc_norm": 0.6495412844036698, "acc_norm_stderr": 0.020456077599824467 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.28703703703703703, "acc_stderr": 0.030851992993257013, "acc_norm": 0.28703703703703703, "acc_norm_stderr": 0.030851992993257013 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.5784313725490197, "acc_stderr": 0.03465868196380762, "acc_norm": 0.5784313725490197, "acc_norm_stderr": 0.03465868196380762 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.6582278481012658, "acc_stderr": 0.030874537537553617, "acc_norm": 0.6582278481012658, "acc_norm_stderr": 0.030874537537553617 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.5739910313901345, "acc_stderr": 0.033188332862172806, "acc_norm": 0.5739910313901345, "acc_norm_stderr": 0.033188332862172806 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5572519083969466, "acc_stderr": 0.0435644720266507, "acc_norm": 0.5572519083969466, "acc_norm_stderr": 0.0435644720266507 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.6033057851239669, "acc_stderr": 0.04465869780531009, "acc_norm": 0.6033057851239669, "acc_norm_stderr": 0.04465869780531009 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.5648148148148148, "acc_stderr": 0.04792898170907061, "acc_norm": 0.5648148148148148, "acc_norm_stderr": 0.04792898170907061 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.5705521472392638, "acc_stderr": 0.03889066619112723, "acc_norm": 0.5705521472392638, "acc_norm_stderr": 0.03889066619112723 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.45535714285714285, "acc_stderr": 0.047268355537191, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.047268355537191 }, "harness\|hendrycksTest-management\|5": { "acc": 0.6699029126213593, "acc_stderr": 0.0465614711001235, "acc_norm": 0.6699029126213593, "acc_norm_stderr": 0.0465614711001235 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.7863247863247863, "acc_stderr": 0.026853450377009157, "acc_norm": 0.7863247863247863, "acc_norm_stderr": 0.026853450377009157 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.6730523627075351, "acc_stderr": 0.016774908180131467, "acc_norm": 0.6730523627075351, "acc_norm_stderr": 0.016774908180131467 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.5144508670520231, "acc_stderr": 0.02690784985628254, "acc_norm": 0.5144508670520231, "acc_norm_stderr": 0.02690784985628254 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.41564245810055866, "acc_stderr": 0.016482782187500662, "acc_norm": 0.41564245810055866, "acc_norm_stderr": 0.016482782187500662 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.5163398692810458, "acc_stderr": 0.028614624752805427, "acc_norm": 0.5163398692810458, "acc_norm_stderr": 0.028614624752805427 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.5209003215434084, "acc_stderr": 0.02837327096106942, "acc_norm": 0.5209003215434084, "acc_norm_stderr": 0.02837327096106942 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.5185185185185185, "acc_stderr": 0.027801656212323674, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.027801656212323674 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.38652482269503546, "acc_stderr": 0.029049190342543465, "acc_norm": 0.38652482269503546, "acc_norm_stderr": 0.029049190342543465 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3728813559322034, "acc_stderr": 0.012350630058333353, "acc_norm": 0.3728813559322034, "acc_norm_stderr": 0.012350630058333353 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.40441176470588236, "acc_stderr": 0.029812630701569743, "acc_norm": 0.40441176470588236, "acc_norm_stderr": 0.029812630701569743 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.45588235294117646, "acc_stderr": 0.020148939420415738, "acc_norm": 0.45588235294117646, "acc_norm_stderr": 0.020148939420415738 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.5909090909090909, "acc_stderr": 0.04709306978661896, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.04709306978661896 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.5306122448979592, "acc_stderr": 0.031949171367580624, "acc_norm": 0.5306122448979592, "acc_norm_stderr": 0.031949171367580624 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.572139303482587, "acc_stderr": 0.03498541988407795, "acc_norm": 0.572139303482587, "acc_norm_stderr": 0.03498541988407795 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.65, "acc_stderr": 0.0479372485441102, "acc_norm": 0.65, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.39759036144578314, "acc_stderr": 0.038099730845402184, "acc_norm": 0.39759036144578314, "acc_norm_stderr": 0.038099730845402184 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7017543859649122, "acc_stderr": 0.03508771929824563, "acc_norm": 0.7017543859649122, "acc_norm_stderr": 0.03508771929824563 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.32558139534883723, "mc1_stderr": 0.016403989469907825, "mc2": 0.5188093512935639, "mc2_stderr": 0.016351300657386426 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.6917582750320435, -0.8863488435745239, 0.2444681078195572, 0.21955189108848572, -0.16950513422489166, -0.01821230538189411, -0.022385558113455772, -0.20394641160964966, 0.5876709222793579, -0.05081917345523834, -0.48791059851646423, -0.6732193231582642, -0.44697892665863037, 0.241201251745224, -0.05290975421667099, 0.8216570615768433, -0.17402775585651398, -0.14296841621398926, 0.07033505290746689, -0.054405707865953445, -0.26064953207969666, -0.35940420627593994, 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accavdar/donut_employee_info_v1	accavdar	2023-11-09T23:52:57Z	254	0	[ "region:us" ]	null	2023-11-09T23:52:48Z	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: ground_truth dtype: string splits: - name: train num_bytes: 6186374.0 num_examples: 80 - name: test num_bytes: 1540228.0 num_examples: 20 download_size: 6685265 dataset_size: 7726602.0 --- # Dataset Card for "donut_employee_info_v1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.12233609706163406, -0.27155494689941406, 0.24370864033699036, 0.042469292879104614, 0.022411571815609932, -0.08018138259649277, 0.32730215787887573, -0.14824946224689484, 0.9385977983474731, 0.6919660568237305, -0.9987242817878723, -0.6066684126853943, -0.5580957531929016, -0.27971434593200684, -0.280835896730423, 1.375502109527588, 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Graphcore/gqa-lxmert	Graphcore	2023-01-09T11:28:07Z	253	0	[ "language:en", "license:cc-by-4.0", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en license: - cc-by-4.0 ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 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albertvillanova/sat	albertvillanova	2022-10-24T15:25:54Z	253	0	[ "task_categories:text-generation", "task_categories:translation", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:translation", "size_categories:1M<n<10M", "source_datasets:original", "source_datasets:extended\|bible_para", "source_datasets:extended\|kde4", "source_datasets:extended\|opus_gnome", "source_datasets:extended\|open_subtitles", "source_datasets:extended\|tatoeba", "language:en", "language:vi", "license:unknown", "conditional-text-generation", "region:us" ]	[ "text-generation", "translation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - en - vi license: - unknown multilinguality: - translation size_categories: - 1M<n<10M source_datasets: - original - extended\|bible_para - extended\|kde4 - extended\|opus_gnome - extended\|open_subtitles - extended\|tatoeba task_categories: - text-generation - translation task_ids: [] pretty_name: SAT tags: - conditional-text-generation --- # Dataset Card for SAT ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://blog.vietai.org/sat/ - Repository: https://github.com/vietai/sat - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary SAT (Style Augmented Translation) dataset contains roughly 3.3 million English-Vietnamese pairs of texts. ### Supported Tasks and Leaderboards - Machine Translation ### Languages The languages in the dataset are: - Vietnamese (`vi`) - English (`en`) ## Dataset Structure ### Data Instances ``` { 'translation': { 'en': 'Rachel Pike : The science behind a climate headline', 'vi': 'Khoa học đằng sau một tiêu đề về khí hậu' } } ``` ### Data Fields - `translation`: - `en`: Parallel text in English. - `vi`: Parallel text in Vietnamese. ### Data Splits The dataset is split in "train" and "test". \| \| train \| test \| \|--------------------\|--------:\|-----:\| \| Number of examples \| 3359574 \| 7221 \| ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Unknown. ### Citation Information Unknown. ### Contributions Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.	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mozilla-foundation/common_voice_10_0	mozilla-foundation	2023-07-29T16:00:14Z	253	19	[ "task_categories:automatic-speech-recognition", "annotations_creators:crowdsourced", "language_creators:crowdsourced", "multilinguality:multilingual", "source_datasets:extended\|common_voice", "license:cc0-1.0", "arxiv:1912.06670", "region:us" ]	[ "automatic-speech-recognition" ]	2022-07-22T15:10:26Z	--- pretty_name: Common Voice Corpus 10.0 annotations_creators: - crowdsourced language_creators: - crowdsourced language_bcp47: - ab - ar - as - ast - az - ba - bas - be - bg - bn - br - ca - ckb - cnh - cs - cv - cy - da - de - dv - el - en - eo - es - et - eu - fa - fi - fr - fy-NL - ga-IE - gl - gn - ha - hi - hsb - hu - hy-AM - ia - id - ig - it - ja - ka - kab - kk - kmr - ky - lg - lt - lv - mdf - mhr - mk - ml - mn - mr - mt - myv - nan-tw - ne-NP - nl - nn-NO - or - pa-IN - pl - pt - rm-sursilv - rm-vallader - ro - ru - rw - sah - sat - sc - sk - sl - sr - sv-SE - sw - ta - th - tig - tok - tr - tt - ug - uk - ur - uz - vi - vot - yue - zh-CN - zh-HK - zh-TW license: - cc0-1.0 multilinguality: - multilingual size_categories: ab: - 10K<n<100K ar: - 100K<n<1M as: - 1K<n<10K ast: - n<1K az: - n<1K ba: - 100K<n<1M bas: - 1K<n<10K be: - 100K<n<1M bg: - 1K<n<10K bn: - 100K<n<1M br: - 10K<n<100K ca: - 1M<n<10M ckb: - 100K<n<1M cnh: - 1K<n<10K cs: - 10K<n<100K cv: - 10K<n<100K cy: - 100K<n<1M da: - 1K<n<10K de: - 100K<n<1M dv: - 10K<n<100K el: - 10K<n<100K en: - 1M<n<10M eo: - 1M<n<10M es: - 100K<n<1M et: - 10K<n<100K eu: - 100K<n<1M fa: - 100K<n<1M fi: - 10K<n<100K fr: - 100K<n<1M fy-NL: - 10K<n<100K ga-IE: - 1K<n<10K gl: - 10K<n<100K gn: - 1K<n<10K ha: - 1K<n<10K hi: - 10K<n<100K hsb: - 1K<n<10K hu: - 10K<n<100K hy-AM: - 1K<n<10K ia: - 10K<n<100K id: - 10K<n<100K ig: - 1K<n<10K it: - 100K<n<1M ja: - 10K<n<100K ka: - 1K<n<10K kab: - 100K<n<1M kk: - 1K<n<10K kmr: - 10K<n<100K ky: - 10K<n<100K lg: - 100K<n<1M lt: - 10K<n<100K lv: - 1K<n<10K mdf: - n<1K mhr: - 10K<n<100K mk: - n<1K ml: - 1K<n<10K mn: - 10K<n<100K mr: - 10K<n<100K mt: - 10K<n<100K myv: - 1K<n<10K nan-tw: - 10K<n<100K ne-NP: - n<1K nl: - 10K<n<100K nn-NO: - n<1K or: - 1K<n<10K pa-IN: - 1K<n<10K pl: - 100K<n<1M pt: - 100K<n<1M rm-sursilv: - 1K<n<10K rm-vallader: - 1K<n<10K ro: - 10K<n<100K ru: - 100K<n<1M rw: - 1M<n<10M sah: - 1K<n<10K sat: - n<1K sc: - n<1K sk: - 10K<n<100K sl: - 10K<n<100K sr: - 1K<n<10K sv-SE: - 10K<n<100K sw: - 100K<n<1M ta: - 100K<n<1M th: - 100K<n<1M tig: - n<1K tok: - 1K<n<10K tr: - 10K<n<100K tt: - 10K<n<100K ug: - 10K<n<100K uk: - 10K<n<100K ur: - 100K<n<1M uz: - 100K<n<1M vi: - 10K<n<100K vot: - n<1K yue: - 10K<n<100K zh-CN: - 100K<n<1M zh-HK: - 100K<n<1M zh-TW: - 100K<n<1M source_datasets: - extended\|common_voice task_categories: - automatic-speech-recognition paperswithcode_id: common-voice extra_gated_prompt: "By clicking on “Access repository” below, you also agree to not attempt to determine the identity of speakers in the Common Voice dataset." --- # Dataset Card for Common Voice Corpus 10.0 ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://commonvoice.mozilla.org/en/datasets - Repository: https://github.com/common-voice/common-voice - Paper: https://arxiv.org/abs/1912.06670 - Leaderboard: https://paperswithcode.com/dataset/common-voice - Point of Contact: [Anton Lozhkov](mailto:[email protected]) ### Dataset Summary The Common Voice dataset consists of a unique MP3 and corresponding text file. Many of the 20817 recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help improve the accuracy of speech recognition engines. The dataset currently consists of 15234 validated hours in 96 languages, but more voices and languages are always added. Take a look at the [Languages](https://commonvoice.mozilla.org/en/languages) page to request a language or start contributing. ### Supported Tasks and Leaderboards The results for models trained on the Common Voice datasets are available via the [🤗 Speech Bench](https://huggingface.co/spaces/huggingface/hf-speech-bench) ### Languages ``` Abkhaz, Arabic, Armenian, Assamese, Asturian, Azerbaijani, Basaa, Bashkir, Basque, Belarusian, Bengali, Breton, Bulgarian, Cantonese, Catalan, Central Kurdish, Chinese (China), Chinese (Hong Kong), Chinese (Taiwan), Chuvash, Czech, Danish, Dhivehi, Dutch, English, Erzya, Esperanto, Estonian, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Hakha Chin, Hausa, Hindi, Hungarian, Igbo, Indonesian, Interlingua, Irish, Italian, Japanese, Kabyle, Kazakh, Kinyarwanda, Kurmanji Kurdish, Kyrgyz, Latvian, Lithuanian, Luganda, Macedonian, Malayalam, Maltese, Marathi, Meadow Mari, Moksha, Mongolian, Nepali, Norwegian Nynorsk, Odia, Persian, Polish, Portuguese, Punjabi, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Sardinian, Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamil, Tatar, Thai, Tigre, Toki Pona, Turkish, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh ``` ## Dataset Structure ### Data Instances A typical data point comprises the `path` to the audio file and its `sentence`. Additional fields include `accent`, `age`, `client_id`, `up_votes`, `down_votes`, `gender`, `locale` and `segment`. ```python { 'client_id': 'd59478fbc1ee646a28a3c652a119379939123784d99131b865a89f8b21c81f69276c48bd574b81267d9d1a77b83b43e6d475a6cfc79c232ddbca946ae9c7afc5', 'path': 'et/clips/common_voice_et_18318995.mp3', 'audio': { 'path': 'et/clips/common_voice_et_18318995.mp3', 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), 'sampling_rate': 48000 }, 'sentence': 'Tasub kokku saada inimestega, keda tunned juba ammust ajast saati.', 'up_votes': 2, 'down_votes': 0, 'age': 'twenties', 'gender': 'male', 'accent': '', 'locale': 'et', 'segment': '' } ``` ### Data Fields `client_id` (`string`): An id for which client (voice) made the recording `path` (`string`): The path to the audio file `audio` (`dict`): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, i.e. `dataset[0]["audio"]` should always be preferred over `dataset["audio"][0]`. `sentence` (`string`): The sentence the user was prompted to speak `up_votes` (`int64`): How many upvotes the audio file has received from reviewers `down_votes` (`int64`): How many downvotes the audio file has received from reviewers `age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`) `gender` (`string`): The gender of the speaker `accent` (`string`): Accent of the speaker `locale` (`string`): The locale of the speaker `segment` (`string`): Usually an empty field ### Data Splits The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other. The validated data is data that has been validated with reviewers and received upvotes that the data is of high quality. The invalidated data is data has been invalidated by reviewers and received downvotes indicating that the data is of low quality. The reported data is data that has been reported, for different reasons. The other data is data that has not yet been reviewed. The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train. ## Data Preprocessing Recommended by Hugging Face The following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice. Many examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_. In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, almost all sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation. ```python from datasets import load_dataset ds = load_dataset("mozilla-foundation/common_voice_10_0", "en", use_auth_token=True) def prepare_dataset(batch): """Function to preprocess the dataset with the .map method""" transcription = batch["sentence"] if transcription.startswith('"') and transcription.endswith('"'): # we can remove trailing quotation marks as they do not affect the transcription transcription = transcription[1:-1] if transcription[-1] not in [".", "?", "!"]: # append a full-stop to sentences that do not end in punctuation transcription = transcription + "." batch["sentence"] = transcription return batch ds = ds.map(prepare_dataset, desc="preprocess dataset") ``` ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset. ## Considerations for Using the Data ### Social Impact of Dataset The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset. ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/) ### Citation Information ``` @inproceedings{commonvoice:2020, author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.}, title = {Common Voice: A Massively-Multilingual Speech Corpus}, booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)}, pages = {4211--4215}, year = 2020 } ```	[ -0.5463180541992188, -0.7199245095252991, 0.14910103380680084, 0.4297794997692108, -0.26992735266685486, 0.043433777987957, -0.5827479958534241, -0.2093125283718109, 0.4495946168899536, 0.5330334305763245, -0.7590958476066589, -1.0002228021621704, -0.4513309597969055, 0.2508442997932434, -0.2750920355319977, 0.9573414325714111, 0.423595130443573, 0.08026961237192154, -0.0691586285829544, -0.17915478348731995, -0.36970722675323486, -0.6519954204559326, -0.6398017406463623, -0.023742808029055595, 0.16831807792186737, 0.6004095673561096, 0.4479852020740509, 0.551845371723175, 0.22364069521427155, 0.34309065341949463, -0.31872957944869995, 0.08719608932733536, -0.2932213842868805, 0.04885257035493851, 0.10869868099689484, -0.3277225196361542, -0.45074883103370667, 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haitengzhao/molecule_property_instruction	haitengzhao	2023-07-13T10:30:29Z	253	4	[ "task_categories:question-answering", "language:en", "license:afl-3.0", "chemistry", "biology", "region:us" ]	[ "question-answering" ]	2023-07-09T07:36:09Z	--- dataset_info: features: - name: graph dtype: string - name: text sequence: string - name: label dtype: string - name: dataset_name dtype: string - name: task_index dtype: string - name: molecule_index dtype: string - name: split dtype: string splits: - name: esol num_bytes: 542831 num_examples: 1128 - name: lipo num_bytes: 1519836 num_examples: 4200 - name: freesolv num_bytes: 527615 num_examples: 642 - name: bace num_bytes: 5103112 num_examples: 1513 - name: hiv num_bytes: 215094514 num_examples: 41127 - name: muv num_bytes: 594798639 num_examples: 249886 - name: tox21 num_bytes: 121153396 num_examples: 77946 - name: toxcast num_bytes: 1543462519 num_examples: 1490412 - name: bbbp num_bytes: 2521597 num_examples: 2039 - name: cyp450 num_bytes: 30602477 num_examples: 53178 - name: chembl_zero_shot num_bytes: 89499667 num_examples: 180229 - name: chembl_pretraining num_bytes: 12246285194 num_examples: 23874346 - name: pcba num_bytes: 21761726609 num_examples: 34017170 download_size: 2163300521 dataset_size: 36612838006 license: afl-3.0 task_categories: - question-answering language: - en tags: - chemistry - biology pretty_name: p --- # Dataset Card for "molecule_property_instruction" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.490411639213562, -0.5719837546348572, 0.14333072304725647, 0.0008006074349395931, -0.02975170500576496, 0.009086530655622482, -0.008314290083944798, 0.0727001279592514, 0.5624854564666748, 0.5143765807151794, -0.6538606286048889, -0.8867617249488831, -0.5814072489738464, -0.40854647755622864, -0.12497846782207489, 1.3997881412506104, -0.02739897556602955, 0.3431890606880188, -0.5720162987709045, 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open-llm-leaderboard/details_bhenrym14__airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16	open-llm-leaderboard	2023-09-23T11:51:16Z	253	0	[ "region:us" ]	null	2023-08-18T11:17:33Z	--- pretty_name: Evaluation run of bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16](https://huggingface.co/bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_bhenrym14__airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T11:51:04.890467](https://huggingface.co/datasets/open-llm-leaderboard/details_bhenrym14__airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16/blob/main/results_2023-09-23T11-51-04.890467.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.05044043624161074,\n\ \ \"em_stderr\": 0.002241249338683634,\n \"f1\": 0.1215436241610737,\n\ \ \"f1_stderr\": 0.002582740471791708,\n \"acc\": 0.4114226953164035,\n\ \ \"acc_stderr\": 0.01004007069157239\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.05044043624161074,\n \"em_stderr\": 0.002241249338683634,\n\ \ \"f1\": 0.1215436241610737,\n \"f1_stderr\": 0.002582740471791708\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08567096285064443,\n \ \ \"acc_stderr\": 0.007709218855882771\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7371744277821626,\n \"acc_stderr\": 0.012370922527262008\n\ \ }\n}\n```" repo_url: https://huggingface.co/bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|arc:challenge\|25_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-09T13:44:06.910726.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T02_06_28.152881 path: - '/details_harness\|drop\|3_2023-09-23T02-06-28.152881.parquet' - split: 2023_09_23T11_51_04.890467 path: - '/details_harness\|drop\|3_2023-09-23T11-51-04.890467.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-23T11-51-04.890467.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T02_06_28.152881 path: - '/details_harness\|gsm8k\|5_2023-09-23T02-06-28.152881.parquet' - split: 2023_09_23T11_51_04.890467 path: - '/details_harness\|gsm8k\|5_2023-09-23T11-51-04.890467.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-23T11-51-04.890467.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hellaswag\|10_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:44:06.910726.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:44:06.910726.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T13_44_06.910726 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T13:44:06.910726.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T13:44:06.910726.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T02_06_28.152881 path: - '/details_harness\|winogrande\|5_2023-09-23T02-06-28.152881.parquet' - split: 2023_09_23T11_51_04.890467 path: - '/details_harness\|winogrande\|5_2023-09-23T11-51-04.890467.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-23T11-51-04.890467.parquet' - config_name: results data_files: - split: 2023_08_09T13_44_06.910726 path: - results_2023-08-09T13:44:06.910726.parquet - split: 2023_09_23T02_06_28.152881 path: - results_2023-09-23T02-06-28.152881.parquet - split: 2023_09_23T11_51_04.890467 path: - results_2023-09-23T11-51-04.890467.parquet - split: latest path: - results_2023-09-23T11-51-04.890467.parquet --- # Dataset Card for Evaluation run of bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 ## Dataset Description - Homepage: - Repository: https://huggingface.co/bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16](https://huggingface.co/bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_bhenrym14__airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T11:51:04.890467](https://huggingface.co/datasets/open-llm-leaderboard/details_bhenrym14__airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16/blob/main/results_2023-09-23T11-51-04.890467.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.05044043624161074, "em_stderr": 0.002241249338683634, "f1": 0.1215436241610737, "f1_stderr": 0.002582740471791708, "acc": 0.4114226953164035, "acc_stderr": 0.01004007069157239 }, "harness\|drop\|3": { "em": 0.05044043624161074, "em_stderr": 0.002241249338683634, "f1": 0.1215436241610737, "f1_stderr": 0.002582740471791708 }, "harness\|gsm8k\|5": { "acc": 0.08567096285064443, "acc_stderr": 0.007709218855882771 }, "harness\|winogrande\|5": { "acc": 0.7371744277821626, "acc_stderr": 0.012370922527262008 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.42493292689323425, -0.6725358963012695, 0.2199561446905136, 0.22950267791748047, -0.13193459808826447, 0.12155544012784958, -0.3951758146286011, -0.1860353648662567, 0.3367738723754883, 0.46091219782829285, -0.708634614944458, -0.8840764164924622, -0.6912842988967896, 0.1727220118045807, -0.12903960049152374, 1.1181604862213135, -0.31022781133651733, -0.26730021834373474, 0.10192236304283142, -0.23995377123355865, -0.3535810112953186, -0.5054139494895935, -0.49429020285606384, 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open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M	open-llm-leaderboard	2023-10-19T04:17:16Z	253	0	[ "region:us" ]	null	2023-08-18T11:45:50Z	--- pretty_name: Evaluation run of KoboldAI/fairseq-dense-125M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [KoboldAI/fairseq-dense-125M](https://huggingface.co/KoboldAI/fairseq-dense-125M)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-19T04:17:04.516677](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M/blob/main/results_2023-10-19T04-17-04.516677.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.016149328859060404,\n\ \ \"em_stderr\": 0.001290866955681,\n \"f1\": 0.0550492869127517,\n\ \ \"f1_stderr\": 0.0017708903745179366,\n \"acc\": 0.25295974743488553,\n\ \ \"acc_stderr\": 0.007025750419242903\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.016149328859060404,\n \"em_stderr\": 0.001290866955681,\n\ \ \"f1\": 0.0550492869127517,\n \"f1_stderr\": 0.0017708903745179366\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5059194948697711,\n\ \ \"acc_stderr\": 0.014051500838485807\n }\n}\n```" repo_url: https://huggingface.co/KoboldAI/fairseq-dense-125M leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|arc:challenge\|25_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T13:55:37.353557.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_19T04_17_04.516677 path: - '/details_harness\|drop\|3_2023-10-19T04-17-04.516677.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-19T04-17-04.516677.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_19T04_17_04.516677 path: - '/details_harness\|gsm8k\|5_2023-10-19T04-17-04.516677.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-19T04-17-04.516677.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hellaswag\|10_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T13:55:37.353557.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T13:55:37.353557.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T13_55_37.353557 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T13:55:37.353557.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T13:55:37.353557.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_19T04_17_04.516677 path: - '/details_harness\|winogrande\|5_2023-10-19T04-17-04.516677.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-19T04-17-04.516677.parquet' - config_name: results data_files: - split: 2023_07_19T13_55_37.353557 path: - results_2023-07-19T13:55:37.353557.parquet - split: 2023_10_19T04_17_04.516677 path: - results_2023-10-19T04-17-04.516677.parquet - split: latest path: - results_2023-10-19T04-17-04.516677.parquet --- # Dataset Card for Evaluation run of KoboldAI/fairseq-dense-125M ## Dataset Description - Homepage: - Repository: https://huggingface.co/KoboldAI/fairseq-dense-125M - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [KoboldAI/fairseq-dense-125M](https://huggingface.co/KoboldAI/fairseq-dense-125M) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-19T04:17:04.516677](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M/blob/main/results_2023-10-19T04-17-04.516677.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.016149328859060404, "em_stderr": 0.001290866955681, "f1": 0.0550492869127517, "f1_stderr": 0.0017708903745179366, "acc": 0.25295974743488553, "acc_stderr": 0.007025750419242903 }, "harness\|drop\|3": { "em": 0.016149328859060404, "em_stderr": 0.001290866955681, "f1": 0.0550492869127517, "f1_stderr": 0.0017708903745179366 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5059194948697711, "acc_stderr": 0.014051500838485807 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.41947999596595764, -0.6736559271812439, 0.26720914244651794, 0.23512864112854004, -0.08532483130693436, -0.046073269098997116, -0.41046860814094543, -0.17484146356582642, 0.3236300051212311, 0.5921817421913147, -0.7061313390731812, -0.8716518878936768, -0.6609933972358704, 0.17273592948913574, -0.1544647365808487, 1.1074832677841187, -0.22402238845825195, -0.15168456733226776, 0.06307147443294525, -0.43331703543663025, -0.40759187936782837, -0.43057024478912354, -0.5671939253807068, 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open-llm-leaderboard/details_NousResearch__Nous-Hermes-Llama2-70b	open-llm-leaderboard	2023-08-27T12:43:54Z	253	0	[ "region:us" ]	null	2023-08-27T11:50:20Z	--- pretty_name: Evaluation run of NousResearch/Nous-Hermes-Llama2-70b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NousResearch/Nous-Hermes-Llama2-70b](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-70b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 60 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_NousResearch__Nous-Hermes-Llama2-70b\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-24T16:19:15.258893](https://huggingface.co/datasets/open-llm-leaderboard/details_NousResearch__Nous-Hermes-Llama2-70b/blob/main/results_2023-08-24T16%3A19%3A15.258893.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6957673179292897,\n\ \ \"acc_stderr\": 0.030886230677725023,\n \"acc_norm\": 0.6997447643290794,\n\ \ \"acc_norm_stderr\": 0.030857325329783844,\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769632,\n \"mc2\": 0.5504358942461541,\n\ \ \"mc2_stderr\": 0.01494092300772985\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6313993174061433,\n \"acc_stderr\": 0.014097810678042196,\n\ \ \"acc_norm\": 0.6757679180887372,\n \"acc_norm_stderr\": 0.013678810399518826\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6777534355706034,\n\ \ \"acc_stderr\": 0.004663817291468729,\n \"acc_norm\": 0.8680541724756025,\n\ \ \"acc_norm_stderr\": 0.0033774020414626227\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047424,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047424\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.8026315789473685,\n \"acc_stderr\": 0.03238981601699397,\n\ \ \"acc_norm\": 0.8026315789473685,\n \"acc_norm_stderr\": 0.03238981601699397\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.720754716981132,\n \"acc_stderr\": 0.027611163402399715,\n\ \ \"acc_norm\": 0.720754716981132,\n \"acc_norm_stderr\": 0.027611163402399715\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8402777777777778,\n\ \ \"acc_stderr\": 0.030635578972093274,\n \"acc_norm\": 0.8402777777777778,\n\ \ \"acc_norm_stderr\": 0.030635578972093274\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n\ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105653,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105653\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.7148936170212766,\n \"acc_stderr\": 0.029513196625539355,\n\ \ \"acc_norm\": 0.7148936170212766,\n \"acc_norm_stderr\": 0.029513196625539355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4298245614035088,\n\ \ \"acc_stderr\": 0.046570472605949625,\n \"acc_norm\": 0.4298245614035088,\n\ \ \"acc_norm_stderr\": 0.046570472605949625\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.040131241954243856,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.040131241954243856\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.43915343915343913,\n \"acc_stderr\": 0.02555992055053101,\n \"\ acc_norm\": 0.43915343915343913,\n \"acc_norm_stderr\": 0.02555992055053101\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.47619047619047616,\n\ \ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.47619047619047616,\n\ \ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.8032258064516129,\n \"acc_stderr\": 0.022616409420742015,\n \"\ acc_norm\": 0.8032258064516129,\n \"acc_norm_stderr\": 0.022616409420742015\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.5467980295566502,\n \"acc_stderr\": 0.03502544650845872,\n \"\ acc_norm\": 0.5467980295566502,\n \"acc_norm_stderr\": 0.03502544650845872\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.74,\n \"acc_stderr\": 0.044084400227680794,\n \"acc_norm\"\ : 0.74,\n \"acc_norm_stderr\": 0.044084400227680794\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.02799807379878168,\n\ \ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.02799807379878168\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8737373737373737,\n \"acc_stderr\": 0.02366435940288022,\n \"\ acc_norm\": 0.8737373737373737,\n \"acc_norm_stderr\": 0.02366435940288022\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240528,\n\ \ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240528\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.7025641025641025,\n \"acc_stderr\": 0.023177408131465942,\n\ \ \"acc_norm\": 0.7025641025641025,\n \"acc_norm_stderr\": 0.023177408131465942\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3111111111111111,\n \"acc_stderr\": 0.02822644674968352,\n \ \ \"acc_norm\": 0.3111111111111111,\n \"acc_norm_stderr\": 0.02822644674968352\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.7605042016806722,\n \"acc_stderr\": 0.027722065493361276,\n\ \ \"acc_norm\": 0.7605042016806722,\n \"acc_norm_stderr\": 0.027722065493361276\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.48344370860927155,\n \"acc_stderr\": 0.0408024418562897,\n \"\ acc_norm\": 0.48344370860927155,\n \"acc_norm_stderr\": 0.0408024418562897\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8990825688073395,\n \"acc_stderr\": 0.012914673545364434,\n \"\ acc_norm\": 0.8990825688073395,\n \"acc_norm_stderr\": 0.012914673545364434\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5972222222222222,\n \"acc_stderr\": 0.03344887382997865,\n \"\ acc_norm\": 0.5972222222222222,\n \"acc_norm_stderr\": 0.03344887382997865\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9264705882352942,\n \"acc_stderr\": 0.01831885585008968,\n \"\ acc_norm\": 0.9264705882352942,\n \"acc_norm_stderr\": 0.01831885585008968\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8818565400843882,\n \"acc_stderr\": 0.021011052659878463,\n \ \ \"acc_norm\": 0.8818565400843882,\n \"acc_norm_stderr\": 0.021011052659878463\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7892376681614349,\n\ \ \"acc_stderr\": 0.02737309550054019,\n \"acc_norm\": 0.7892376681614349,\n\ \ \"acc_norm_stderr\": 0.02737309550054019\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8625954198473282,\n \"acc_stderr\": 0.030194823996804475,\n\ \ \"acc_norm\": 0.8625954198473282,\n \"acc_norm_stderr\": 0.030194823996804475\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8760330578512396,\n \"acc_stderr\": 0.030083098716035202,\n \"\ acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.030083098716035202\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8466257668711656,\n \"acc_stderr\": 0.028311601441438596,\n\ \ \"acc_norm\": 0.8466257668711656,\n \"acc_norm_stderr\": 0.028311601441438596\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5446428571428571,\n\ \ \"acc_stderr\": 0.04726835553719098,\n \"acc_norm\": 0.5446428571428571,\n\ \ \"acc_norm_stderr\": 0.04726835553719098\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8252427184466019,\n \"acc_stderr\": 0.0376017800602662,\n\ \ \"acc_norm\": 0.8252427184466019,\n \"acc_norm_stderr\": 0.0376017800602662\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9017094017094017,\n\ \ \"acc_stderr\": 0.019503444900757567,\n \"acc_norm\": 0.9017094017094017,\n\ \ \"acc_norm_stderr\": 0.019503444900757567\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8582375478927203,\n\ \ \"acc_stderr\": 0.012473289071272046,\n \"acc_norm\": 0.8582375478927203,\n\ \ \"acc_norm_stderr\": 0.012473289071272046\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7803468208092486,\n \"acc_stderr\": 0.022289638852617883,\n\ \ \"acc_norm\": 0.7803468208092486,\n \"acc_norm_stderr\": 0.022289638852617883\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4446927374301676,\n\ \ \"acc_stderr\": 0.01661988198817702,\n \"acc_norm\": 0.4446927374301676,\n\ \ \"acc_norm_stderr\": 0.01661988198817702\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7712418300653595,\n \"acc_stderr\": 0.024051029739912258,\n\ \ \"acc_norm\": 0.7712418300653595,\n \"acc_norm_stderr\": 0.024051029739912258\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7717041800643086,\n\ \ \"acc_stderr\": 0.023839303311398195,\n \"acc_norm\": 0.7717041800643086,\n\ \ \"acc_norm_stderr\": 0.023839303311398195\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8271604938271605,\n \"acc_stderr\": 0.02103851777015738,\n\ \ \"acc_norm\": 0.8271604938271605,\n \"acc_norm_stderr\": 0.02103851777015738\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5602836879432624,\n \"acc_stderr\": 0.029609912075594113,\n \ \ \"acc_norm\": 0.5602836879432624,\n \"acc_norm_stderr\": 0.029609912075594113\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5508474576271186,\n\ \ \"acc_stderr\": 0.012704030518851474,\n \"acc_norm\": 0.5508474576271186,\n\ \ \"acc_norm_stderr\": 0.012704030518851474\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.02667925227010313,\n\ \ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.02667925227010313\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7630718954248366,\n \"acc_stderr\": 0.01720166216978977,\n \ \ \"acc_norm\": 0.7630718954248366,\n \"acc_norm_stderr\": 0.01720166216978977\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7181818181818181,\n\ \ \"acc_stderr\": 0.043091187099464585,\n \"acc_norm\": 0.7181818181818181,\n\ \ \"acc_norm_stderr\": 0.043091187099464585\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.8081632653061225,\n \"acc_stderr\": 0.025206963154225378,\n\ \ \"acc_norm\": 0.8081632653061225,\n \"acc_norm_stderr\": 0.025206963154225378\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8706467661691543,\n\ \ \"acc_stderr\": 0.02372983088101853,\n \"acc_norm\": 0.8706467661691543,\n\ \ \"acc_norm_stderr\": 0.02372983088101853\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.91,\n \"acc_stderr\": 0.028762349126466125,\n \ \ \"acc_norm\": 0.91,\n \"acc_norm_stderr\": 0.028762349126466125\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5301204819277109,\n\ \ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\ \ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.025172984350155747,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.025172984350155747\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769632,\n \"mc2\": 0.5504358942461541,\n\ \ \"mc2_stderr\": 0.01494092300772985\n }\n}\n```" repo_url: https://huggingface.co/NousResearch/Nous-Hermes-Llama2-70b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|arc:challenge\|25_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hellaswag\|10_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-24T16:19:15.258893.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-24T16:19:15.258893.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_24T16_19_15.258893 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-24T16:19:15.258893.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-24T16:19:15.258893.parquet' --- # Dataset Card for Evaluation run of NousResearch/Nous-Hermes-Llama2-70b ## Dataset Description - Homepage: - Repository: https://huggingface.co/NousResearch/Nous-Hermes-Llama2-70b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [NousResearch/Nous-Hermes-Llama2-70b](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-70b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 60 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_NousResearch__Nous-Hermes-Llama2-70b", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-24T16:19:15.258893](https://huggingface.co/datasets/open-llm-leaderboard/details_NousResearch__Nous-Hermes-Llama2-70b/blob/main/results_2023-08-24T16%3A19%3A15.258893.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.6957673179292897, "acc_stderr": 0.030886230677725023, "acc_norm": 0.6997447643290794, "acc_norm_stderr": 0.030857325329783844, "mc1": 0.39167686658506734, "mc1_stderr": 0.017087795881769632, "mc2": 0.5504358942461541, "mc2_stderr": 0.01494092300772985 }, "harness\|arc:challenge\|25": { "acc": 0.6313993174061433, "acc_stderr": 0.014097810678042196, "acc_norm": 0.6757679180887372, "acc_norm_stderr": 0.013678810399518826 }, "harness\|hellaswag\|10": { "acc": 0.6777534355706034, "acc_stderr": 0.004663817291468729, "acc_norm": 0.8680541724756025, "acc_norm_stderr": 0.0033774020414626227 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047424, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047424 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.8026315789473685, "acc_stderr": 0.03238981601699397, "acc_norm": 0.8026315789473685, "acc_norm_stderr": 0.03238981601699397 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.720754716981132, "acc_stderr": 0.027611163402399715, "acc_norm": 0.720754716981132, "acc_norm_stderr": 0.027611163402399715 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8402777777777778, "acc_stderr": 0.030635578972093274, "acc_norm": 0.8402777777777778, "acc_norm_stderr": 0.030635578972093274 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105653, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105653 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.7148936170212766, "acc_stderr": 0.029513196625539355, "acc_norm": 0.7148936170212766, "acc_norm_stderr": 0.029513196625539355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4298245614035088, "acc_stderr": 0.046570472605949625, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.046570472605949625 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6344827586206897, "acc_stderr": 0.040131241954243856, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.040131241954243856 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.43915343915343913, "acc_stderr": 0.02555992055053101, "acc_norm": 0.43915343915343913, "acc_norm_stderr": 0.02555992055053101 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.47619047619047616, "acc_stderr": 0.04467062628403273, "acc_norm": 0.47619047619047616, "acc_norm_stderr": 0.04467062628403273 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8032258064516129, "acc_stderr": 0.022616409420742015, "acc_norm": 0.8032258064516129, "acc_norm_stderr": 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[More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7132309079170227, -0.8319036960601807, 0.31775686144828796, 0.20031167566776276, -0.1629723310470581, -0.05299433320760727, 0.0222731102257967, -0.2101498246192932, 0.6043255925178528, -0.00025939708575606346, -0.5079051852226257, -0.7251700758934021, -0.4431721866130829, 0.25901538133621216, -0.06334062665700912, 0.8766704797744751, -0.19931785762310028, -0.14262160658836365, 0.06546766310930252, -0.06339944899082184, -0.20408569276332855, -0.33621108531951904, -0.4882100224494934, 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open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-Fintune_1_17w-gate_up_down_proj	open-llm-leaderboard	2023-09-04T21:16:51Z	253	0	[ "region:us" ]	null	2023-09-04T21:15:54Z	--- pretty_name: Evaluation run of CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj](https://huggingface.co/CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-Fintune_1_17w-gate_up_down_proj\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-04T21:15:30.560082](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-Fintune_1_17w-gate_up_down_proj/blob/main/results_2023-09-04T21%3A15%3A30.560082.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.5475267614652215,\n\ \ \"acc_stderr\": 0.034609984402304776,\n \"acc_norm\": 0.5517087027206374,\n\ \ \"acc_norm_stderr\": 0.03459190488664288,\n \"mc1\": 0.25703794369645044,\n\ \ \"mc1_stderr\": 0.015298077509485076,\n \"mc2\": 0.369230031760143,\n\ \ \"mc2_stderr\": 0.013637900924748413\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5213310580204779,\n \"acc_stderr\": 0.014598087973127106,\n\ \ \"acc_norm\": 0.5614334470989761,\n \"acc_norm_stderr\": 0.014500682618212865\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6037641904003187,\n\ \ \"acc_stderr\": 0.0048811488668741845,\n \"acc_norm\": 0.8103963353913562,\n\ \ \"acc_norm_stderr\": 0.003911862797736198\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.45925925925925926,\n\ \ \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.45925925925925926,\n\ \ \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5526315789473685,\n \"acc_stderr\": 0.0404633688397825,\n\ \ \"acc_norm\": 0.5526315789473685,\n \"acc_norm_stderr\": 0.0404633688397825\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5886792452830188,\n \"acc_stderr\": 0.030285009259009794,\n\ \ \"acc_norm\": 0.5886792452830188,\n \"acc_norm_stderr\": 0.030285009259009794\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6041666666666666,\n\ \ \"acc_stderr\": 0.04089465449325583,\n \"acc_norm\": 0.6041666666666666,\n\ \ \"acc_norm_stderr\": 0.04089465449325583\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.44,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5144508670520231,\n\ \ \"acc_stderr\": 0.03810871630454764,\n \"acc_norm\": 0.5144508670520231,\n\ \ \"acc_norm_stderr\": 0.03810871630454764\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.7,\n\ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.451063829787234,\n \"acc_stderr\": 0.032529096196131965,\n\ \ \"acc_norm\": 0.451063829787234,\n \"acc_norm_stderr\": 0.032529096196131965\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3157894736842105,\n\ \ \"acc_stderr\": 0.04372748290278005,\n \"acc_norm\": 0.3157894736842105,\n\ \ \"acc_norm_stderr\": 0.04372748290278005\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5172413793103449,\n \"acc_stderr\": 0.04164188720169375,\n\ \ \"acc_norm\": 0.5172413793103449,\n \"acc_norm_stderr\": 0.04164188720169375\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3492063492063492,\n \"acc_stderr\": 0.024552292209342658,\n \"\ acc_norm\": 0.3492063492063492,\n \"acc_norm_stderr\": 0.024552292209342658\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.38095238095238093,\n\ \ \"acc_stderr\": 0.04343525428949097,\n \"acc_norm\": 0.38095238095238093,\n\ \ \"acc_norm_stderr\": 0.04343525428949097\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.6580645161290323,\n \"acc_stderr\": 0.026985289576552742,\n \"\ acc_norm\": 0.6580645161290323,\n \"acc_norm_stderr\": 0.026985289576552742\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.4236453201970443,\n \"acc_stderr\": 0.03476725747649037,\n \"\ acc_norm\": 0.4236453201970443,\n \"acc_norm_stderr\": 0.03476725747649037\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\"\ : 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6787878787878788,\n \"acc_stderr\": 0.036462049632538115,\n\ \ \"acc_norm\": 0.6787878787878788,\n \"acc_norm_stderr\": 0.036462049632538115\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7070707070707071,\n \"acc_stderr\": 0.03242497958178816,\n \"\ acc_norm\": 0.7070707070707071,\n \"acc_norm_stderr\": 0.03242497958178816\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7772020725388601,\n \"acc_stderr\": 0.030031147977641538,\n\ \ \"acc_norm\": 0.7772020725388601,\n \"acc_norm_stderr\": 0.030031147977641538\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4794871794871795,\n \"acc_stderr\": 0.02532966316348994,\n \ \ \"acc_norm\": 0.4794871794871795,\n \"acc_norm_stderr\": 0.02532966316348994\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3037037037037037,\n \"acc_stderr\": 0.028037929969114986,\n \ \ \"acc_norm\": 0.3037037037037037,\n \"acc_norm_stderr\": 0.028037929969114986\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5378151260504201,\n \"acc_stderr\": 0.032385469487589795,\n\ \ \"acc_norm\": 0.5378151260504201,\n \"acc_norm_stderr\": 0.032385469487589795\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7486238532110092,\n \"acc_stderr\": 0.018599206360287415,\n \"\ acc_norm\": 0.7486238532110092,\n \"acc_norm_stderr\": 0.018599206360287415\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4583333333333333,\n \"acc_stderr\": 0.03398110890294636,\n \"\ acc_norm\": 0.4583333333333333,\n \"acc_norm_stderr\": 0.03398110890294636\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7303921568627451,\n \"acc_stderr\": 0.031145570659486782,\n \"\ acc_norm\": 0.7303921568627451,\n \"acc_norm_stderr\": 0.031145570659486782\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7341772151898734,\n \"acc_stderr\": 0.02875679962965834,\n \ \ \"acc_norm\": 0.7341772151898734,\n \"acc_norm_stderr\": 0.02875679962965834\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6322869955156951,\n\ \ \"acc_stderr\": 0.03236198350928275,\n \"acc_norm\": 0.6322869955156951,\n\ \ \"acc_norm_stderr\": 0.03236198350928275\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5954198473282443,\n \"acc_stderr\": 0.043046937953806645,\n\ \ \"acc_norm\": 0.5954198473282443,\n \"acc_norm_stderr\": 0.043046937953806645\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302872,\n \"acc_norm\"\ : 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302872\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.6851851851851852,\n\ \ \"acc_stderr\": 0.04489931073591312,\n \"acc_norm\": 0.6851851851851852,\n\ \ \"acc_norm_stderr\": 0.04489931073591312\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6319018404907976,\n \"acc_stderr\": 0.03789213935838396,\n\ \ \"acc_norm\": 0.6319018404907976,\n \"acc_norm_stderr\": 0.03789213935838396\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7087378640776699,\n \"acc_stderr\": 0.04498676320572924,\n\ \ \"acc_norm\": 0.7087378640776699,\n \"acc_norm_stderr\": 0.04498676320572924\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.02441494730454368,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.02441494730454368\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \ \ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7522349936143039,\n\ \ \"acc_stderr\": 0.015438083080568973,\n \"acc_norm\": 0.7522349936143039,\n\ \ \"acc_norm_stderr\": 0.015438083080568973\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6560693641618497,\n \"acc_stderr\": 0.025574123786546665,\n\ \ \"acc_norm\": 0.6560693641618497,\n \"acc_norm_stderr\": 0.025574123786546665\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.31620111731843575,\n\ \ \"acc_stderr\": 0.015551673652172537,\n \"acc_norm\": 0.31620111731843575,\n\ \ \"acc_norm_stderr\": 0.015551673652172537\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6241830065359477,\n \"acc_stderr\": 0.027732834353363947,\n\ \ \"acc_norm\": 0.6241830065359477,\n \"acc_norm_stderr\": 0.027732834353363947\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6109324758842444,\n\ \ \"acc_stderr\": 0.027690337536485372,\n \"acc_norm\": 0.6109324758842444,\n\ \ \"acc_norm_stderr\": 0.027690337536485372\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6419753086419753,\n \"acc_stderr\": 0.0266756119260371,\n\ \ \"acc_norm\": 0.6419753086419753,\n \"acc_norm_stderr\": 0.0266756119260371\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4078014184397163,\n \"acc_stderr\": 0.029316011776343555,\n \ \ \"acc_norm\": 0.4078014184397163,\n \"acc_norm_stderr\": 0.029316011776343555\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4132985658409387,\n\ \ \"acc_stderr\": 0.012576779494860083,\n \"acc_norm\": 0.4132985658409387,\n\ \ \"acc_norm_stderr\": 0.012576779494860083\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5477941176470589,\n \"acc_stderr\": 0.03023375855159643,\n\ \ \"acc_norm\": 0.5477941176470589,\n \"acc_norm_stderr\": 0.03023375855159643\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5473856209150327,\n \"acc_stderr\": 0.020136790918492523,\n \ \ \"acc_norm\": 0.5473856209150327,\n \"acc_norm_stderr\": 0.020136790918492523\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.0469237132203465,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.0469237132203465\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.5877551020408164,\n \"acc_stderr\": 0.031512360446742695,\n\ \ \"acc_norm\": 0.5877551020408164,\n \"acc_norm_stderr\": 0.031512360446742695\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6965174129353234,\n\ \ \"acc_stderr\": 0.03251006816458619,\n \"acc_norm\": 0.6965174129353234,\n\ \ \"acc_norm_stderr\": 0.03251006816458619\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.42168674698795183,\n\ \ \"acc_stderr\": 0.03844453181770917,\n \"acc_norm\": 0.42168674698795183,\n\ \ \"acc_norm_stderr\": 0.03844453181770917\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7251461988304093,\n \"acc_stderr\": 0.03424042924691583,\n\ \ \"acc_norm\": 0.7251461988304093,\n \"acc_norm_stderr\": 0.03424042924691583\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.25703794369645044,\n\ \ \"mc1_stderr\": 0.015298077509485076,\n \"mc2\": 0.369230031760143,\n\ \ \"mc2_stderr\": 0.013637900924748413\n }\n}\n```" repo_url: https://huggingface.co/CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|arc:challenge\|25_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hellaswag\|10_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-04T21:15:30.560082.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-04T21:15:30.560082.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_04T21_15_30.560082 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-04T21:15:30.560082.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-04T21:15:30.560082.parquet' - config_name: results data_files: - split: 2023_09_04T21_15_30.560082 path: - results_2023-09-04T21:15:30.560082.parquet - split: latest path: - results_2023-09-04T21:15:30.560082.parquet --- # Dataset Card for Evaluation run of CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj ## Dataset Description - Homepage: - Repository: https://huggingface.co/CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj](https://huggingface.co/CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-Fintune_1_17w-gate_up_down_proj", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-04T21:15:30.560082](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-Fintune_1_17w-gate_up_down_proj/blob/main/results_2023-09-04T21%3A15%3A30.560082.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.5475267614652215, "acc_stderr": 0.034609984402304776, "acc_norm": 0.5517087027206374, "acc_norm_stderr": 0.03459190488664288, "mc1": 0.25703794369645044, "mc1_stderr": 0.015298077509485076, "mc2": 0.369230031760143, "mc2_stderr": 0.013637900924748413 }, "harness\|arc:challenge\|25": { "acc": 0.5213310580204779, "acc_stderr": 0.014598087973127106, "acc_norm": 0.5614334470989761, "acc_norm_stderr": 0.014500682618212865 }, "harness\|hellaswag\|10": { "acc": 0.6037641904003187, "acc_stderr": 0.0048811488668741845, "acc_norm": 0.8103963353913562, "acc_norm_stderr": 0.003911862797736198 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.45925925925925926, "acc_stderr": 0.04304979692464242, "acc_norm": 0.45925925925925926, "acc_norm_stderr": 0.04304979692464242 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5526315789473685, "acc_stderr": 0.0404633688397825, "acc_norm": 0.5526315789473685, "acc_norm_stderr": 0.0404633688397825 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5886792452830188, "acc_stderr": 0.030285009259009794, "acc_norm": 0.5886792452830188, "acc_norm_stderr": 0.030285009259009794 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6041666666666666, "acc_stderr": 0.04089465449325583, "acc_norm": 0.6041666666666666, "acc_norm_stderr": 0.04089465449325583 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5144508670520231, "acc_stderr": 0.03810871630454764, "acc_norm": 0.5144508670520231, "acc_norm_stderr": 0.03810871630454764 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.451063829787234, "acc_stderr": 0.032529096196131965, "acc_norm": 0.451063829787234, "acc_norm_stderr": 0.032529096196131965 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.3157894736842105, "acc_stderr": 0.04372748290278005, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.04372748290278005 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5172413793103449, "acc_stderr": 0.04164188720169375, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.04164188720169375 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3492063492063492, "acc_stderr": 0.024552292209342658, "acc_norm": 0.3492063492063492, "acc_norm_stderr": 0.024552292209342658 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.38095238095238093, "acc_stderr": 0.04343525428949097, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.04343525428949097 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6580645161290323, "acc_stderr": 0.026985289576552742, "acc_norm": 0.6580645161290323, "acc_norm_stderr": 0.026985289576552742 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4236453201970443, "acc_stderr": 0.03476725747649037, "acc_norm": 0.4236453201970443, "acc_norm_stderr": 0.03476725747649037 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6787878787878788, "acc_stderr": 0.036462049632538115, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.036462049632538115 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7070707070707071, "acc_stderr": 0.03242497958178816, "acc_norm": 0.7070707070707071, "acc_norm_stderr": 0.03242497958178816 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7772020725388601, "acc_stderr": 0.030031147977641538, "acc_norm": 0.7772020725388601, "acc_norm_stderr": 0.030031147977641538 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.4794871794871795, "acc_stderr": 0.02532966316348994, "acc_norm": 0.4794871794871795, "acc_norm_stderr": 0.02532966316348994 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114986, "acc_norm": 0.3037037037037037, "acc_norm_stderr": 0.028037929969114986 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5378151260504201, "acc_stderr": 0.032385469487589795, "acc_norm": 0.5378151260504201, "acc_norm_stderr": 0.032385469487589795 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7486238532110092, "acc_stderr": 0.018599206360287415, "acc_norm": 0.7486238532110092, "acc_norm_stderr": 0.018599206360287415 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4583333333333333, "acc_stderr": 0.03398110890294636, "acc_norm": 0.4583333333333333, "acc_norm_stderr": 0.03398110890294636 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7303921568627451, "acc_stderr": 0.031145570659486782, "acc_norm": 0.7303921568627451, "acc_norm_stderr": 0.031145570659486782 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7341772151898734, "acc_stderr": 0.02875679962965834, "acc_norm": 0.7341772151898734, "acc_norm_stderr": 0.02875679962965834 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6322869955156951, "acc_stderr": 0.03236198350928275, "acc_norm": 0.6322869955156951, "acc_norm_stderr": 0.03236198350928275 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5954198473282443, "acc_stderr": 0.043046937953806645, "acc_norm": 0.5954198473282443, "acc_norm_stderr": 0.043046937953806645 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.743801652892562, "acc_stderr": 0.03984979653302872, "acc_norm": 0.743801652892562, "acc_norm_stderr": 0.03984979653302872 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.6851851851851852, "acc_stderr": 0.04489931073591312, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.04489931073591312 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6319018404907976, "acc_stderr": 0.03789213935838396, "acc_norm": 0.6319018404907976, "acc_norm_stderr": 0.03789213935838396 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7087378640776699, "acc_stderr": 0.04498676320572924, "acc_norm": 0.7087378640776699, "acc_norm_stderr": 0.04498676320572924 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.02441494730454368, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.02441494730454368 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7522349936143039, "acc_stderr": 0.015438083080568973, "acc_norm": 0.7522349936143039, "acc_norm_stderr": 0.015438083080568973 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6560693641618497, "acc_stderr": 0.025574123786546665, "acc_norm": 0.6560693641618497, "acc_norm_stderr": 0.025574123786546665 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.31620111731843575, "acc_stderr": 0.015551673652172537, "acc_norm": 0.31620111731843575, "acc_norm_stderr": 0.015551673652172537 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6241830065359477, "acc_stderr": 0.027732834353363947, "acc_norm": 0.6241830065359477, "acc_norm_stderr": 0.027732834353363947 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6109324758842444, "acc_stderr": 0.027690337536485372, "acc_norm": 0.6109324758842444, "acc_norm_stderr": 0.027690337536485372 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6419753086419753, "acc_stderr": 0.0266756119260371, "acc_norm": 0.6419753086419753, "acc_norm_stderr": 0.0266756119260371 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4078014184397163, "acc_stderr": 0.029316011776343555, "acc_norm": 0.4078014184397163, "acc_norm_stderr": 0.029316011776343555 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4132985658409387, "acc_stderr": 0.012576779494860083, "acc_norm": 0.4132985658409387, "acc_norm_stderr": 0.012576779494860083 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5477941176470589, "acc_stderr": 0.03023375855159643, "acc_norm": 0.5477941176470589, "acc_norm_stderr": 0.03023375855159643 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5473856209150327, "acc_stderr": 0.020136790918492523, "acc_norm": 0.5473856209150327, "acc_norm_stderr": 0.020136790918492523 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6, "acc_stderr": 0.0469237132203465, "acc_norm": 0.6, "acc_norm_stderr": 0.0469237132203465 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.5877551020408164, "acc_stderr": 0.031512360446742695, "acc_norm": 0.5877551020408164, "acc_norm_stderr": 0.031512360446742695 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.6965174129353234, "acc_stderr": 0.03251006816458619, "acc_norm": 0.6965174129353234, "acc_norm_stderr": 0.03251006816458619 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.42168674698795183, "acc_stderr": 0.03844453181770917, "acc_norm": 0.42168674698795183, "acc_norm_stderr": 0.03844453181770917 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7251461988304093, "acc_stderr": 0.03424042924691583, "acc_norm": 0.7251461988304093, "acc_norm_stderr": 0.03424042924691583 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.25703794369645044, "mc1_stderr": 0.015298077509485076, "mc2": 0.369230031760143, "mc2_stderr": 0.013637900924748413 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7007175087928772, -0.879589855670929, 0.2914242744445801, 0.2167137712240219, -0.1813991665840149, -0.03491554036736488, 0.00900977198034525, -0.25402992963790894, 0.5820631980895996, -0.036402419209480286, -0.5051484107971191, -0.6924445629119873, -0.4623689353466034, 0.2648756802082062, -0.04739859700202942, 0.8577244281768799, -0.2121080905199051, -0.14247816801071167, 0.0945056676864624, -0.0008301684283651412, -0.27111002802848816, -0.33315029740333557, -0.47966286540031433, 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allenai/scifact_entailment	allenai	2023-09-27T05:00:41Z	253	0	[ "task_categories:text-classification", "task_ids:fact-checking", "annotations_creators:expert-generated", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "license:cc-by-nc-2.0", "region:us" ]	[ "text-classification" ]	2023-09-26T22:04:02Z	--- annotations_creators: - expert-generated language: - en language_creators: - found license: - cc-by-nc-2.0 multilinguality: - monolingual pretty_name: SciFact size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - fact-checking paperswithcode_id: scifact dataset_info: features: - name: claim_id dtype: int32 - name: claim dtype: string - name: abstract_id dtype: int32 - name: title dtype: string - name: abstract sequence: string - name: verdict dtype: string - name: evidence sequence: int32 splits: - name: train num_bytes: 1649655 num_examples: 919 - name: validation num_bytes: 605262 num_examples: 340 download_size: 3115079 dataset_size: 2254917 --- # Dataset Card for "scifact_entailment" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) ## Dataset Description - Homepage: [https://scifact.apps.allenai.org/](https://scifact.apps.allenai.org/) - Repository: <https://github.com/allenai/scifact> - Paper: [Fact or Fiction: Verifying Scientific Claims](https://aclanthology.org/2020.emnlp-main.609/) - Point of Contact: [David Wadden](mailto:[email protected]) ### Dataset Summary SciFact, a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts, and annotated with labels and rationales. For more information on the dataset, see [allenai/scifact](https://huggingface.co/datasets/allenai/scifact). This has the same data, but reformatted as an entailment task. A single instance includes a claim paired with a paper title and abstract, together with an entailment label and a list of evidence sentences (if any). ## Dataset Structure ### Data fields - `claim_id`: An `int32` claim identifier. - `claim`: A `string`. - `abstract_id`: An `int32` abstract identifier. - `title`: A `string`. - `abstract`: A list of `strings`, one for each sentence in the abstract. - `verdict`: The fact-checking verdict, a `string`. - `evidence`: A list of sentences from the abstract which provide evidence for the verdict. ### Data Splits \| \|train\|validation\| \|------\|----:\|---------:\| \|claims\| 919 \| 340\|	[ -0.21247048676013947, -0.589434027671814, 0.3517349362373352, 0.26010775566101074, -0.15689238905906677, -0.1355876326560974, 0.1676430106163025, -0.3530219793319702, 0.6331222057342529, 0.30261191725730896, -0.3807261884212494, -0.564893364906311, -0.6299939751625061, 0.395280659198761, -0.3777942359447479, 1.2548280954360962, -0.3498886823654175, 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Team-PIXEL/bigrams_bookcorpus_529	Team-PIXEL	2023-10-02T07:54:20Z	253	0	[ "license:apache-2.0", "region:us" ]	null	2023-10-02T07:22:07Z	--- license: apache-2.0 dataset_info: features: - name: title dtype: string - name: data dtype: string splits: - name: train num_bytes: 7031990695 num_examples: 9814746 download_size: 4016929000 dataset_size: 7031990695 configs: - config_name: default data_files: - split: train path: data/train-* ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 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atmallen/qm_mixture_1.0e	atmallen	2023-11-16T18:17:48Z	253	0	[ "region:us" ]	null	2023-11-16T03:32:56Z	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: alice_label dtype: bool - name: bob_label dtype: bool - name: difficulty dtype: int64 - name: statement dtype: string - name: choices sequence: string - name: character dtype: string - name: label dtype: class_label: names: '0': 'False' '1': 'True' splits: - name: train num_bytes: 44733311 num_examples: 400000 - name: validation num_bytes: 4508863 num_examples: 40000 - name: test num_bytes: 4496765 num_examples: 40000 download_size: 0 dataset_size: 53738939 --- # Dataset Card for "qm_mixture_1.0e" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.7176345586776733, -0.11748471111059189, 0.2298213541507721, 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DebateLabKIT/aaac	DebateLabKIT	2022-10-24T16:25:56Z	252	3	[ "task_categories:summarization", "task_categories:text-retrieval", "task_categories:text-generation", "task_ids:parsing", "task_ids:text-simplification", "annotations_creators:machine-generated", "annotations_creators:expert-generated", "language_creators:machine-generated", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:cc-by-sa-4.0", "argument-mining", "conditional-text-generation", "structure-prediction", "arxiv:2110.01509", "region:us" ]	[ "summarization", "text-retrieval", "text-generation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - machine-generated - expert-generated language_creators: - machine-generated language: - en license: - cc-by-sa-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - summarization - text-retrieval - text-generation task_ids: - parsing - text-simplification paperswithcode_id: aaac pretty_name: Artificial Argument Analysis Corpus language_bcp47: - en-US tags: - argument-mining - conditional-text-generation - structure-prediction --- # Dataset Card for Artificial Argument Analysis Corpus (AAAC) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Construction of the Synthetic Data](#construction-of-the-synthetic-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://debatelab.github.io/journal/deepa2.html - Repository: None - Paper: G. Betz, K. Richardson. DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models. https://arxiv.org/abs/2110.01509 - Leaderboard: None ### Dataset Summary DeepA2 is a modular framework for deep argument analysis. DeepA2 datasets contain comprehensive logical reconstructions of informally presented arguments in short argumentative texts. This document describes two synthetic DeepA2 datasets for artificial argument analysis: AAAC01 and AAAC02. ```sh # clone git lfs clone https://huggingface.co/datasets/debatelab/aaac ``` ```python import pandas as pd from datasets import Dataset # loading train split as pandas df df = pd.read_json("aaac/aaac01_train.jsonl", lines=True, orient="records") # creating dataset from pandas df Dataset.from_pandas(df) ``` ### Supported Tasks and Leaderboards The multi-dimensional datasets can be used to define various text-2-text tasks (see also [Betz and Richardson 2021](https://arxiv.org/abs/2110.01509)), for example: * Premise extraction, * Conclusion extraction, * Logical formalization, * Logical reconstrcution. ### Languages English. ## Dataset Structure ### Data Instances The following histograms (number of dataset records with given property) describe and compare the two datasets AAAC01 (train split, N=16000) and AAAC02 (dev split, N=4000). \|AAAC01 / train split\|AAAC02 / dev split\| \|-\|-\| \|![domains](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_domains_aaac01.png) \|![domains](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_domains_aaac02.png) \| \|![schemes](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_schemes_aaac01.png) \|![schemes](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_schemes_aaac02.png) \| \|![var](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_sch-vars_aaac01.png) \|![domains](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_sch-vars_aaac02.png) \| \|![steps](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_steps_aaac01.png) \|![steps](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_steps_aaac02.png) \| \|![prem](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_prem_aaac01.png) \|![prem](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_prem_aaac02.png) \| \|![impl prem](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_impl-prem_aaac01.png) \|![impl prem](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_impl-prem_aaac02.png) \| \|![impl fc](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_impl-fc_aaac01.png) \|![impl fc](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_impl-fc_aaac02.png) \| \|![dist](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_distr_aaac01.png) \|![dist](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/st_distr_aaac02.png) \| ### Data Fields The following multi-dimensional example record (2-step argument with one implicit premise) illustrates the structure of the AAAC datasets. #### argument_source ``` If someone was discovered in 'Moonlight', then they won't play the lead in 'Booksmart', because being a candidate for the lead in 'Booksmart' is sufficient for not being an Oscar-Nominee for a role in 'Eighth Grade'. Yet every BAFTA-Nominee for a role in 'The Shape of Water' is a fan-favourite since 'Moonlight' or a supporting actor in 'Black Panther'. And if someone is a supporting actor in 'Black Panther', then they could never become the main actor in 'Booksmart'. Consequently, if someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are not a candidate for the lead in 'Booksmart'. ``` #### reason_statements ```json [ {"text":"being a candidate for the lead in 'Booksmart' is sufficient for not being an Oscar-Nominee for a role in 'Eighth Grade'","starts_at":96, "ref_reco":2}, {"text":"every BAFTA-Nominee for a role in 'The Shape of Water' is a fan-favourite since 'Moonlight' or a supporting actor in 'Black Panther'", "starts_at":221,"ref_reco":4}, {"text":"if someone is a supporting actor in 'Black Panther', then they could never become the main actor in 'Booksmart'","starts_at":359, "ref_reco":5} ] ``` #### conclusion_statements ```json [ {"text":"If someone was discovered in 'Moonlight', then they won't play the lead in 'Booksmart'","starts_at":0,"ref_reco":3}, {"text":"if someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are not a candidate for the lead in 'Booksmart'","starts_at":486, "ref_reco":6} ] ``` #### distractors `[]` #### argdown_reconstruction ``` (1) If someone is a fan-favourite since 'Moonlight', then they are an Oscar-Nominee for a role in 'Eighth Grade'. (2) If someone is a candidate for the lead in 'Booksmart', then they are not an Oscar-Nominee for a role in 'Eighth Grade'. -- with hypothetical syllogism {variant: ["negation variant", "transposition"], uses: [1,2]} -- (3) If someone is beloved for their role in 'Moonlight', then they don't audition in 'Booksmart'. (4) If someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are a fan-favourite since 'Moonlight' or a supporting actor in 'Black Panther'. (5) If someone is a supporting actor in 'Black Panther', then they don't audition in 'Booksmart'. -- with generalized dilemma {variant: ["negation variant"], uses: [3,4,5]} -- (6) If someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are not a candidate for the lead in 'Booksmart'. ``` #### premises ```json [ {"ref_reco":1,"text":"If someone is a fan-favourite since 'Moonlight', then they are an Oscar-Nominee for a role in 'Eighth Grade'.","explicit":false}, {"ref_reco":2,"text":"If someone is a candidate for the lead in 'Booksmart', then they are not an Oscar-Nominee for a role in 'Eighth Grade'.","explicit":true}, {"ref_reco":4,"text":"If someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are a fan-favourite since 'Moonlight' or a supporting actor in 'Black Panther'.","explicit":true}, {"ref_reco":5,"text":"If someone is a supporting actor in 'Black Panther', then they don't audition in 'Booksmart'.","explicit":true} ] ``` #### premises_formalized ```json [ {"form":"(x): ${F2}x -> ${F5}x","ref_reco":1}, {"form":"(x): ${F4}x -> ¬${F5}x","ref_reco":2}, {"form":"(x): ${F1}x -> (${F2}x v ${F3}x)","ref_reco":4}, {"form":"(x): ${F3}x -> ¬${F4}x","ref_reco":5} ] ``` #### conclusion ```json [{"ref_reco":6,"text":"If someone is a BAFTA-Nominee for a role in 'The Shape of Water', then they are not a candidate for the lead in 'Booksmart'.", "explicit":true}] ``` #### conclusion_formalized ```json [{"form":"(x): ${F1}x -> ¬${F4}x","ref_reco":6}] ``` #### intermediary_conclusions ```json [{"ref_reco":3,"text":"If someone is beloved for their role in 'Moonlight', then they don't audition in 'Booksmart'.","explicit":true}] ``` #### intermediary_conclusions_formalized ```json [{"form":"(x): ${F2}x -> ¬${F4}x","ref_reco":3}] ``` #### plcd_subs ```json { "F1":"BAFTA-Nominee for a role in 'The Shape of Water'", "F2":"fan-favourite since 'Moonlight'", "F3":"supporting actor in 'Black Panther'", "F4":"candidate for the lead in 'Booksmart'", "F5":"Oscar-Nominee for a role in 'Eighth Grade'" } ``` ### Data Splits Number of instances in the various splits: \| Split \| AAAC01 \| AAAC02 \| \| :--- \| :---: \| :---: \| \| TRAIN \| 16,000 \| 16,000 \| \| DEV \| 4,000 \| 4,000 \| \| TEST \| 4,000 \| 4,000 \| To correctly load a specific split, define `data_files` as follows: ```python >>> data_files = {"train": "aaac01_train.jsonl", "eval": "aaac01_dev.jsonl", "test": "aaac01_test.jsonl"} >>> dataset = load_dataset("debatelab/aaac", data_files=data_files) ``` ## Dataset Creation ### Curation Rationale Argument analysis refers to the interpretation and logical reconstruction of argumentative texts. Its goal is to make an argument transparent, so as to understand, appreciate and (possibly) criticize it. Argument analysis is a key critical thinking skill. Here's a first example of an informally presented argument, Descartes' Cogito: > I have convinced myself that there is absolutely nothing in the world, no sky, no earth, no minds, no bodies. Does it now follow that I too do not exist? No: if I convinced myself of something then I certainly existed. But there is a deceiver of supreme power and cunning who is deliberately and constantly deceiving me. In that case I too undoubtedly exist, if he is deceiving me; and let him deceive me as much as he can, he will never bring it about that I am nothing so long as I think that I am something. So after considering everything very thoroughly, I must finally conclude that this proposition, I am, I exist, is necessarily true whenever it is put forward by me or conceived in my mind. (AT 7:25, CSM 2:16f) And here's a second example, taken from the Debater's Handbook, Pro Censorship: > Freedom of speech is never an absolute right but an aspiration. It ceases to be a right when it causes harm to others -- we all recognise the value of, for example, legislating against incitement to racial hatred. Therefore it is not the case that censorship is wrong in principle. Given such texts, argument analysis aims at answering the following questions: 1. Does the text present an argument? 2. If so, how many? 3. What is the argument supposed to show (conclusion)? 4. What exactly are the premises of the argument? * Which statements, explicit in the text, are not relevant for the argument? * Which premises are required, but not explicitly stated? 5. Is the argument deductively valid, inductively strong, or simply fallacious? To answer these questions, argument analysts interpret the text by (re-)constructing its argument in a standardized way (typically as a premise-conclusion list) and by making use of logical streamlining and formalization. A reconstruction of Pro Censorship which answers the above questions is: ```argdown (1) Freedom of speech is never an absolute right but an aspiration. (2) Censorship is wrong in principle only if freedom of speech is an absolute right. --with modus tollens-- (3) It is not the case that censorship is wrong in principle ``` There are typically multiple, more or less different interpretations and logical reconstructions of an argumentative text. For instance, there exists an [extensive debate](https://plato.stanford.edu/entries/descartes-epistemology/) about how to interpret Descartes' Cogito, and scholars have advanced rival interpretation of the argument. An alternative reconstruction of the much simpler Pro Censorship might read: ```argdown (1) Legislating against incitement to racial hatred is valuable. (2) Legislating against incitement to racial hatred is an instance of censorship. (3) If some instance of censorship is valuable, censorship is not wrong in principle. ----- (4) Censorship is not wrong in principle. (5) Censorship is wrong in principle only if and only if freedom of speech is an absolute right. ----- (4) Freedom of speech is not an absolute right. (5) Freedom of speech is an absolute right or an aspiration. --with disjunctive syllogism-- (6) Freedom of speech is an aspiration. ``` What are the main reasons for this kind of underdetermination? * Incompleteness. Many relevant parts of an argument (statements, their function in the argument, inference rules, argumentative goals) are not stated in its informal presentation. The argument analyst must infer the missing parts. * Additional material. Over and above what is strictly part of the argument, informal presentations contain typically further material: relevant premises are repeated in slightly different ways, further examples are added to illustrate a point, statements are contrasted with views by opponents, etc. etc. It's argument analyst to choice which of the presented material is really part of the argument. * Errors. Authors may err in the presentation of an argument, confounding, e.g., necessary and sufficient conditions in stating a premise. Following the principle of charity, benevolent argument analysts correct such errors and have to choose on of the different ways for how to do so. * Linguistic indeterminacy. One and the same statement can be interpreted -- regarding its logical form -- in different ways. * Equivalence. There are different natural language expressions for one and the same proposition. AAAC datasets provide logical reconstructions of informal argumentative texts: Each record contains a source text to-be-reconstructed and further fields which describe an internally consistent interpretation of the text, notwithstanding the fact that there might be alternative interpretations of this very text. ### Construction of the Synthetic Data Argument analysis starts with a text and reconstructs its argument (cf. [Motivation and Background](#curation-rationale)). In constructing our synthetic data, we inverse this direction: We start by sampling a complete argument, construct an informal presentation, and provide further info that describes both logical reconstruction and informal presentation. More specifically, the construction of the data involves the following steps: 1. [Generation of valid symbolic inference schemes](#step-1-generation-of-symbolic-inference-schemes) 2. [Assembling complex ("multi-hop") argument schemes from symbolic inference schemes](#step-2-assembling-complex-multi-hop-argument-schemes-from-symbolic-inference-schemes) 3. [Creation of (precise and informal) natural-language argument](#step-3-creation-of-precise-and-informal-natural-language-argument-schemes) 4. [Substitution of placeholders with domain-specific predicates and names](#step-4-substitution-of-placeholders-with-domain-specific-predicates-and-names) 5. [Creation of the argdown-snippet](#step-5-creation-of-the-argdown-snippet) 7. [Paraphrasing](#step-6-paraphrasing) 6. [Construction of a storyline for the argument source text](#step-7-construction-of-a-storyline-for-the-argument-source-text) 8. [Assembling the argument source text](#step-8-assembling-the-argument-source-text) 9. [Linking the precise reconstruction and the informal argumentative text](#step-9-linking-informal-presentation-and-formal-reconstruction) #### Step 1: Generation of symbolic inference schemes We construct the set of available inference schemes by systematically transforming the following 12 base schemes (6 from propositional and another 6 from predicate logic): * modus ponens: `['Fa -> Gb', 'Fa', 'Gb']` * chain rule: `['Fa -> Gb', 'Gb -> Hc', 'Fa -> Hc']` * adjunction: `['Fa', 'Gb', 'Fa & Gb']` * case analysis: `['Fa v Gb', 'Fa -> Hc', 'Gb -> Hc', 'Hc']` * disjunctive syllogism: `['Fa v Gb', '¬Fa', 'Gb']` * biconditional elimination: `['Fa <-> Gb', 'Fa -> Gb']` * instantiation: `['(x): Fx -> Gx', 'Fa -> Ga']` * hypothetical syllogism: `['(x): Fx -> Gx', '(x): Gx -> Hx', '(x): Fx -> Hx']` * generalized biconditional elimination: `['(x): Fx <-> Gx', '(x): Fx -> Gx']` * generalized adjunction: `['(x): Fx -> Gx', '(x): Fx -> Hx', '(x): Fx -> (Gx & Hx)']` * generalized dilemma: `['(x): Fx -> (Gx v Hx)', '(x): Gx -> Ix', '(x): Hx -> Ix', '(x): Fx -> Ix']` * generalized disjunctive syllogism: `['(x): Fx -> (Gx v Hx)', '(x): Fx -> ¬Gx', '(x): Fx -> Hx']` (Regarding the propositional schemes, we allow for `a`=`b`=`c`.) Further symbolic inference schemes are generated by applying the following transformations to each of these base schemes: * negation: replace all occurrences of an atomic formula by its negation (for any number of such atomic sentences) * transposition: transpose exactly one (generalized) conditional * dna: simplify by applying duplex negatio affirmat * complex predicates: replace all occurrences of a given atomic formula by a complex formula consisting in the conjunction or disjunction of two atomic formulas * de morgan: apply de Morgan's rule once These transformations are applied to the base schemes in the following order: > {base_schemes} > negation_variants > transposition_variants > dna > {transposition_variants} > complex_predicates > negation_variants > dna > {complex_predicates} > de_morgan > dna > {de_morgan} All transformations, except dna, are monotonic, i.e. simply add further schemes to the ones generated in the previous step. Results of bold steps are added to the list of valid inference schemes. Each inference scheme is stored with information about which transformations were used to create it. All in all, this gives us 5542 schemes. #### Step 2: Assembling complex ("multi-hop") argument schemes from symbolic inference schemes The complex argument scheme, which consists in multiple inferences, is assembled recursively by adding inferences that support premises of previously added inferences, as described by the following pseudocode: ``` argument = [] intermediary_conclusion = [] inference = randomly choose from list of all schemes add inference to argument for i in range(number_of_sub_arguments - 1): target = randomly choose a premise which is not an intermediary_conclusion inference = randomly choose a scheme whose conclusion is identical with target add inference to argument add target to intermediary_conclusion return argument ``` The complex arguments we create are hence trees, with a root scheme. Let's walk through this algorithm by means of an illustrative example and construct a symbolic argument scheme with two sub-arguments. First, we randomly choose some inference scheme (random sampling is controlled by weights that compensate for the fact that the list of schemes mainly contains, for combinatorial reasons, complex inferences), say: ```json { "id": "mp", "base_scheme_group": "modus ponens", "scheme_variant": ["complex_variant"], "scheme": [ ["${A}${a} -> (${B}${a} & ${C}${a})", {"A": "${F}", "B": "${G}", "C": "${H}", "a": "${a}"}], ["${A}${a}", {"A": "${F}", "a": "${a}"}], ["${A}${a} & ${B}${a}", {"A": "${G}", "B": "${H}", "a": "${a}"}] ], "predicate-placeholders": ["F", "G", "H"], "entity-placeholders": ["a"] } ``` Now, the target premise (= intermediary conclusion) of the next subargument is chosen, say: premise 1 of the already added root scheme. We filter the list of schemes for schemes whose conclusion structurally matches the target, i.e. has the form `${A}${a} -> (${B}${a} v ${C}${a})`. From this filtered list of suitable schemes, we randomly choose, for example ```json { "id": "bicelim", "base_scheme_group": "biconditional elimination", "scheme_variant": [complex_variant], "scheme": [ ["${A}${a} <-> (${B}${a} & ${C}${a})", {"A": "${F}", "B": "${G}", "C": "${H}", "a": "${a}"}], ["${A}${a} -> (${B}${a} & ${C}${a})", {"A": "${F}", "B": "${G}", "C": "${H}", "a": "${a}"}] ], "predicate-placeholders": ["F", "G", "H"], "entity-placeholders": [] } ``` So, we have generated this 2-step symbolic argument scheme with two premises, one intermediary and one final conclusion: ``` (1) Fa <-> Ga & Ha -- with biconditional elimination (complex variant) from 1 -- (2) Fa -> Ga & Ha (3) Fa -- with modus ponens (complex variant) from 2,3 -- (4) Ga & Ha ``` General properties of the argument are now determined and can be stored in the dataset (its `domain` is randomly chosen): ```json "steps":2, // number of inference steps "n_premises":2, "base_scheme_groups":[ "biconditional elimination", "modus ponens" ], "scheme_variants":[ "complex variant" ], "domain_id":"consumers_personalcare", "domain_type":"persons" ``` #### Step 3: Creation of (precise and informal) natural-language argument schemes In step 3, the symbolic and formal complex argument scheme is transformed into a natural language argument scheme by replacing symbolic formulas (e.g., `${A}${a} v ${B}${a}`) with suitable natural language sentence schemes (such as, `${a} is a ${A}, and ${a} is a ${B}` or `${a} is a ${A} and a ${B}`). Natural language sentence schemes which translate symbolic formulas are classified according to whether they are precise, informal, or imprecise. For each symbolic formula, there are many (partly automatically, partly manually generated) natural-language sentence scheme which render the formula in more or less precise way. Each of these natural-language "translations" of a symbolic formula is labeled according to whether it presents the logical form in a "precise", "informal", or "imprecise" way. e.g. \|type\|form\| \|-\|-\| \|symbolic\|`(x): ${A}x -> ${B}x`\| \|precise\|`If someone is a ${A}, then they are a ${B}.`\| \|informal\|`Every ${A} is a ${B}.`\| \|imprecise\|`${A} might be a ${B}.`\| The labels "precise", "informal", "imprecise" are used to control the generation of two natural-language versions of the argument scheme, a precise one (for creating the argdown snippet) and an informal one (for creating the source text). Moreover, the natural-language "translations" are also chosen in view of the domain (see below) of the to-be-generated argument, specifically in view of whether it is quantified over persons ("everyone", "nobody") or objects ("something, nothing"). So, as a precise rendition of our symbolic argument scheme, we may obtain: ``` (1) If, and only if, a is a F, then a is G and a is a H. -- with biconditional elimination (complex variant) from 1 -- (2) If a is a F, then a is a G and a is a H. (3) a is a F. -- with modus ponens (complex variant) from 3,2 -- (4) a is G and a is a H. ``` Likewise, an informal rendition may be: ``` (1) a is a F if a is both a G and a H -- and vice versa. -- with biconditional elimination (complex variant) from 1 -- (2) a is a G and a H, provided a is a F. (3) a is a F. -- with modus ponens (complex variant) from 3,2 -- (4) a is both a G and a H. ``` #### Step 4: Substitution of placeholders with domain-specific predicates and names Every argument falls within a domain. A domain provides * a list of `subject names` (e.g., Peter, Sarah) * a list of `object names` (e.g., New York, Lille) * a list of `binary predicates` (e.g., [subject is an] admirer of [object]) These domains are manually created. Replacements for the placeholders are sampled from the corresponding domain. Substitutes for entity placeholders (`a`, `b` etc.) are simply chosen from the list of `subject names`. Substitutes for predicate placeholders (`F`, `G` etc.) are constructed by combining `binary predicates` with `object names`, which yields unary predicates of the form "___ stands in some relation to some object". This combinatorial construction of unary predicates drastically increases the number of replacements available and hence the variety of generated arguments. Assuming that we sample our argument from the domain `consumers personal care`, we may choose and construct the following substitutes for placeholders in our argument scheme: * `F`: regular consumer of Kiss My Face soap * `G`: regular consumer of Nag Champa soap * `H`: occasional purchaser of Shield soap * `a`: Orlando #### Step 5: Creation of the argdown-snippet From the precise rendition of the natural language argument scheme ([step 3](#step-3-creation-of-precise-and-informal-natural-language-argument-schemes)) and the replacements for its placeholders ([step 4](#step-4-substitution-of-placeholders-with-domain-specific-predicates-and-names)), we construct the `argdown-snippet` by simple substitution and formatting the complex argument in accordance with [argdown syntax](https://argdown.org). This yields, for our example from above: ```argdown (1) If, and only if, Orlando is a regular consumer of Kiss My Face soap, then Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap. -- with biconditional elimination (complex variant) from 1 -- (2) If Orlando is a regular consumer of Kiss My Face soap, then Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap. (3) Orlando is a regular consumer of Kiss My Face soap. -- with modus ponens (complex variant) from 3,2 -- (4) Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap. ``` That's the `argdown_snippet`. By construction of such a synthetic argument (from formal schemes, see [step 2](#step-2-assembling-complex-multi-hop-argument-schemes-from-symbolic-inference-schemes)), we already know its conclusions and their formalization (the value of the field `explicit` will be determined later). ```json "conclusion":[ { "ref_reco":4, "text":"Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap.", "explicit": TBD } ], "conclusion_formalized":[ { "ref_reco":4, "form":"(${F2}${a1} & ${F3}${a1})" } ], "intermediary_conclusions":[ { "ref_reco":2, "text":"If Orlando is a regular consumer of Kiss My Face soap, then Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap.", "explicit": TBD } ] "intermediary_conclusions_formalized":[ { "ref_reco":2, "text":"${F1}${a1} -> (${F2}${a1} & ${F3}${a1})" } ], ``` ... and the corresponding keys (see [step 4](#step-4-substitution-of-placeholders-with-domain-specific-predicates-and-names))): ```json "plcd_subs":{ "a1":"Orlando", "F1":"regular consumer of Kiss My Face soap", "F2":"regular consumer of Nag Champa soap", "F3":"occasional purchaser of Shield soap" } ``` #### Step 6: Paraphrasing From the informal rendition of the natural language argument scheme ([step 3](#step-3-creation-of-precise-and-informal-natural-language-argument-schemes)) and the replacements for its placeholders ([step 4](#step-4-substitution-of-placeholders-with-domain-specific-predicates-and-names)), we construct an informal argument (argument tree) by substitution. The statements (premises, conclusions) of the informal argument are individually paraphrased in two steps 1. rule-based and in a domain-specific way, 2. automatically by means of a specifically fine-tuned T5 model. Each domain (see [step 4](#step-4-substitution-of-placeholders-with-domain-specific-predicates-and-names)) provides rules for substituting noun constructs ("is a supporter of X", "is a product made of X") with verb constructs ("supports x", "contains X"). These rules are applied whenever possible. Next, each sentence is -- with a probability specified by parameter `lm_paraphrasing` -- replaced with an automatically generated paraphrase, using a [T5 model fine-tuned on the Google PAWS dataset](https://huggingface.co/Vamsi/T5_Paraphrase_Paws) and filtering for paraphrases with acceptable _cola_ and sufficiently high _STSB_ value (both as predicted by T5). \| \|AAAC01\|AAAC02\| \|-\|-\|-\| \|`lm_paraphrasing`\|0.2\|0.\| #### Step 7: Construction of a storyline for the argument source text The storyline determines in which order the premises, intermediary conclusions and final conclusions are to be presented in the text paragraph to-be-constructed (`argument-source`). The storyline is constructed from the paraphrased informal complex argument (see [step 6](#step-6-paraphrasing))). Before determining the order of presentation (storyline), the informal argument tree is pre-processed to account for: * implicit premises, * implicit intermediary conclusions, and * implicit final conclusion, which is documented in the dataset record as ```json "presentation_parameters":{ "resolve_steps":[1], "implicit_conclusion":false, "implicit_premise":true, "...":"..." } ``` In order to make an intermediary conclusion C implicit, the inference to C is "resolved" by re-assigning all premisses from which C is directly inferred to the inference to the (final or intermediary) conclusion which C supports. Original tree: ``` P1 ... Pn ————————— C Q1 ... Qn ————————————— C' ``` Tree with resolved inference and implicit intermediary conclusion: ``` P1 ... Pn Q1 ... Qn ——————————————————— C' ``` The original argument tree in our example reads: ``` (1) ——— (2) (3) ——————— (4) ``` This might be pre-processed (by resolving the first inference step and dropping the first premise) to: ``` (3) ——— (4) ``` Given such a pre-processed argument tree, a storyline, which determines the order of presentation, can be constructed by specifying the direction of presentation and a starting point. The direction is either * forward (premise AND ... AND premise THEREFORE conclusion) * backward (conclusion SINCE premise AND ... AND premise) Any conclusion in the pre-processed argument tree may serve as starting point. The storyline is now constructed recursively, as illustrated in Figure~1. Integer labels of the nodes represent the order of presentation, i.e. the storyline. (Note that the starting point is not necessarily the statement which is presented first according to the storyline.) ![Storyline Construction](https://huggingface.co/datasets/debatelab/aaac/resolve/main/img/storylines1-4.png) So as to introduce redundancy, the storyline may be post-processed by repeating a premiss that has been stated previously. The likelihood that a single premise is repeated is controlled by the presentation parameters: ```json "presentation_parameters":{ "redundancy_frequency":0.1, } ``` Moreover, distractors, i.e. arbitrary statements sampled from the argument's very domain, may be inserted in the storyline. #### Step 8: Assembling the argument source text The `argument-source` is constructed by concatenating the statements of the informal argument ([step 6](#step-6-paraphrasing)) according to the order of the storyline ([step 7](#step-7-construction-of-a-storyline-for-the-argument-source-text)). In principle, each statement is prepended by a conjunction. There are four types of conjunction: * THEREFORE: left-to-right inference * SINCE: right-to-left inference * AND: joins premises with similar inferential role * MOREOVER: catch all conjunction Each statement is assigned a specific conjunction type by the storyline. For every conjunction type, we provide multiple natural-language terms which may figure as conjunctions when concatenating the statements, e.g. "So, necessarily,", "So", "Thus,", "It follows that", "Therefore,", "Consequently,", "Hence,", "In consequence,", "All this entails that", "From this follows that", "We may conclude that" for THEREFORE. The parameter ```json "presentation_parameters":{ "drop_conj_frequency":0.1, "...":"..." } ``` determines the probability that a conjunction is omitted and a statement is concatenated without prepending a conjunction. With the parameters given above we obtain the following `argument_source` for our example: > Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap, since Orlando is a regular consumer of Kiss My Face soap. #### Step 9: Linking informal presentation and formal reconstruction We can identify all statements _in the informal presentation_ (`argument_source`), categorize them according to their argumentative function GIVEN the logical reconstruction and link them to the corresponding statements in the `argdown_snippet`. We distinguish `reason_statement` (AKA REASONS, correspond to premises in the reconstruction) and `conclusion_statement` (AKA CONJECTURES, correspond to conclusion and intermediary conclusion in the reconstruction): ```json "reason_statements":[ // aka reasons { "text":"Orlando is a regular consumer of Kiss My Face soap", "starts_at":109, "ref_reco":3 } ], "conclusion_statements":[ // aka conjectures { "text":"Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap", "starts_at":0, "ref_reco":4 } ] ``` Moreover, we are now able to classify all premises in the formal reconstruction (`argdown_snippet`) according to whether they are implicit or explicit given the informal presentation: ```json "premises":[ { "ref_reco":1, "text":"If, and only if, Orlando is a regular consumer of Kiss My Face soap, then Orlando is a regular consumer of Nag Champa soap and Orlando is a occasional purchaser of Shield soap.", "explicit":False }, { "ref_reco":3, "text":"Orlando is a regular consumer of Kiss My Face soap. ", "explicit":True } ], "premises_formalized":[ { "ref_reco":1, "form":"${F1}${a1} <-> (${F2}${a1} & ${F3}${a1})" }, { "ref_reco":3, "form":"${F1}${a1}" } ] ``` #### Initial Data Collection and Normalization N.A. #### Who are the source language producers? N.A. ### Annotations #### Annotation process N.A. #### Who are the annotators? N.A. ### Personal and Sensitive Information N.A. ## Considerations for Using the Data ### Social Impact of Dataset None ### Discussion of Biases None ### Other Known Limitations See [Betz and Richardson 2021](https://arxiv.org/abs/2110.01509). ## Additional Information ### Dataset Curators Gregor Betz, Kyle Richardson ### Licensing Information Creative Commons cc-by-sa-4.0 ### Citation Information ``` @misc{betz2021deepa2, title={DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models}, author={Gregor Betz and Kyle Richardson}, year={2021}, eprint={2110.01509}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ### Contributions <!--Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.-->	[ -0.634746789932251, -0.6140331029891968, 0.420738160610199, -0.08424369245767593, -0.3020554482936859, -0.026742389425635338, 0.177129864692688, -0.22612214088439941, 0.4633091986179352, 0.4630812406539917, 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huggingartists/tiamat	huggingartists	2022-10-25T09:48:11Z	252	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/tiamat" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.115111 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/9ca13ed308504f6f9ac7c3cabdb54138.556x556x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/tiamat"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Tiamat</div> <a href="https://genius.com/artists/tiamat"> <div style="text-align: center; font-size: 14px;">@tiamat</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/tiamat). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/tiamat") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|122\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/tiamat") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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open-llm-leaderboard/details_psmathur__model_420	open-llm-leaderboard	2023-10-25T12:29:44Z	252	0	[ "region:us" ]	null	2023-08-18T00:15:55Z	--- pretty_name: Evaluation run of psmathur/model_420 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [psmathur/model_420](https://huggingface.co/psmathur/model_420) on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_psmathur__model_420\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T12:29:32.127683](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_420/blob/main/results_2023-10-25T12-29-32.127683.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.07770553691275167,\n\ \ \"em_stderr\": 0.002741576916689869,\n \"f1\": 0.1435245385906032,\n\ \ \"f1_stderr\": 0.0028999685202973128,\n \"acc\": 0.5616169002251712,\n\ \ \"acc_stderr\": 0.01140770950597949\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.07770553691275167,\n \"em_stderr\": 0.002741576916689869,\n\ \ \"f1\": 0.1435245385906032,\n \"f1_stderr\": 0.0028999685202973128\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.28582259287338896,\n \ \ \"acc_stderr\": 0.01244496346061563\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8374112075769534,\n \"acc_stderr\": 0.010370455551343348\n\ \ }\n}\n```" repo_url: https://huggingface.co/psmathur/model_420 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|arc:challenge\|25_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-09T21:30:53.861982.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T12_29_32.127683 path: - '/details_harness\|drop\|3_2023-10-25T12-29-32.127683.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-25T12-29-32.127683.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T12_29_32.127683 path: - '/details_harness\|gsm8k\|5_2023-10-25T12-29-32.127683.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-25T12-29-32.127683.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hellaswag\|10_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T21:30:53.861982.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T21:30:53.861982.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T21_30_53.861982 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T21:30:53.861982.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T21:30:53.861982.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T12_29_32.127683 path: - '/details_harness\|winogrande\|5_2023-10-25T12-29-32.127683.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-25T12-29-32.127683.parquet' - config_name: results data_files: - split: 2023_08_09T21_30_53.861982 path: - results_2023-08-09T21:30:53.861982.parquet - split: 2023_10_25T12_29_32.127683 path: - results_2023-10-25T12-29-32.127683.parquet - split: latest path: - results_2023-10-25T12-29-32.127683.parquet --- # Dataset Card for Evaluation run of psmathur/model_420 ## Dataset Description - Homepage: - Repository: https://huggingface.co/psmathur/model_420 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [psmathur/model_420](https://huggingface.co/psmathur/model_420) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_psmathur__model_420", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T12:29:32.127683](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_420/blob/main/results_2023-10-25T12-29-32.127683.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.07770553691275167, "em_stderr": 0.002741576916689869, "f1": 0.1435245385906032, "f1_stderr": 0.0028999685202973128, "acc": 0.5616169002251712, "acc_stderr": 0.01140770950597949 }, "harness\|drop\|3": { "em": 0.07770553691275167, "em_stderr": 0.002741576916689869, "f1": 0.1435245385906032, "f1_stderr": 0.0028999685202973128 }, "harness\|gsm8k\|5": { "acc": 0.28582259287338896, "acc_stderr": 0.01244496346061563 }, "harness\|winogrande\|5": { "acc": 0.8374112075769534, "acc_stderr": 0.010370455551343348 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.3985297679901123, -0.5802887082099915, 0.29743266105651855, 0.20329678058624268, -0.26596736907958984, 0.16878792643547058, -0.34813955426216125, -0.06316111236810684, 0.36110803484916687, 0.5224965810775757, -0.7475345134735107, -0.8875560760498047, -0.7082647085189819, 0.1930406540632248, -0.12249834835529327, 1.1604188680648804, -0.30322349071502686, -0.16266575455665588, -0.011378294788300991, -0.2410040646791458, -0.18314172327518463, -0.5221167206764221, -0.41490471363067627, 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open-llm-leaderboard/details_ToolBench__ToolLLaMA-7b-LoRA	open-llm-leaderboard	2023-09-18T01:38:44Z	252	1	[ "region:us" ]	null	2023-08-18T11:18:34Z	--- pretty_name: Evaluation run of ToolBench/ToolLLaMA-7b-LoRA dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ToolBench/ToolLLaMA-7b-LoRA](https://huggingface.co/ToolBench/ToolLLaMA-7b-LoRA)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ToolBench__ToolLLaMA-7b-LoRA\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-18T01:38:32.661486](https://huggingface.co/datasets/open-llm-leaderboard/details_ToolBench__ToolLLaMA-7b-LoRA/blob/main/results_2023-09-18T01-38-32.661486.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0010486577181208054,\n\ \ \"em_stderr\": 0.00033145814652191404,\n \"f1\": 0.056097944630872455,\n\ \ \"f1_stderr\": 0.001312187728090684,\n \"acc\": 0.40586103293913917,\n\ \ \"acc_stderr\": 0.00960950347641371\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0010486577181208054,\n \"em_stderr\": 0.00033145814652191404,\n\ \ \"f1\": 0.056097944630872455,\n \"f1_stderr\": 0.001312187728090684\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.06823351023502654,\n \ \ \"acc_stderr\": 0.006945358944067431\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7434885556432518,\n \"acc_stderr\": 0.01227364800875999\n\ \ }\n}\n```" repo_url: https://huggingface.co/ToolBench/ToolLLaMA-7b-LoRA leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|arc:challenge\|25_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-09T17:09:39.923597.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_18T01_38_32.661486 path: - '/details_harness\|drop\|3_2023-09-18T01-38-32.661486.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-18T01-38-32.661486.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_18T01_38_32.661486 path: - '/details_harness\|gsm8k\|5_2023-09-18T01-38-32.661486.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-18T01-38-32.661486.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hellaswag\|10_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T17:09:39.923597.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T17:09:39.923597.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T17_09_39.923597 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T17:09:39.923597.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T17:09:39.923597.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_18T01_38_32.661486 path: - '/details_harness\|winogrande\|5_2023-09-18T01-38-32.661486.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-18T01-38-32.661486.parquet' - config_name: results data_files: - split: 2023_08_09T17_09_39.923597 path: - results_2023-08-09T17:09:39.923597.parquet - split: 2023_09_18T01_38_32.661486 path: - results_2023-09-18T01-38-32.661486.parquet - split: latest path: - results_2023-09-18T01-38-32.661486.parquet --- # Dataset Card for Evaluation run of ToolBench/ToolLLaMA-7b-LoRA ## Dataset Description - Homepage: - Repository: https://huggingface.co/ToolBench/ToolLLaMA-7b-LoRA - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [ToolBench/ToolLLaMA-7b-LoRA](https://huggingface.co/ToolBench/ToolLLaMA-7b-LoRA) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ToolBench__ToolLLaMA-7b-LoRA", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-18T01:38:32.661486](https://huggingface.co/datasets/open-llm-leaderboard/details_ToolBench__ToolLLaMA-7b-LoRA/blob/main/results_2023-09-18T01-38-32.661486.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0010486577181208054, "em_stderr": 0.00033145814652191404, "f1": 0.056097944630872455, "f1_stderr": 0.001312187728090684, "acc": 0.40586103293913917, "acc_stderr": 0.00960950347641371 }, "harness\|drop\|3": { "em": 0.0010486577181208054, "em_stderr": 0.00033145814652191404, "f1": 0.056097944630872455, "f1_stderr": 0.001312187728090684 }, "harness\|gsm8k\|5": { "acc": 0.06823351023502654, "acc_stderr": 0.006945358944067431 }, "harness\|winogrande\|5": { "acc": 0.7434885556432518, "acc_stderr": 0.01227364800875999 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.4360024034976959, -0.7499079704284668, 0.2703962028026581, 0.2264321893453598, -0.19889789819717407, 0.1287187784910202, -0.3046393096446991, -0.1981835663318634, 0.4635685682296753, 0.5892806649208069, -0.6478828191757202, -0.9840114712715149, -0.6207358837127686, 0.08614951372146606, -0.31277334690093994, 1.0658977031707764, -0.19449639320373535, -0.2398485243320465, 0.13786198198795319, -0.34443971514701843, -0.3305421471595764, -0.41036131978034973, -0.4571765661239624, 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open-llm-leaderboard/details_sauce1337__BerrySauce-L2-13b	open-llm-leaderboard	2023-12-01T14:02:55Z	252	0	[ "region:us" ]	null	2023-09-14T17:30:13Z	--- pretty_name: Evaluation run of sauce1337/BerrySauce-L2-13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [sauce1337/BerrySauce-L2-13b](https://huggingface.co/sauce1337/BerrySauce-L2-13b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_sauce1337__BerrySauce-L2-13b_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-06T15:44:21.249547](https://huggingface.co/datasets/open-llm-leaderboard/details_sauce1337__BerrySauce-L2-13b_public/blob/main/results_2023-11-06T15-44-21.249547.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.30002097315436244,\n\ \ \"em_stderr\": 0.004693080166542511,\n \"f1\": 0.37748741610738484,\n\ \ \"f1_stderr\": 0.004586092728093026,\n \"acc\": 0.43918283744411857,\n\ \ \"acc_stderr\": 0.010429436550666943\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.30002097315436244,\n \"em_stderr\": 0.004693080166542511,\n\ \ \"f1\": 0.37748741610738484,\n \"f1_stderr\": 0.004586092728093026\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.11751326762699014,\n \ \ \"acc_stderr\": 0.008870331256489977\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.760852407261247,\n \"acc_stderr\": 0.011988541844843909\n\ \ }\n}\n```" repo_url: https://huggingface.co/sauce1337/BerrySauce-L2-13b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_drop_3 data_files: - split: 2023_11_04T16_52_54.420127 path: - '/details_harness\|drop\|3_2023-11-04T16-52-54.420127.parquet' - split: 2023_11_06T15_44_21.249547 path: - '/details_harness\|drop\|3_2023-11-06T15-44-21.249547.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-06T15-44-21.249547.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_04T16_52_54.420127 path: - '/details_harness\|gsm8k\|5_2023-11-04T16-52-54.420127.parquet' - split: 2023_11_06T15_44_21.249547 path: - '/details_harness\|gsm8k\|5_2023-11-06T15-44-21.249547.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-06T15-44-21.249547.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_04T16_52_54.420127 path: - '/details_harness\|winogrande\|5_2023-11-04T16-52-54.420127.parquet' - split: 2023_11_06T15_44_21.249547 path: - '/details_harness\|winogrande\|5_2023-11-06T15-44-21.249547.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-06T15-44-21.249547.parquet' - config_name: results data_files: - split: 2023_11_04T16_52_54.420127 path: - results_2023-11-04T16-52-54.420127.parquet - split: 2023_11_06T15_44_21.249547 path: - results_2023-11-06T15-44-21.249547.parquet - split: latest path: - results_2023-11-06T15-44-21.249547.parquet --- # Dataset Card for Evaluation run of sauce1337/BerrySauce-L2-13b ## Dataset Description - Homepage: - Repository: https://huggingface.co/sauce1337/BerrySauce-L2-13b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [sauce1337/BerrySauce-L2-13b](https://huggingface.co/sauce1337/BerrySauce-L2-13b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_sauce1337__BerrySauce-L2-13b_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-06T15:44:21.249547](https://huggingface.co/datasets/open-llm-leaderboard/details_sauce1337__BerrySauce-L2-13b_public/blob/main/results_2023-11-06T15-44-21.249547.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.30002097315436244, "em_stderr": 0.004693080166542511, "f1": 0.37748741610738484, "f1_stderr": 0.004586092728093026, "acc": 0.43918283744411857, "acc_stderr": 0.010429436550666943 }, "harness\|drop\|3": { "em": 0.30002097315436244, "em_stderr": 0.004693080166542511, "f1": 0.37748741610738484, "f1_stderr": 0.004586092728093026 }, "harness\|gsm8k\|5": { "acc": 0.11751326762699014, "acc_stderr": 0.008870331256489977 }, "harness\|winogrande\|5": { "acc": 0.760852407261247, "acc_stderr": 0.011988541844843909 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.3946404755115509, -0.6333516836166382, 0.08523184806108475, 0.23632235825061798, -0.0793626680970192, 0.11283894628286362, -0.4724344313144684, -0.1875716745853424, 0.4592858552932739, 0.5454442501068115, -0.7674182653427124, -0.9143031239509583, -0.6907347440719604, 0.1918492317199707, -0.18517138063907623, 1.1834670305252075, -0.21393126249313354, -0.12557436525821686, 0.020454049110412598, -0.20332425832748413, -0.4293866455554962, -0.3237681984901428, -0.5334576964378357, 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romero61/test_merra_pm25	romero61	2023-10-31T04:00:19Z	252	0	[ "license:mit", "region:us" ]	null	2023-10-20T23:08:57Z	--- license: mit ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 0.7903715372085571, -0.3810413181781769, 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fededeleon/CriteriosClasificacion	fededeleon	2022-02-08T15:35:04Z	251	0	[ "license:mit", "region:us" ]	null	2022-03-02T23:29:22Z	--- license: mit ---	[ -0.1285339891910553, -0.186167910695076, 0.6529129147529602, 0.4943627417087555, -0.19319313764572144, 0.23607458174228668, 0.3607197701931, 0.05056354030966759, 0.5793653726577759, 0.740013599395752, -0.6508103609085083, -0.2378397285938263, -0.7102249264717102, -0.047825902700424194, -0.3894753158092499, 0.8470762372016907, -0.09598255157470703, 0.024004921317100525, 0.047120124101638794, -0.14317825436592102, -0.612104058265686, -0.04771730303764343, -1.052453875541687, -0.06787486374378204, 0.3002282381057739, 0.5120974779129028, 0.8275899291038513, 0.3960294723510742, 0.503056526184082, 1.7515552043914795, -0.08836923539638519, -0.22754432260990143, -0.458920419216156, 0.4223068356513977, -0.3327738642692566, -0.4213368892669678, -0.26241645216941833, -0.0744934156537056, 0.32380396127700806, 0.7903715372085571, 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open-llm-leaderboard/details_facebook__opt-125m	open-llm-leaderboard	2023-10-19T00:45:41Z	251	0	[ "region:us" ]	null	2023-08-18T11:10:34Z	--- pretty_name: Evaluation run of facebook/opt-125m dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_facebook__opt-125m\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-19T00:45:29.121149](https://huggingface.co/datasets/open-llm-leaderboard/details_facebook__opt-125m/blob/main/results_2023-10-19T00-45-29.121149.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0009437919463087249,\n\ \ \"em_stderr\": 0.0003144653119413193,\n \"f1\": 0.0336220637583893,\n\ \ \"f1_stderr\": 0.001037070791466854,\n \"acc\": 0.25846905137888176,\n\ \ \"acc_stderr\": 0.007401638122350564\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0009437919463087249,\n \"em_stderr\": 0.0003144653119413193,\n\ \ \"f1\": 0.0336220637583893,\n \"f1_stderr\": 0.001037070791466854\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.000758150113722517,\n \ \ \"acc_stderr\": 0.0007581501137225268\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.516179952644041,\n \"acc_stderr\": 0.014045126130978601\n\ \ }\n}\n```" repo_url: https://huggingface.co/facebook/opt-125m leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|arc:challenge\|25_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T14:00:10.742260.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_19T00_45_29.121149 path: - '/details_harness\|drop\|3_2023-10-19T00-45-29.121149.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-19T00-45-29.121149.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_19T00_45_29.121149 path: - '/details_harness\|gsm8k\|5_2023-10-19T00-45-29.121149.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-19T00-45-29.121149.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hellaswag\|10_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T14:00:10.742260.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T14:00:10.742260.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T14_00_10.742260 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T14:00:10.742260.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T14:00:10.742260.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_19T00_45_29.121149 path: - '/details_harness\|winogrande\|5_2023-10-19T00-45-29.121149.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-19T00-45-29.121149.parquet' - config_name: results data_files: - split: 2023_07_19T14_00_10.742260 path: - results_2023-07-19T14:00:10.742260.parquet - split: 2023_10_19T00_45_29.121149 path: - results_2023-10-19T00-45-29.121149.parquet - split: latest path: - results_2023-10-19T00-45-29.121149.parquet --- # Dataset Card for Evaluation run of facebook/opt-125m ## Dataset Description - Homepage: - Repository: https://huggingface.co/facebook/opt-125m - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_facebook__opt-125m", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-19T00:45:29.121149](https://huggingface.co/datasets/open-llm-leaderboard/details_facebook__opt-125m/blob/main/results_2023-10-19T00-45-29.121149.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0009437919463087249, "em_stderr": 0.0003144653119413193, "f1": 0.0336220637583893, "f1_stderr": 0.001037070791466854, "acc": 0.25846905137888176, "acc_stderr": 0.007401638122350564 }, "harness\|drop\|3": { "em": 0.0009437919463087249, "em_stderr": 0.0003144653119413193, "f1": 0.0336220637583893, "f1_stderr": 0.001037070791466854 }, "harness\|gsm8k\|5": { "acc": 0.000758150113722517, "acc_stderr": 0.0007581501137225268 }, "harness\|winogrande\|5": { "acc": 0.516179952644041, "acc_stderr": 0.014045126130978601 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.41948121786117554, -0.8013442158699036, 0.20196513831615448, 0.2576545178890228, -0.10855524986982346, 0.16985610127449036, -0.4105670750141144, -0.20493152737617493, 0.5084872245788574, 0.5319650173187256, -0.8041663765907288, -0.9461069703102112, -0.6100829839706421, 0.18169903755187988, -0.2037789225578308, 1.0713766813278198, -0.23838847875595093, -0.2669793665409088, 0.029205242171883583, -0.24972335994243622, -0.282092422246933, -0.3944059908390045, -0.6019536852836609, 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open-llm-leaderboard/details_TFLai__OrcaMini-Platypus2-13B-QLoRA-0.80-epoch	open-llm-leaderboard	2023-10-18T23:55:12Z	251	0	[ "region:us" ]	null	2023-08-28T22:53:27Z	--- pretty_name: Evaluation run of TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch](https://huggingface.co/TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TFLai__OrcaMini-Platypus2-13B-QLoRA-0.80-epoch\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-18T23:54:59.357050](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__OrcaMini-Platypus2-13B-QLoRA-0.80-epoch/blob/main/results_2023-10-18T23-54-59.357050.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.40216023489932884,\n\ \ \"em_stderr\": 0.005021478569413354,\n \"f1\": 0.47240666946308846,\n\ \ \"f1_stderr\": 0.004780752235261512,\n \"acc\": 0.39100918935382517,\n\ \ \"acc_stderr\": 0.008061089924986945\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.40216023489932884,\n \"em_stderr\": 0.005021478569413354,\n\ \ \"f1\": 0.47240666946308846,\n \"f1_stderr\": 0.004780752235261512\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.022744503411675512,\n \ \ \"acc_stderr\": 0.004106620637749706\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7592738752959748,\n \"acc_stderr\": 0.012015559212224183\n\ \ }\n}\n```" repo_url: https://huggingface.co/TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|arc:challenge\|25_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-28T22:52:27.560095.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_18T23_54_59.357050 path: - '/details_harness\|drop\|3_2023-10-18T23-54-59.357050.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-18T23-54-59.357050.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_18T23_54_59.357050 path: - '/details_harness\|gsm8k\|5_2023-10-18T23-54-59.357050.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-18T23-54-59.357050.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hellaswag\|10_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-28T22:52:27.560095.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-28T22:52:27.560095.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_28T22_52_27.560095 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-28T22:52:27.560095.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-28T22:52:27.560095.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_18T23_54_59.357050 path: - '/details_harness\|winogrande\|5_2023-10-18T23-54-59.357050.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-18T23-54-59.357050.parquet' - config_name: results data_files: - split: 2023_08_28T22_52_27.560095 path: - results_2023-08-28T22:52:27.560095.parquet - split: 2023_10_18T23_54_59.357050 path: - results_2023-10-18T23-54-59.357050.parquet - split: latest path: - results_2023-10-18T23-54-59.357050.parquet --- # Dataset Card for Evaluation run of TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch ## Dataset Description - Homepage: - Repository: https://huggingface.co/TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch](https://huggingface.co/TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TFLai__OrcaMini-Platypus2-13B-QLoRA-0.80-epoch", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-18T23:54:59.357050](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__OrcaMini-Platypus2-13B-QLoRA-0.80-epoch/blob/main/results_2023-10-18T23-54-59.357050.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.40216023489932884, "em_stderr": 0.005021478569413354, "f1": 0.47240666946308846, "f1_stderr": 0.004780752235261512, "acc": 0.39100918935382517, "acc_stderr": 0.008061089924986945 }, "harness\|drop\|3": { "em": 0.40216023489932884, "em_stderr": 0.005021478569413354, "f1": 0.47240666946308846, "f1_stderr": 0.004780752235261512 }, "harness\|gsm8k\|5": { "acc": 0.022744503411675512, "acc_stderr": 0.004106620637749706 }, "harness\|winogrande\|5": { "acc": 0.7592738752959748, "acc_stderr": 0.012015559212224183 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.33580052852630615, -0.6422783136367798, 0.2156350165605545, 0.17613713443279266, -0.21740806102752686, 0.10329925268888474, -0.3623524308204651, -0.20605969429016113, 0.35326847434043884, 0.44962629675865173, -0.6364198327064514, -0.8938819169998169, -0.6343321800231934, 0.0571708157658577, -0.09045781940221786, 1.1093472242355347, -0.2607516944408417, -0.14243333041667938, 0.18344564735889435, -0.35240015387535095, -0.37481507658958435, -0.3507869243621826, -0.6502650380134583, 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tner/ontonotes5	tner	2022-07-18T00:43:55Z	250	3	[ "task_categories:token-classification", "task_ids:named-entity-recognition", "multilinguality:monolingual", "size_categories:10K<n<100K", "language:en", "license:other", "region:us" ]	[ "token-classification" ]	2022-07-16T11:07:45Z	--- language: - en license: - other multilinguality: - monolingual size_categories: - 10K<n<100K task_categories: - token-classification task_ids: - named-entity-recognition pretty_name: Ontonotes5 --- # Dataset Card for "tner/ontonotes5" ## Dataset Description - Repository: [T-NER](https://github.com/asahi417/tner) - Paper: [https://aclanthology.org/N06-2015/](https://aclanthology.org/N06-2015/) - Dataset: Ontonotes5 - Domain: News - Number of Entity: 8 ### Dataset Summary Ontonotes5 NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. - Entity Types: `CARDINAL`, `DATE`, `PERSON`, `NORP`, `GPE`, `LAW`, `PERCENT`, `ORDINAL`, `MONEY`, `WORK_OF_ART`, `FAC`, `TIME`, `QUANTITY`, `PRODUCT`, `LANGUAGE`, `ORG`, `LOC`, `EVENT` ## Dataset Structure ### Data Instances An example of `train` looks as follows. ``` { 'tags': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 5, 0, 0, 0, 0, 11, 12, 12, 12, 12, 0, 0, 7, 0, 0, 0, 0, 0], 'tokens': ['``', 'It', "'s", 'very', 'costly', 'and', 'time', '-', 'consuming', ',', "''", 'says', 'Phil', 'Rosen', ',', 'a', 'partner', 'in', 'Fleet', '&', 'Leasing', 'Management', 'Inc.', ',', 'a', 'Boston', 'car', '-', 'leasing', 'company', '.'] } ``` ### Label ID The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/onotonotes5/raw/main/dataset/label.json). ```python { "O": 0, "B-CARDINAL": 1, "B-DATE": 2, "I-DATE": 3, "B-PERSON": 4, "I-PERSON": 5, "B-NORP": 6, "B-GPE": 7, "I-GPE": 8, "B-LAW": 9, "I-LAW": 10, "B-ORG": 11, "I-ORG": 12, "B-PERCENT": 13, "I-PERCENT": 14, "B-ORDINAL": 15, "B-MONEY": 16, "I-MONEY": 17, "B-WORK_OF_ART": 18, "I-WORK_OF_ART": 19, "B-FAC": 20, "B-TIME": 21, "I-CARDINAL": 22, "B-LOC": 23, "B-QUANTITY": 24, "I-QUANTITY": 25, "I-NORP": 26, "I-LOC": 27, "B-PRODUCT": 28, "I-TIME": 29, "B-EVENT": 30, "I-EVENT": 31, "I-FAC": 32, "B-LANGUAGE": 33, "I-PRODUCT": 34, "I-ORDINAL": 35, "I-LANGUAGE": 36 } ``` ### Data Splits \| name \|train\|validation\|test\| \|---------\|----:\|---------:\|---:\| \|ontonotes5\|59924\| 8528\|8262\| ### Citation Information ``` @inproceedings{hovy-etal-2006-ontonotes, title = "{O}nto{N}otes: The 90{\%} Solution", author = "Hovy, Eduard and Marcus, Mitchell and Palmer, Martha and Ramshaw, Lance and Weischedel, Ralph", booktitle = "Proceedings of the Human Language Technology Conference of the {NAACL}, Companion Volume: Short Papers", month = jun, year = "2006", address = "New York City, USA", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/N06-2015", pages = "57--60", } ```	[ -0.501763105392456, -0.43243956565856934, 0.1742819994688034, 0.13700741529464722, -0.20349140465259552, -0.10511665046215057, 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clarin-pl/poquad	clarin-pl	2023-07-04T10:50:43Z	250	1	[ "task_categories:question-answering", "task_ids:extractive-qa", "task_ids:open-domain-qa", "annotations_creators:expert-generated", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:pl", "license:cc-by-4.0", "region:us" ]	[ "question-answering" ]	2023-02-28T09:46:17Z	--- annotations_creators: - expert-generated language_creators: - found language: - pl license: - cc-by-4.0 multilinguality: - monolingual pretty_name: PoQuaD size_categories: - 10K<n<100K source_datasets: - original task_categories: - question-answering task_ids: - extractive-qa - open-domain-qa --- PoQuaD dataset	[ -0.21460585296154022, -0.5306757688522339, -0.035968780517578125, 0.19868560135364532, -0.19321803748607635, -0.1726938933134079, 0.4395027458667755, 0.4703359007835388, 0.29812130331993103, 0.8671456575393677, -0.032054878771305084, -0.6531209945678711, -0.27551016211509705, 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open-llm-leaderboard/details_TigerResearch__tigerbot-7b-sft	open-llm-leaderboard	2023-09-16T22:00:13Z	250	0	[ "region:us" ]	null	2023-08-17T23:44:54Z	--- pretty_name: Evaluation run of TigerResearch/tigerbot-7b-sft dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TigerResearch/tigerbot-7b-sft](https://huggingface.co/TigerResearch/tigerbot-7b-sft)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TigerResearch__tigerbot-7b-sft\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-16T22:00:02.425460](https://huggingface.co/datasets/open-llm-leaderboard/details_TigerResearch__tigerbot-7b-sft/blob/main/results_2023-09-16T22-00-02.425460.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.23290687919463088,\n\ \ \"em_stderr\": 0.0043286737393498816,\n \"f1\": 0.26997588087248303,\n\ \ \"f1_stderr\": 0.00434706090322385,\n \"acc\": 0.3491427877305342,\n\ \ \"acc_stderr\": 0.010108254601981293\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.23290687919463088,\n \"em_stderr\": 0.0043286737393498816,\n\ \ \"f1\": 0.26997588087248303,\n \"f1_stderr\": 0.00434706090322385\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.06292645943896892,\n \ \ \"acc_stderr\": 0.006688762581532747\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6353591160220995,\n \"acc_stderr\": 0.013527746622429839\n\ \ }\n}\n```" repo_url: https://huggingface.co/TigerResearch/tigerbot-7b-sft leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|arc:challenge\|25_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-17T10:11:16.133446.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_16T22_00_02.425460 path: - '/details_harness\|drop\|3_2023-09-16T22-00-02.425460.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-16T22-00-02.425460.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_16T22_00_02.425460 path: - '/details_harness\|gsm8k\|5_2023-09-16T22-00-02.425460.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-16T22-00-02.425460.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hellaswag\|10_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T10:11:16.133446.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T10:11:16.133446.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_17T10_11_16.133446 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T10:11:16.133446.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T10:11:16.133446.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_16T22_00_02.425460 path: - '/details_harness\|winogrande\|5_2023-09-16T22-00-02.425460.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-16T22-00-02.425460.parquet' - config_name: results data_files: - split: 2023_08_17T10_11_16.133446 path: - results_2023-08-17T10:11:16.133446.parquet - split: 2023_09_16T22_00_02.425460 path: - results_2023-09-16T22-00-02.425460.parquet - split: latest path: - results_2023-09-16T22-00-02.425460.parquet --- # Dataset Card for Evaluation run of TigerResearch/tigerbot-7b-sft ## Dataset Description - Homepage: - Repository: https://huggingface.co/TigerResearch/tigerbot-7b-sft - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [TigerResearch/tigerbot-7b-sft](https://huggingface.co/TigerResearch/tigerbot-7b-sft) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TigerResearch__tigerbot-7b-sft", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-16T22:00:02.425460](https://huggingface.co/datasets/open-llm-leaderboard/details_TigerResearch__tigerbot-7b-sft/blob/main/results_2023-09-16T22-00-02.425460.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.23290687919463088, "em_stderr": 0.0043286737393498816, "f1": 0.26997588087248303, "f1_stderr": 0.00434706090322385, "acc": 0.3491427877305342, "acc_stderr": 0.010108254601981293 }, "harness\|drop\|3": { "em": 0.23290687919463088, "em_stderr": 0.0043286737393498816, "f1": 0.26997588087248303, "f1_stderr": 0.00434706090322385 }, "harness\|gsm8k\|5": { "acc": 0.06292645943896892, "acc_stderr": 0.006688762581532747 }, "harness\|winogrande\|5": { "acc": 0.6353591160220995, "acc_stderr": 0.013527746622429839 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.4178852438926697, -0.6235637664794922, 0.1923273205757141, 0.23674146831035614, -0.2247723639011383, 0.17970289289951324, -0.3606410622596741, -0.15660731494426727, 0.43909192085266113, 0.5764943361282349, -0.6901885271072388, -0.8924827575683594, -0.5545397400856018, 0.2291918694972992, -0.1407235562801361, 1.1688518524169922, -0.17276844382286072, -0.2797762453556061, 0.07368110120296478, -0.3531728982925415, -0.34665510058403015, -0.5113113522529602, -0.5586288571357727, 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open-llm-leaderboard/details_edor__Stable-Platypus2-mini-7B	open-llm-leaderboard	2023-08-27T12:25:35Z	250	0	[ "region:us" ]	null	2023-08-17T23:57:18Z	--- pretty_name: Evaluation run of edor/Stable-Platypus2-mini-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [edor/Stable-Platypus2-mini-7B](https://huggingface.co/edor/Stable-Platypus2-mini-7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_edor__Stable-Platypus2-mini-7B\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-16T10:44:20.574252](https://huggingface.co/datasets/open-llm-leaderboard/details_edor__Stable-Platypus2-mini-7B/blob/main/results_2023-08-16T10%3A44%3A20.574252.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.519238503099194,\n\ \ \"acc_stderr\": 0.03487887571401071,\n \"acc_norm\": 0.5229272130971759,\n\ \ \"acc_norm_stderr\": 0.03486396112216957,\n \"mc1\": 0.3561811505507956,\n\ \ \"mc1_stderr\": 0.01676379072844634,\n \"mc2\": 0.5106039601116779,\n\ \ \"mc2_stderr\": 0.015454187246822623\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5238907849829352,\n \"acc_stderr\": 0.014594701798071654,\n\ \ \"acc_norm\": 0.5486348122866894,\n \"acc_norm_stderr\": 0.014542104569955267\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5965943039235212,\n\ \ \"acc_stderr\": 0.004895782107786497,\n \"acc_norm\": 0.7894841665006971,\n\ \ \"acc_norm_stderr\": 0.0040684184172756635\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4888888888888889,\n\ \ \"acc_stderr\": 0.04318275491977976,\n \"acc_norm\": 0.4888888888888889,\n\ \ \"acc_norm_stderr\": 0.04318275491977976\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.40789473684210525,\n \"acc_stderr\": 0.03999309712777471,\n\ \ \"acc_norm\": 0.40789473684210525,\n \"acc_norm_stderr\": 0.03999309712777471\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5924528301886792,\n \"acc_stderr\": 0.03024223380085449,\n\ \ \"acc_norm\": 0.5924528301886792,\n \"acc_norm_stderr\": 0.03024223380085449\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.5416666666666666,\n\ \ \"acc_stderr\": 0.04166666666666666,\n \"acc_norm\": 0.5416666666666666,\n\ \ \"acc_norm_stderr\": 0.04166666666666666\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145632,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145632\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001974\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.4682080924855491,\n\ \ \"acc_stderr\": 0.03804749744364764,\n \"acc_norm\": 0.4682080924855491,\n\ \ \"acc_norm_stderr\": 0.03804749744364764\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.27450980392156865,\n \"acc_stderr\": 0.04440521906179327,\n\ \ \"acc_norm\": 0.27450980392156865,\n \"acc_norm_stderr\": 0.04440521906179327\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.61,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.4765957446808511,\n \"acc_stderr\": 0.03265019475033582,\n\ \ \"acc_norm\": 0.4765957446808511,\n \"acc_norm_stderr\": 0.03265019475033582\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2631578947368421,\n\ \ \"acc_stderr\": 0.041424397194893624,\n \"acc_norm\": 0.2631578947368421,\n\ \ \"acc_norm_stderr\": 0.041424397194893624\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4896551724137931,\n \"acc_stderr\": 0.04165774775728763,\n\ \ \"acc_norm\": 0.4896551724137931,\n \"acc_norm_stderr\": 0.04165774775728763\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.30158730158730157,\n \"acc_stderr\": 0.0236369759961018,\n \"\ acc_norm\": 0.30158730158730157,\n \"acc_norm_stderr\": 0.0236369759961018\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.31746031746031744,\n\ \ \"acc_stderr\": 0.04163453031302859,\n \"acc_norm\": 0.31746031746031744,\n\ \ \"acc_norm_stderr\": 0.04163453031302859\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.5645161290322581,\n \"acc_stderr\": 0.02820622559150274,\n \"\ acc_norm\": 0.5645161290322581,\n \"acc_norm_stderr\": 0.02820622559150274\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.3448275862068966,\n \"acc_stderr\": 0.033442837442804574,\n \"\ acc_norm\": 0.3448275862068966,\n \"acc_norm_stderr\": 0.033442837442804574\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7212121212121212,\n \"acc_stderr\": 0.03501438706296781,\n\ \ \"acc_norm\": 0.7212121212121212,\n \"acc_norm_stderr\": 0.03501438706296781\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.6414141414141414,\n \"acc_stderr\": 0.034169036403915214,\n \"\ acc_norm\": 0.6414141414141414,\n \"acc_norm_stderr\": 0.034169036403915214\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7772020725388601,\n \"acc_stderr\": 0.030031147977641538,\n\ \ \"acc_norm\": 0.7772020725388601,\n \"acc_norm_stderr\": 0.030031147977641538\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4948717948717949,\n \"acc_stderr\": 0.02534967290683866,\n \ \ \"acc_norm\": 0.4948717948717949,\n \"acc_norm_stderr\": 0.02534967290683866\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.24814814814814815,\n \"acc_stderr\": 0.0263357394040558,\n \ \ \"acc_norm\": 0.24814814814814815,\n \"acc_norm_stderr\": 0.0263357394040558\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5168067226890757,\n \"acc_stderr\": 0.03246013680375308,\n \ \ \"acc_norm\": 0.5168067226890757,\n \"acc_norm_stderr\": 0.03246013680375308\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.037345356767871984,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.037345356767871984\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7321100917431193,\n \"acc_stderr\": 0.018987462257978652,\n \"\ acc_norm\": 0.7321100917431193,\n \"acc_norm_stderr\": 0.018987462257978652\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.42592592592592593,\n \"acc_stderr\": 0.03372343271653063,\n \"\ acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.03372343271653063\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.696078431372549,\n \"acc_stderr\": 0.03228210387037893,\n \"acc_norm\"\ : 0.696078431372549,\n \"acc_norm_stderr\": 0.03228210387037893\n },\n\ \ \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"acc\":\ \ 0.7130801687763713,\n \"acc_stderr\": 0.029443773022594693,\n \"\ acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.029443773022594693\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6143497757847534,\n\ \ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.6143497757847534,\n\ \ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6106870229007634,\n \"acc_stderr\": 0.04276486542814591,\n\ \ \"acc_norm\": 0.6106870229007634,\n \"acc_norm_stderr\": 0.04276486542814591\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.6859504132231405,\n \"acc_stderr\": 0.042369647530410184,\n \"\ acc_norm\": 0.6859504132231405,\n \"acc_norm_stderr\": 0.042369647530410184\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.5833333333333334,\n\ \ \"acc_stderr\": 0.04766075165356461,\n \"acc_norm\": 0.5833333333333334,\n\ \ \"acc_norm_stderr\": 0.04766075165356461\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.5460122699386503,\n \"acc_stderr\": 0.0391170190467718,\n\ \ \"acc_norm\": 0.5460122699386503,\n \"acc_norm_stderr\": 0.0391170190467718\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4107142857142857,\n\ \ \"acc_stderr\": 0.04669510663875191,\n \"acc_norm\": 0.4107142857142857,\n\ \ \"acc_norm_stderr\": 0.04669510663875191\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7281553398058253,\n \"acc_stderr\": 0.044052680241409216,\n\ \ \"acc_norm\": 0.7281553398058253,\n \"acc_norm_stderr\": 0.044052680241409216\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.782051282051282,\n\ \ \"acc_stderr\": 0.02704685763071669,\n \"acc_norm\": 0.782051282051282,\n\ \ \"acc_norm_stderr\": 0.02704685763071669\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7164750957854407,\n\ \ \"acc_stderr\": 0.01611731816683227,\n \"acc_norm\": 0.7164750957854407,\n\ \ \"acc_norm_stderr\": 0.01611731816683227\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.5780346820809249,\n \"acc_stderr\": 0.026589231142174263,\n\ \ \"acc_norm\": 0.5780346820809249,\n \"acc_norm_stderr\": 0.026589231142174263\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2569832402234637,\n\ \ \"acc_stderr\": 0.01461446582196633,\n \"acc_norm\": 0.2569832402234637,\n\ \ \"acc_norm_stderr\": 0.01461446582196633\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5424836601307189,\n \"acc_stderr\": 0.028526383452142635,\n\ \ \"acc_norm\": 0.5424836601307189,\n \"acc_norm_stderr\": 0.028526383452142635\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.5852090032154341,\n\ \ \"acc_stderr\": 0.027982680459759563,\n \"acc_norm\": 0.5852090032154341,\n\ \ \"acc_norm_stderr\": 0.027982680459759563\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.5370370370370371,\n \"acc_stderr\": 0.027744313443376536,\n\ \ \"acc_norm\": 0.5370370370370371,\n \"acc_norm_stderr\": 0.027744313443376536\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.3900709219858156,\n \"acc_stderr\": 0.029097675599463926,\n \ \ \"acc_norm\": 0.3900709219858156,\n \"acc_norm_stderr\": 0.029097675599463926\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3917861799217731,\n\ \ \"acc_stderr\": 0.01246756441814513,\n \"acc_norm\": 0.3917861799217731,\n\ \ \"acc_norm_stderr\": 0.01246756441814513\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5183823529411765,\n \"acc_stderr\": 0.03035230339535197,\n\ \ \"acc_norm\": 0.5183823529411765,\n \"acc_norm_stderr\": 0.03035230339535197\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5098039215686274,\n \"acc_stderr\": 0.0202239460050743,\n \ \ \"acc_norm\": 0.5098039215686274,\n \"acc_norm_stderr\": 0.0202239460050743\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6181818181818182,\n\ \ \"acc_stderr\": 0.046534298079135075,\n \"acc_norm\": 0.6181818181818182,\n\ \ \"acc_norm_stderr\": 0.046534298079135075\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6571428571428571,\n \"acc_stderr\": 0.030387262919547735,\n\ \ \"acc_norm\": 0.6571428571428571,\n \"acc_norm_stderr\": 0.030387262919547735\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6318407960199005,\n\ \ \"acc_stderr\": 0.03410410565495302,\n \"acc_norm\": 0.6318407960199005,\n\ \ \"acc_norm_stderr\": 0.03410410565495302\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.42771084337349397,\n\ \ \"acc_stderr\": 0.03851597683718534,\n \"acc_norm\": 0.42771084337349397,\n\ \ \"acc_norm_stderr\": 0.03851597683718534\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.695906432748538,\n \"acc_stderr\": 0.03528211258245229,\n\ \ \"acc_norm\": 0.695906432748538,\n \"acc_norm_stderr\": 0.03528211258245229\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3561811505507956,\n\ \ \"mc1_stderr\": 0.01676379072844634,\n \"mc2\": 0.5106039601116779,\n\ \ \"mc2_stderr\": 0.015454187246822623\n }\n}\n```" repo_url: https://huggingface.co/edor/Stable-Platypus2-mini-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|arc:challenge\|25_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hellaswag\|10_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-16T10:44:20.574252.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-16T10:44:20.574252.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_16T10_44_20.574252 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-16T10:44:20.574252.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-16T10:44:20.574252.parquet' - config_name: results data_files: - split: 2023_08_16T10_44_20.574252 path: - results_2023-08-16T10:44:20.574252.parquet - split: latest path: - results_2023-08-16T10:44:20.574252.parquet --- # Dataset Card for Evaluation run of edor/Stable-Platypus2-mini-7B ## Dataset Description - Homepage: - Repository: https://huggingface.co/edor/Stable-Platypus2-mini-7B - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [edor/Stable-Platypus2-mini-7B](https://huggingface.co/edor/Stable-Platypus2-mini-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_edor__Stable-Platypus2-mini-7B", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-16T10:44:20.574252](https://huggingface.co/datasets/open-llm-leaderboard/details_edor__Stable-Platypus2-mini-7B/blob/main/results_2023-08-16T10%3A44%3A20.574252.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.519238503099194, "acc_stderr": 0.03487887571401071, "acc_norm": 0.5229272130971759, "acc_norm_stderr": 0.03486396112216957, "mc1": 0.3561811505507956, "mc1_stderr": 0.01676379072844634, "mc2": 0.5106039601116779, "mc2_stderr": 0.015454187246822623 }, "harness\|arc:challenge\|25": { "acc": 0.5238907849829352, "acc_stderr": 0.014594701798071654, "acc_norm": 0.5486348122866894, "acc_norm_stderr": 0.014542104569955267 }, "harness\|hellaswag\|10": { "acc": 0.5965943039235212, "acc_stderr": 0.004895782107786497, "acc_norm": 0.7894841665006971, "acc_norm_stderr": 0.0040684184172756635 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4888888888888889, "acc_stderr": 0.04318275491977976, "acc_norm": 0.4888888888888889, "acc_norm_stderr": 0.04318275491977976 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.40789473684210525, "acc_stderr": 0.03999309712777471, "acc_norm": 0.40789473684210525, "acc_norm_stderr": 0.03999309712777471 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5924528301886792, "acc_stderr": 0.03024223380085449, "acc_norm": 0.5924528301886792, "acc_norm_stderr": 0.03024223380085449 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.5416666666666666, "acc_stderr": 0.04166666666666666, "acc_norm": 0.5416666666666666, "acc_norm_stderr": 0.04166666666666666 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.38, "acc_stderr": 0.04878317312145632, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145632 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.4682080924855491, "acc_stderr": 0.03804749744364764, "acc_norm": 0.4682080924855491, "acc_norm_stderr": 0.03804749744364764 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.27450980392156865, "acc_stderr": 0.04440521906179327, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.04440521906179327 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.4765957446808511, "acc_stderr": 0.03265019475033582, "acc_norm": 0.4765957446808511, "acc_norm_stderr": 0.03265019475033582 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2631578947368421, "acc_stderr": 0.041424397194893624, "acc_norm": 0.2631578947368421, "acc_norm_stderr": 0.041424397194893624 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4896551724137931, "acc_stderr": 0.04165774775728763, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.04165774775728763 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.30158730158730157, "acc_stderr": 0.0236369759961018, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.0236369759961018 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.5645161290322581, "acc_stderr": 0.02820622559150274, "acc_norm": 0.5645161290322581, "acc_norm_stderr": 0.02820622559150274 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3448275862068966, "acc_stderr": 0.033442837442804574, "acc_norm": 0.3448275862068966, "acc_norm_stderr": 0.033442837442804574 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.6414141414141414, "acc_stderr": 0.034169036403915214, "acc_norm": 0.6414141414141414, "acc_norm_stderr": 0.034169036403915214 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7772020725388601, "acc_stderr": 0.030031147977641538, "acc_norm": 0.7772020725388601, "acc_norm_stderr": 0.030031147977641538 }, 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[More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7417596578598022, -0.8678562045097351, 0.2740305960178375, 0.1998538225889206, -0.1751689612865448, -0.06231966242194176, 0.008731464855372906, -0.20075270533561707, 0.582740306854248, -0.0684046745300293, -0.4518018066883087, -0.6539527177810669, -0.45504888892173767, 0.258643239736557, -0.01750931702554226, 0.8358926773071289, -0.21710258722305298, -0.14744529128074646, 0.07584372162818909, -0.07562555372714996, -0.2736036777496338, -0.3256322741508484, -0.49749720096588135, 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open-llm-leaderboard/details_KnutJaegersberg__galactica-orca-wizardlm-1.3b	open-llm-leaderboard	2023-08-27T12:31:03Z	250	0	[ "region:us" ]	null	2023-08-18T11:11:16Z	--- pretty_name: Evaluation run of KnutJaegersberg/galactica-orca-wizardlm-1.3b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [KnutJaegersberg/galactica-orca-wizardlm-1.3b](https://huggingface.co/KnutJaegersberg/galactica-orca-wizardlm-1.3b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_KnutJaegersberg__galactica-orca-wizardlm-1.3b\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-07-27T10:33:13.422388](https://huggingface.co/datasets/open-llm-leaderboard/details_KnutJaegersberg__galactica-orca-wizardlm-1.3b/blob/main/results_2023-07-27T10%3A33%3A13.422388.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2607167828475717,\n\ \ \"acc_stderr\": 0.031890976655530354,\n \"acc_norm\": 0.2619942427603414,\n\ \ \"acc_norm_stderr\": 0.03190140774792886,\n \"mc1\": 0.25458996328029376,\n\ \ \"mc1_stderr\": 0.015250117079156494,\n \"mc2\": 0.41268090479367026,\n\ \ \"mc2_stderr\": 0.015430187488430076\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.27303754266211605,\n \"acc_stderr\": 0.013019332762635727,\n\ \ \"acc_norm\": 0.30887372013651876,\n \"acc_norm_stderr\": 0.013501770929344004\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.32065325632344155,\n\ \ \"acc_stderr\": 0.004657738398900916,\n \"acc_norm\": 0.3601872137024497,\n\ \ \"acc_norm_stderr\": 0.004790734683704583\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2814814814814815,\n\ \ \"acc_stderr\": 0.038850042458002526,\n \"acc_norm\": 0.2814814814814815,\n\ \ \"acc_norm_stderr\": 0.038850042458002526\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.24342105263157895,\n \"acc_stderr\": 0.034923496688842384,\n\ \ \"acc_norm\": 0.24342105263157895,\n \"acc_norm_stderr\": 0.034923496688842384\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.31,\n\ \ \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n \ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.26037735849056604,\n \"acc_stderr\": 0.027008766090708104,\n\ \ \"acc_norm\": 0.26037735849056604,\n \"acc_norm_stderr\": 0.027008766090708104\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.03942082639927213,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.03942082639927213\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.17,\n \"acc_stderr\": 0.03775251680686371,\n \ \ \"acc_norm\": 0.17,\n \"acc_norm_stderr\": 0.03775251680686371\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.19,\n \"acc_stderr\": 0.03942772444036623,\n \"acc_norm\": 0.19,\n\ \ \"acc_norm_stderr\": 0.03942772444036623\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768079,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768079\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.2774566473988439,\n\ \ \"acc_stderr\": 0.03414014007044036,\n \"acc_norm\": 0.2774566473988439,\n\ \ \"acc_norm_stderr\": 0.03414014007044036\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237655,\n\ \ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237655\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n\ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102963,\n\ \ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102963\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2543859649122807,\n\ \ \"acc_stderr\": 0.040969851398436716,\n \"acc_norm\": 0.2543859649122807,\n\ \ \"acc_norm_stderr\": 0.040969851398436716\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.3310344827586207,\n \"acc_stderr\": 0.03921545312467122,\n\ \ \"acc_norm\": 0.3310344827586207,\n \"acc_norm_stderr\": 0.03921545312467122\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2830687830687831,\n \"acc_stderr\": 0.023201392938194974,\n \"\ acc_norm\": 0.2830687830687831,\n \"acc_norm_stderr\": 0.023201392938194974\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.19047619047619047,\n\ \ \"acc_stderr\": 0.035122074123020534,\n \"acc_norm\": 0.19047619047619047,\n\ \ \"acc_norm_stderr\": 0.035122074123020534\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.2161290322580645,\n\ \ \"acc_stderr\": 0.02341529343356852,\n \"acc_norm\": 0.2161290322580645,\n\ \ \"acc_norm_stderr\": 0.02341529343356852\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.23645320197044334,\n \"acc_stderr\": 0.029896114291733552,\n\ \ \"acc_norm\": 0.23645320197044334,\n \"acc_norm_stderr\": 0.029896114291733552\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.23030303030303031,\n \"acc_stderr\": 0.03287666758603489,\n\ \ \"acc_norm\": 0.23030303030303031,\n \"acc_norm_stderr\": 0.03287666758603489\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.20707070707070707,\n \"acc_stderr\": 0.028869778460267063,\n \"\ acc_norm\": 0.20707070707070707,\n \"acc_norm_stderr\": 0.028869778460267063\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.22279792746113988,\n \"acc_stderr\": 0.03003114797764154,\n\ \ \"acc_norm\": 0.22279792746113988,\n \"acc_norm_stderr\": 0.03003114797764154\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.31794871794871793,\n \"acc_stderr\": 0.023610884308927865,\n\ \ \"acc_norm\": 0.31794871794871793,\n \"acc_norm_stderr\": 0.023610884308927865\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2777777777777778,\n \"acc_stderr\": 0.027309140588230182,\n \ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.027309140588230182\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.23529411764705882,\n \"acc_stderr\": 0.027553614467863804,\n\ \ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.027553614467863804\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.24503311258278146,\n \"acc_stderr\": 0.03511807571804724,\n \"\ acc_norm\": 0.24503311258278146,\n \"acc_norm_stderr\": 0.03511807571804724\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.25137614678899084,\n \"acc_stderr\": 0.018599206360287415,\n \"\ acc_norm\": 0.25137614678899084,\n \"acc_norm_stderr\": 0.018599206360287415\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.30092592592592593,\n \"acc_stderr\": 0.03128039084329883,\n \"\ acc_norm\": 0.30092592592592593,\n \"acc_norm_stderr\": 0.03128039084329883\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.2549019607843137,\n \"acc_stderr\": 0.030587591351604246,\n \"\ acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.030587591351604246\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n \ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.32286995515695066,\n\ \ \"acc_stderr\": 0.03138147637575498,\n \"acc_norm\": 0.32286995515695066,\n\ \ \"acc_norm_stderr\": 0.03138147637575498\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.183206106870229,\n \"acc_stderr\": 0.033927709264947335,\n\ \ \"acc_norm\": 0.183206106870229,\n \"acc_norm_stderr\": 0.033927709264947335\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.24793388429752067,\n \"acc_stderr\": 0.03941897526516301,\n \"\ acc_norm\": 0.24793388429752067,\n \"acc_norm_stderr\": 0.03941897526516301\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.2147239263803681,\n \"acc_stderr\": 0.032262193772867744,\n\ \ \"acc_norm\": 0.2147239263803681,\n \"acc_norm_stderr\": 0.032262193772867744\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.25892857142857145,\n\ \ \"acc_stderr\": 0.04157751539865629,\n \"acc_norm\": 0.25892857142857145,\n\ \ \"acc_norm_stderr\": 0.04157751539865629\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.32038834951456313,\n \"acc_stderr\": 0.0462028408228004,\n\ \ \"acc_norm\": 0.32038834951456313,\n \"acc_norm_stderr\": 0.0462028408228004\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.02934311479809447,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.02934311479809447\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.24393358876117496,\n\ \ \"acc_stderr\": 0.015357212665829468,\n \"acc_norm\": 0.24393358876117496,\n\ \ \"acc_norm_stderr\": 0.015357212665829468\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.30057803468208094,\n \"acc_stderr\": 0.02468531686725781,\n\ \ \"acc_norm\": 0.30057803468208094,\n \"acc_norm_stderr\": 0.02468531686725781\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23687150837988827,\n\ \ \"acc_stderr\": 0.014219570788103982,\n \"acc_norm\": 0.23687150837988827,\n\ \ \"acc_norm_stderr\": 0.014219570788103982\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.24836601307189543,\n \"acc_stderr\": 0.024739981355113596,\n\ \ \"acc_norm\": 0.24836601307189543,\n \"acc_norm_stderr\": 0.024739981355113596\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2057877813504823,\n\ \ \"acc_stderr\": 0.022961339906764244,\n \"acc_norm\": 0.2057877813504823,\n\ \ \"acc_norm_stderr\": 0.022961339906764244\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2839506172839506,\n \"acc_stderr\": 0.025089478523765127,\n\ \ \"acc_norm\": 0.2839506172839506,\n \"acc_norm_stderr\": 0.025089478523765127\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.2553191489361702,\n \"acc_stderr\": 0.026011992930902,\n \ \ \"acc_norm\": 0.2553191489361702,\n \"acc_norm_stderr\": 0.026011992930902\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.24902216427640156,\n\ \ \"acc_stderr\": 0.01104489226404077,\n \"acc_norm\": 0.24902216427640156,\n\ \ \"acc_norm_stderr\": 0.01104489226404077\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.2757352941176471,\n \"acc_stderr\": 0.027146271936625166,\n\ \ \"acc_norm\": 0.2757352941176471,\n \"acc_norm_stderr\": 0.027146271936625166\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.27941176470588236,\n \"acc_stderr\": 0.01815287105153882,\n \ \ \"acc_norm\": 0.27941176470588236,\n \"acc_norm_stderr\": 0.01815287105153882\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.23636363636363636,\n\ \ \"acc_stderr\": 0.04069306319721376,\n \"acc_norm\": 0.23636363636363636,\n\ \ \"acc_norm_stderr\": 0.04069306319721376\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.19591836734693877,\n \"acc_stderr\": 0.025409301953225678,\n\ \ \"acc_norm\": 0.19591836734693877,\n \"acc_norm_stderr\": 0.025409301953225678\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.263681592039801,\n\ \ \"acc_stderr\": 0.031157150869355582,\n \"acc_norm\": 0.263681592039801,\n\ \ \"acc_norm_stderr\": 0.031157150869355582\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.28313253012048195,\n\ \ \"acc_stderr\": 0.03507295431370519,\n \"acc_norm\": 0.28313253012048195,\n\ \ \"acc_norm_stderr\": 0.03507295431370519\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.30409356725146197,\n \"acc_stderr\": 0.03528211258245232,\n\ \ \"acc_norm\": 0.30409356725146197,\n \"acc_norm_stderr\": 0.03528211258245232\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.25458996328029376,\n\ \ \"mc1_stderr\": 0.015250117079156494,\n \"mc2\": 0.41268090479367026,\n\ \ \"mc2_stderr\": 0.015430187488430076\n }\n}\n```" repo_url: https://huggingface.co/KnutJaegersberg/galactica-orca-wizardlm-1.3b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|arc:challenge\|25_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hellaswag\|10_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:33:13.422388.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:33:13.422388.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_27T10_33_13.422388 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-27T10:33:13.422388.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-27T10:33:13.422388.parquet' - config_name: results data_files: - split: 2023_07_27T10_33_13.422388 path: - results_2023-07-27T10:33:13.422388.parquet - split: latest path: - results_2023-07-27T10:33:13.422388.parquet --- # Dataset Card for Evaluation run of KnutJaegersberg/galactica-orca-wizardlm-1.3b ## Dataset Description - Homepage: - Repository: https://huggingface.co/KnutJaegersberg/galactica-orca-wizardlm-1.3b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [KnutJaegersberg/galactica-orca-wizardlm-1.3b](https://huggingface.co/KnutJaegersberg/galactica-orca-wizardlm-1.3b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_KnutJaegersberg__galactica-orca-wizardlm-1.3b", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-07-27T10:33:13.422388](https://huggingface.co/datasets/open-llm-leaderboard/details_KnutJaegersberg__galactica-orca-wizardlm-1.3b/blob/main/results_2023-07-27T10%3A33%3A13.422388.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2607167828475717, "acc_stderr": 0.031890976655530354, "acc_norm": 0.2619942427603414, "acc_norm_stderr": 0.03190140774792886, "mc1": 0.25458996328029376, "mc1_stderr": 0.015250117079156494, "mc2": 0.41268090479367026, "mc2_stderr": 0.015430187488430076 }, "harness\|arc:challenge\|25": { "acc": 0.27303754266211605, "acc_stderr": 0.013019332762635727, "acc_norm": 0.30887372013651876, "acc_norm_stderr": 0.013501770929344004 }, "harness\|hellaswag\|10": { "acc": 0.32065325632344155, "acc_stderr": 0.004657738398900916, "acc_norm": 0.3601872137024497, "acc_norm_stderr": 0.004790734683704583 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2814814814814815, "acc_stderr": 0.038850042458002526, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.038850042458002526 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.24342105263157895, "acc_stderr": 0.034923496688842384, "acc_norm": 0.24342105263157895, "acc_norm_stderr": 0.034923496688842384 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.26037735849056604, "acc_stderr": 0.027008766090708104, "acc_norm": 0.26037735849056604, "acc_norm_stderr": 0.027008766090708104 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.03942082639927213, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.03942082639927213 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.17, "acc_stderr": 0.03775251680686371, "acc_norm": 0.17, "acc_norm_stderr": 0.03775251680686371 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.19, "acc_stderr": 0.03942772444036623, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036623 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.2774566473988439, "acc_stderr": 0.03414014007044036, "acc_norm": 0.2774566473988439, "acc_norm_stderr": 0.03414014007044036 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237655, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237655 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102963, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102963 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2543859649122807, "acc_stderr": 0.040969851398436716, "acc_norm": 0.2543859649122807, "acc_norm_stderr": 0.040969851398436716 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.3310344827586207, "acc_stderr": 0.03921545312467122, "acc_norm": 0.3310344827586207, "acc_norm_stderr": 0.03921545312467122 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2830687830687831, "acc_stderr": 0.023201392938194974, "acc_norm": 0.2830687830687831, "acc_norm_stderr": 0.023201392938194974 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.19047619047619047, "acc_stderr": 0.035122074123020534, "acc_norm": 0.19047619047619047, "acc_norm_stderr": 0.035122074123020534 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.2161290322580645, "acc_stderr": 0.02341529343356852, "acc_norm": 0.2161290322580645, "acc_norm_stderr": 0.02341529343356852 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.23645320197044334, "acc_stderr": 0.029896114291733552, "acc_norm": 0.23645320197044334, "acc_norm_stderr": 0.029896114291733552 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.23030303030303031, "acc_stderr": 0.03287666758603489, "acc_norm": 0.23030303030303031, "acc_norm_stderr": 0.03287666758603489 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.20707070707070707, "acc_stderr": 0.028869778460267063, "acc_norm": 0.20707070707070707, "acc_norm_stderr": 0.028869778460267063 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.22279792746113988, "acc_stderr": 0.03003114797764154, "acc_norm": 0.22279792746113988, "acc_norm_stderr": 0.03003114797764154 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.31794871794871793, "acc_stderr": 0.023610884308927865, "acc_norm": 0.31794871794871793, "acc_norm_stderr": 0.023610884308927865 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.027309140588230182, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.027309140588230182 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.23529411764705882, "acc_stderr": 0.027553614467863804, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.027553614467863804 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.24503311258278146, "acc_stderr": 0.03511807571804724, "acc_norm": 0.24503311258278146, "acc_norm_stderr": 0.03511807571804724 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.25137614678899084, "acc_stderr": 0.018599206360287415, "acc_norm": 0.25137614678899084, "acc_norm_stderr": 0.018599206360287415 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.30092592592592593, "acc_stderr": 0.03128039084329883, "acc_norm": 0.30092592592592593, "acc_norm_stderr": 0.03128039084329883 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.2549019607843137, "acc_stderr": 0.030587591351604246, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.030587591351604246 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.32286995515695066, "acc_stderr": 0.03138147637575498, "acc_norm": 0.32286995515695066, "acc_norm_stderr": 0.03138147637575498 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.183206106870229, "acc_stderr": 0.033927709264947335, "acc_norm": 0.183206106870229, "acc_norm_stderr": 0.033927709264947335 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.24793388429752067, "acc_stderr": 0.03941897526516301, "acc_norm": 0.24793388429752067, "acc_norm_stderr": 0.03941897526516301 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.2147239263803681, "acc_stderr": 0.032262193772867744, "acc_norm": 0.2147239263803681, "acc_norm_stderr": 0.032262193772867744 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.25892857142857145, "acc_stderr": 0.04157751539865629, "acc_norm": 0.25892857142857145, "acc_norm_stderr": 0.04157751539865629 }, "harness\|hendrycksTest-management\|5": { "acc": 0.32038834951456313, "acc_stderr": 0.0462028408228004, "acc_norm": 0.32038834951456313, "acc_norm_stderr": 0.0462028408228004 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.02934311479809447, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.02934311479809447 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.24393358876117496, "acc_stderr": 0.015357212665829468, "acc_norm": 0.24393358876117496, "acc_norm_stderr": 0.015357212665829468 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.30057803468208094, "acc_stderr": 0.02468531686725781, "acc_norm": 0.30057803468208094, "acc_norm_stderr": 0.02468531686725781 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23687150837988827, "acc_stderr": 0.014219570788103982, "acc_norm": 0.23687150837988827, "acc_norm_stderr": 0.014219570788103982 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.24836601307189543, "acc_stderr": 0.024739981355113596, "acc_norm": 0.24836601307189543, "acc_norm_stderr": 0.024739981355113596 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.2057877813504823, "acc_stderr": 0.022961339906764244, "acc_norm": 0.2057877813504823, "acc_norm_stderr": 0.022961339906764244 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2839506172839506, "acc_stderr": 0.025089478523765127, "acc_norm": 0.2839506172839506, "acc_norm_stderr": 0.025089478523765127 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.2553191489361702, "acc_stderr": 0.026011992930902, "acc_norm": 0.2553191489361702, "acc_norm_stderr": 0.026011992930902 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.24902216427640156, "acc_stderr": 0.01104489226404077, "acc_norm": 0.24902216427640156, "acc_norm_stderr": 0.01104489226404077 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.2757352941176471, "acc_stderr": 0.027146271936625166, "acc_norm": 0.2757352941176471, "acc_norm_stderr": 0.027146271936625166 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.27941176470588236, "acc_stderr": 0.01815287105153882, "acc_norm": 0.27941176470588236, "acc_norm_stderr": 0.01815287105153882 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.23636363636363636, "acc_stderr": 0.04069306319721376, "acc_norm": 0.23636363636363636, "acc_norm_stderr": 0.04069306319721376 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.19591836734693877, "acc_stderr": 0.025409301953225678, "acc_norm": 0.19591836734693877, "acc_norm_stderr": 0.025409301953225678 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.263681592039801, "acc_stderr": 0.031157150869355582, "acc_norm": 0.263681592039801, "acc_norm_stderr": 0.031157150869355582 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370519, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370519 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.30409356725146197, "acc_stderr": 0.03528211258245232, "acc_norm": 0.30409356725146197, "acc_norm_stderr": 0.03528211258245232 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.25458996328029376, "mc1_stderr": 0.015250117079156494, "mc2": 0.41268090479367026, "mc2_stderr": 0.015430187488430076 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7292371988296509, -0.8717400431632996, 0.24779966473579407, 0.18508610129356384, -0.13717754185199738, -0.05952426418662071, 0.03769495710730553, -0.2358817160129547, 0.593139111995697, -0.02724907360970974, -0.4913661479949951, -0.6945188641548157, -0.40972891449928284, 0.23369193077087402, -0.018186913803219795, 0.8281329870223999, -0.1770673543214798, -0.08192584663629532, 0.0986834391951561, -0.0262930728495121, -0.2557164430618286, -0.3594233989715576, -0.5232885479927063, 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open-llm-leaderboard/details_nicholasKluge__Aira-Instruct-PT-1B7	open-llm-leaderboard	2023-08-27T12:31:57Z	250	0	[ "region:us" ]	null	2023-08-18T11:16:22Z	--- pretty_name: Evaluation run of nicholasKluge/Aira-Instruct-PT-1B7 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [nicholasKluge/Aira-Instruct-PT-1B7](https://huggingface.co/nicholasKluge/Aira-Instruct-PT-1B7)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_nicholasKluge__Aira-Instruct-PT-1B7\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-09T20:59:57.404122](https://huggingface.co/datasets/open-llm-leaderboard/details_nicholasKluge__Aira-Instruct-PT-1B7/blob/main/results_2023-08-09T20%3A59%3A57.404122.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2495089085448401,\n\ \ \"acc_stderr\": 0.03135286921160441,\n \"acc_norm\": 0.2508452551647926,\n\ \ \"acc_norm_stderr\": 0.03137437179137316,\n \"mc1\": 0.22888616891064872,\n\ \ \"mc1_stderr\": 0.014706994909055028,\n \"mc2\": 0.4595409979303444,\n\ \ \"mc2_stderr\": 0.01663090921738331\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.2030716723549488,\n \"acc_stderr\": 0.011755899303705583,\n\ \ \"acc_norm\": 0.2687713310580205,\n \"acc_norm_stderr\": 0.012955065963710672\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.25941047600079664,\n\ \ \"acc_stderr\": 0.004374153847826759,\n \"acc_norm\": 0.2725552678749253,\n\ \ \"acc_norm_stderr\": 0.004443639394177424\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04072314811876837,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04072314811876837\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.19736842105263158,\n \"acc_stderr\": 0.03238981601699397,\n\ \ \"acc_norm\": 0.19736842105263158,\n \"acc_norm_stderr\": 0.03238981601699397\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.23,\n\ \ \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.23,\n \ \ \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.26037735849056604,\n \"acc_stderr\": 0.027008766090708087,\n\ \ \"acc_norm\": 0.26037735849056604,\n \"acc_norm_stderr\": 0.027008766090708087\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2361111111111111,\n\ \ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.2361111111111111,\n\ \ \"acc_norm_stderr\": 0.03551446610810826\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.17,\n \"acc_stderr\": 0.03775251680686371,\n \ \ \"acc_norm\": 0.17,\n \"acc_norm_stderr\": 0.03775251680686371\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \"acc_norm\": 0.33,\n\ \ \"acc_norm_stderr\": 0.04725815626252604\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.0416333199893227,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.0416333199893227\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.21965317919075145,\n\ \ \"acc_stderr\": 0.031568093627031744,\n \"acc_norm\": 0.21965317919075145,\n\ \ \"acc_norm_stderr\": 0.031568093627031744\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.19,\n \"acc_stderr\": 0.039427724440366234,\n \"acc_norm\": 0.19,\n\ \ \"acc_norm_stderr\": 0.039427724440366234\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.24680851063829787,\n \"acc_stderr\": 0.028185441301234102,\n\ \ \"acc_norm\": 0.24680851063829787,\n \"acc_norm_stderr\": 0.028185441301234102\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.24561403508771928,\n\ \ \"acc_stderr\": 0.04049339297748141,\n \"acc_norm\": 0.24561403508771928,\n\ \ \"acc_norm_stderr\": 0.04049339297748141\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2620689655172414,\n \"acc_stderr\": 0.036646663372252565,\n\ \ \"acc_norm\": 0.2620689655172414,\n \"acc_norm_stderr\": 0.036646663372252565\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643898,\n \"\ acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643898\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.16666666666666666,\n\ \ \"acc_stderr\": 0.03333333333333337,\n \"acc_norm\": 0.16666666666666666,\n\ \ \"acc_norm_stderr\": 0.03333333333333337\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.19,\n \"acc_stderr\": 0.039427724440366234,\n \ \ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.039427724440366234\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.2870967741935484,\n \"acc_stderr\": 0.025736542745594525,\n \"\ acc_norm\": 0.2870967741935484,\n \"acc_norm_stderr\": 0.025736542745594525\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.3054187192118227,\n \"acc_stderr\": 0.03240661565868408,\n \"\ acc_norm\": 0.3054187192118227,\n \"acc_norm_stderr\": 0.03240661565868408\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\"\ : 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.24848484848484848,\n \"acc_stderr\": 0.033744026441394036,\n\ \ \"acc_norm\": 0.24848484848484848,\n \"acc_norm_stderr\": 0.033744026441394036\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.2676767676767677,\n \"acc_stderr\": 0.03154449888270286,\n \"\ acc_norm\": 0.2676767676767677,\n \"acc_norm_stderr\": 0.03154449888270286\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.22797927461139897,\n \"acc_stderr\": 0.03027690994517826,\n\ \ \"acc_norm\": 0.22797927461139897,\n \"acc_norm_stderr\": 0.03027690994517826\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.2128205128205128,\n \"acc_stderr\": 0.020752423722128013,\n\ \ \"acc_norm\": 0.2128205128205128,\n \"acc_norm_stderr\": 0.020752423722128013\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.24789915966386555,\n \"acc_stderr\": 0.028047967224176892,\n\ \ \"acc_norm\": 0.24789915966386555,\n \"acc_norm_stderr\": 0.028047967224176892\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.23841059602649006,\n \"acc_stderr\": 0.0347918557259966,\n \"\ acc_norm\": 0.23841059602649006,\n \"acc_norm_stderr\": 0.0347918557259966\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.344954128440367,\n \"acc_stderr\": 0.020380605405066966,\n \"\ acc_norm\": 0.344954128440367,\n \"acc_norm_stderr\": 0.020380605405066966\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.3472222222222222,\n \"acc_stderr\": 0.032468872436376486,\n \"\ acc_norm\": 0.3472222222222222,\n \"acc_norm_stderr\": 0.032468872436376486\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.22058823529411764,\n \"acc_stderr\": 0.029102254389674082,\n \"\ acc_norm\": 0.22058823529411764,\n \"acc_norm_stderr\": 0.029102254389674082\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.23628691983122363,\n \"acc_stderr\": 0.027652153144159263,\n \ \ \"acc_norm\": 0.23628691983122363,\n \"acc_norm_stderr\": 0.027652153144159263\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.25112107623318386,\n\ \ \"acc_stderr\": 0.029105220833224615,\n \"acc_norm\": 0.25112107623318386,\n\ \ \"acc_norm_stderr\": 0.029105220833224615\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.22900763358778625,\n \"acc_stderr\": 0.036853466317118506,\n\ \ \"acc_norm\": 0.22900763358778625,\n \"acc_norm_stderr\": 0.036853466317118506\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.21487603305785125,\n \"acc_stderr\": 0.03749492448709698,\n \"\ acc_norm\": 0.21487603305785125,\n \"acc_norm_stderr\": 0.03749492448709698\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.2962962962962963,\n\ \ \"acc_stderr\": 0.044143436668549335,\n \"acc_norm\": 0.2962962962962963,\n\ \ \"acc_norm_stderr\": 0.044143436668549335\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.3006134969325153,\n \"acc_stderr\": 0.03602511318806771,\n\ \ \"acc_norm\": 0.3006134969325153,\n \"acc_norm_stderr\": 0.03602511318806771\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.25892857142857145,\n\ \ \"acc_stderr\": 0.04157751539865629,\n \"acc_norm\": 0.25892857142857145,\n\ \ \"acc_norm_stderr\": 0.04157751539865629\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.20388349514563106,\n \"acc_stderr\": 0.03989139859531773,\n\ \ \"acc_norm\": 0.20388349514563106,\n \"acc_norm_stderr\": 0.03989139859531773\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.23931623931623933,\n\ \ \"acc_stderr\": 0.027951826808924333,\n \"acc_norm\": 0.23931623931623933,\n\ \ \"acc_norm_stderr\": 0.027951826808924333\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.26436781609195403,\n\ \ \"acc_stderr\": 0.01576998484069052,\n \"acc_norm\": 0.26436781609195403,\n\ \ \"acc_norm_stderr\": 0.01576998484069052\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.26011560693641617,\n \"acc_stderr\": 0.02361867831006937,\n\ \ \"acc_norm\": 0.26011560693641617,\n \"acc_norm_stderr\": 0.02361867831006937\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24692737430167597,\n\ \ \"acc_stderr\": 0.014422292204808835,\n \"acc_norm\": 0.24692737430167597,\n\ \ \"acc_norm_stderr\": 0.014422292204808835\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.02392915551735129,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.02392915551735129\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.21543408360128619,\n\ \ \"acc_stderr\": 0.023350225475471425,\n \"acc_norm\": 0.21543408360128619,\n\ \ \"acc_norm_stderr\": 0.023350225475471425\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.23148148148148148,\n \"acc_stderr\": 0.02346842983245114,\n\ \ \"acc_norm\": 0.23148148148148148,\n \"acc_norm_stderr\": 0.02346842983245114\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.25886524822695034,\n \"acc_stderr\": 0.026129572527180844,\n \ \ \"acc_norm\": 0.25886524822695034,\n \"acc_norm_stderr\": 0.026129572527180844\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.24511082138200782,\n\ \ \"acc_stderr\": 0.010986307870045517,\n \"acc_norm\": 0.24511082138200782,\n\ \ \"acc_norm_stderr\": 0.010986307870045517\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.35661764705882354,\n \"acc_stderr\": 0.029097209568411952,\n\ \ \"acc_norm\": 0.35661764705882354,\n \"acc_norm_stderr\": 0.029097209568411952\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.25163398692810457,\n \"acc_stderr\": 0.017555818091322263,\n \ \ \"acc_norm\": 0.25163398692810457,\n \"acc_norm_stderr\": 0.017555818091322263\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.20909090909090908,\n\ \ \"acc_stderr\": 0.03895091015724138,\n \"acc_norm\": 0.20909090909090908,\n\ \ \"acc_norm_stderr\": 0.03895091015724138\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.24489795918367346,\n \"acc_stderr\": 0.027529637440174934,\n\ \ \"acc_norm\": 0.24489795918367346,\n \"acc_norm_stderr\": 0.027529637440174934\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.2537313432835821,\n\ \ \"acc_stderr\": 0.03076944496729601,\n \"acc_norm\": 0.2537313432835821,\n\ \ \"acc_norm_stderr\": 0.03076944496729601\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036843,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036843\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.28313253012048195,\n\ \ \"acc_stderr\": 0.03507295431370518,\n \"acc_norm\": 0.28313253012048195,\n\ \ \"acc_norm_stderr\": 0.03507295431370518\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.2631578947368421,\n \"acc_stderr\": 0.033773102522091945,\n\ \ \"acc_norm\": 0.2631578947368421,\n \"acc_norm_stderr\": 0.033773102522091945\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.22888616891064872,\n\ \ \"mc1_stderr\": 0.014706994909055028,\n \"mc2\": 0.4595409979303444,\n\ \ \"mc2_stderr\": 0.01663090921738331\n }\n}\n```" repo_url: https://huggingface.co/nicholasKluge/Aira-Instruct-PT-1B7 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|arc:challenge\|25_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hellaswag\|10_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T20:59:57.404122.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T20:59:57.404122.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T20_59_57.404122 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T20:59:57.404122.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T20:59:57.404122.parquet' - config_name: results data_files: - split: 2023_08_09T20_59_57.404122 path: - results_2023-08-09T20:59:57.404122.parquet - split: latest path: - results_2023-08-09T20:59:57.404122.parquet --- # Dataset Card for Evaluation run of nicholasKluge/Aira-Instruct-PT-1B7 ## Dataset Description - Homepage: - Repository: https://huggingface.co/nicholasKluge/Aira-Instruct-PT-1B7 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [nicholasKluge/Aira-Instruct-PT-1B7](https://huggingface.co/nicholasKluge/Aira-Instruct-PT-1B7) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_nicholasKluge__Aira-Instruct-PT-1B7", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-09T20:59:57.404122](https://huggingface.co/datasets/open-llm-leaderboard/details_nicholasKluge__Aira-Instruct-PT-1B7/blob/main/results_2023-08-09T20%3A59%3A57.404122.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2495089085448401, "acc_stderr": 0.03135286921160441, "acc_norm": 0.2508452551647926, "acc_norm_stderr": 0.03137437179137316, "mc1": 0.22888616891064872, "mc1_stderr": 0.014706994909055028, "mc2": 0.4595409979303444, "mc2_stderr": 0.01663090921738331 }, "harness\|arc:challenge\|25": { "acc": 0.2030716723549488, "acc_stderr": 0.011755899303705583, "acc_norm": 0.2687713310580205, "acc_norm_stderr": 0.012955065963710672 }, "harness\|hellaswag\|10": { "acc": 0.25941047600079664, "acc_stderr": 0.004374153847826759, "acc_norm": 0.2725552678749253, "acc_norm_stderr": 0.004443639394177424 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04072314811876837, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04072314811876837 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.19736842105263158, "acc_stderr": 0.03238981601699397, "acc_norm": 0.19736842105263158, "acc_norm_stderr": 0.03238981601699397 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.26037735849056604, "acc_stderr": 0.027008766090708087, "acc_norm": 0.26037735849056604, "acc_norm_stderr": 0.027008766090708087 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2361111111111111, "acc_stderr": 0.03551446610810826, "acc_norm": 0.2361111111111111, "acc_norm_stderr": 0.03551446610810826 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.17, "acc_stderr": 0.03775251680686371, "acc_norm": 0.17, "acc_norm_stderr": 0.03775251680686371 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.22, "acc_stderr": 0.0416333199893227, "acc_norm": 0.22, "acc_norm_stderr": 0.0416333199893227 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.21965317919075145, "acc_stderr": 0.031568093627031744, "acc_norm": 0.21965317919075145, "acc_norm_stderr": 0.031568093627031744 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.19, "acc_stderr": 0.039427724440366234, "acc_norm": 0.19, "acc_norm_stderr": 0.039427724440366234 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.24680851063829787, "acc_stderr": 0.028185441301234102, "acc_norm": 0.24680851063829787, "acc_norm_stderr": 0.028185441301234102 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.24561403508771928, "acc_stderr": 0.04049339297748141, "acc_norm": 0.24561403508771928, "acc_norm_stderr": 0.04049339297748141 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2620689655172414, "acc_stderr": 0.036646663372252565, "acc_norm": 0.2620689655172414, "acc_norm_stderr": 0.036646663372252565 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.25132275132275134, "acc_stderr": 0.022340482339643898, "acc_norm": 0.25132275132275134, "acc_norm_stderr": 0.022340482339643898 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.16666666666666666, "acc_stderr": 0.03333333333333337, "acc_norm": 0.16666666666666666, "acc_norm_stderr": 0.03333333333333337 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.19, "acc_stderr": 0.039427724440366234, "acc_norm": 0.19, "acc_norm_stderr": 0.039427724440366234 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.2870967741935484, "acc_stderr": 0.025736542745594525, "acc_norm": 0.2870967741935484, "acc_norm_stderr": 0.025736542745594525 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3054187192118227, "acc_stderr": 0.03240661565868408, "acc_norm": 0.3054187192118227, "acc_norm_stderr": 0.03240661565868408 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.24848484848484848, "acc_stderr": 0.033744026441394036, "acc_norm": 0.24848484848484848, "acc_norm_stderr": 0.033744026441394036 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.2676767676767677, "acc_stderr": 0.03154449888270286, "acc_norm": 0.2676767676767677, "acc_norm_stderr": 0.03154449888270286 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.22797927461139897, "acc_stderr": 0.03027690994517826, "acc_norm": 0.22797927461139897, "acc_norm_stderr": 0.03027690994517826 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.2128205128205128, "acc_stderr": 0.020752423722128013, "acc_norm": 0.2128205128205128, "acc_norm_stderr": 0.020752423722128013 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340492, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340492 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.24789915966386555, "acc_stderr": 0.028047967224176892, "acc_norm": 0.24789915966386555, "acc_norm_stderr": 0.028047967224176892 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.23841059602649006, "acc_stderr": 0.0347918557259966, "acc_norm": 0.23841059602649006, "acc_norm_stderr": 0.0347918557259966 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.344954128440367, "acc_stderr": 0.020380605405066966, "acc_norm": 0.344954128440367, "acc_norm_stderr": 0.020380605405066966 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.3472222222222222, "acc_stderr": 0.032468872436376486, "acc_norm": 0.3472222222222222, "acc_norm_stderr": 0.032468872436376486 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.22058823529411764, "acc_stderr": 0.029102254389674082, "acc_norm": 0.22058823529411764, "acc_norm_stderr": 0.029102254389674082 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.23628691983122363, "acc_stderr": 0.027652153144159263, "acc_norm": 0.23628691983122363, "acc_norm_stderr": 0.027652153144159263 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.25112107623318386, "acc_stderr": 0.029105220833224615, "acc_norm": 0.25112107623318386, "acc_norm_stderr": 0.029105220833224615 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.22900763358778625, "acc_stderr": 0.036853466317118506, "acc_norm": 0.22900763358778625, "acc_norm_stderr": 0.036853466317118506 }, "harness\|hendrycksTest-international_law\|5": 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"harness\|hendrycksTest-world_religions\|5": { "acc": 0.2631578947368421, "acc_stderr": 0.033773102522091945, "acc_norm": 0.2631578947368421, "acc_norm_stderr": 0.033773102522091945 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.22888616891064872, "mc1_stderr": 0.014706994909055028, "mc2": 0.4595409979303444, "mc2_stderr": 0.01663090921738331 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7065203785896301, -0.838286817073822, 0.2596175968647003, 0.18761606514453888, -0.13984791934490204, -0.07524684071540833, 0.05365454778075218, -0.199055016040802, 0.5983582735061646, -0.09692634642124176, -0.4821557104587555, -0.6404532194137573, -0.45486533641815186, 0.19084309041500092, -0.05910910665988922, 0.7733116149902344, -0.1990012675523758, -0.13722455501556396, 0.10387107729911804, -0.009146137163043022, -0.24387884140014648, -0.3718443214893341, -0.468352347612381, 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open-llm-leaderboard/details_TigerResearch__tigerbot-13b-base	open-llm-leaderboard	2023-10-23T13:13:56Z	250	0	[ "region:us" ]	null	2023-10-04T03:31:37Z	--- pretty_name: Evaluation run of TigerResearch/tigerbot-13b-base dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TigerResearch/tigerbot-13b-base](https://huggingface.co/TigerResearch/tigerbot-13b-base)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TigerResearch__tigerbot-13b-base\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-23T13:13:43.194689](https://huggingface.co/datasets/open-llm-leaderboard/details_TigerResearch__tigerbot-13b-base/blob/main/results_2023-10-23T13-13-43.194689.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.40436241610738255,\n\ \ \"em_stderr\": 0.005025925994007285,\n \"f1\": 0.4420973154362425,\n\ \ \"f1_stderr\": 0.00490507412731345,\n \"acc\": 0.46019322954595365,\n\ \ \"acc_stderr\": 0.011266954073591217\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.40436241610738255,\n \"em_stderr\": 0.005025925994007285,\n\ \ \"f1\": 0.4420973154362425,\n \"f1_stderr\": 0.00490507412731345\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.17058377558756635,\n \ \ \"acc_stderr\": 0.010360898504733297\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.749802683504341,\n \"acc_stderr\": 0.012173009642449138\n\ \ }\n}\n```" repo_url: https://huggingface.co/TigerResearch/tigerbot-13b-base leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|arc:challenge\|25_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-04T03-31-16.960858.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_23T13_13_43.194689 path: - '/details_harness\|drop\|3_2023-10-23T13-13-43.194689.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-23T13-13-43.194689.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_23T13_13_43.194689 path: - '/details_harness\|gsm8k\|5_2023-10-23T13-13-43.194689.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-23T13-13-43.194689.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hellaswag\|10_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T03-31-16.960858.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T03-31-16.960858.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_04T03_31_16.960858 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-04T03-31-16.960858.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-04T03-31-16.960858.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_23T13_13_43.194689 path: - '/details_harness\|winogrande\|5_2023-10-23T13-13-43.194689.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-23T13-13-43.194689.parquet' - config_name: results data_files: - split: 2023_10_04T03_31_16.960858 path: - results_2023-10-04T03-31-16.960858.parquet - split: 2023_10_23T13_13_43.194689 path: - results_2023-10-23T13-13-43.194689.parquet - split: latest path: - results_2023-10-23T13-13-43.194689.parquet --- # Dataset Card for Evaluation run of TigerResearch/tigerbot-13b-base ## Dataset Description - Homepage: - Repository: https://huggingface.co/TigerResearch/tigerbot-13b-base - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [TigerResearch/tigerbot-13b-base](https://huggingface.co/TigerResearch/tigerbot-13b-base) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TigerResearch__tigerbot-13b-base", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-23T13:13:43.194689](https://huggingface.co/datasets/open-llm-leaderboard/details_TigerResearch__tigerbot-13b-base/blob/main/results_2023-10-23T13-13-43.194689.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.40436241610738255, "em_stderr": 0.005025925994007285, "f1": 0.4420973154362425, "f1_stderr": 0.00490507412731345, "acc": 0.46019322954595365, "acc_stderr": 0.011266954073591217 }, "harness\|drop\|3": { "em": 0.40436241610738255, "em_stderr": 0.005025925994007285, "f1": 0.4420973154362425, "f1_stderr": 0.00490507412731345 }, "harness\|gsm8k\|5": { "acc": 0.17058377558756635, "acc_stderr": 0.010360898504733297 }, "harness\|winogrande\|5": { "acc": 0.749802683504341, "acc_stderr": 0.012173009642449138 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.43842843174934387, -0.603244960308075, 0.1632796674966812, 0.2542705833911896, -0.2380407750606537, 0.1626405119895935, -0.37305140495300293, -0.16778837144374847, 0.455076664686203, 0.566891610622406, -0.7322523593902588, -0.908632218837738, -0.5639103651046753, 0.21271401643753052, -0.1016993448138237, 1.1542977094650269, -0.13779956102371216, -0.2864857614040375, 0.05646616965532303, -0.3568325340747833, -0.3353005349636078, -0.5182200074195862, -0.5394997596740723, 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clarin-pl/nkjp-pos	clarin-pl	2023-01-30T22:53:57Z	249	1	[ "task_categories:other", "task_ids:part-of-speech", "annotations_creators:expert-generated", "language_creators:other", "multilinguality:monolingual", "size_categories:unknown", "source_datasets:original", "language:pl", "license:gpl-3.0", "structure-prediction", "region:us" ]	[ "other" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - other language: - pl license: - gpl-3.0 multilinguality: - monolingual size_categories: - unknown source_datasets: - original task_categories: - other task_ids: - part-of-speech pretty_name: nkjp-pos tags: - structure-prediction --- # nkjp-pos ## Description NKJP-POS is a part the National Corpus of Polish (Narodowy Korpus Języka Polskiego). Its objective is part-of-speech tagging, e.g. nouns, verbs, adjectives, adverbs, etc. During the creation of corpus, texts of were annotated by humans from various sources, covering many domains and genres. ## Tasks (input, output and metrics) Part-of-speech tagging (POS tagging) - tagging words in text with their corresponding part of speech. Input ('tokens' column): sequence of tokens Output ('pos_tags' column): sequence of predicted tokens’ classes (35 possible classes, described in detail in the annotation guidelines) Measurements: F1-score (seqeval) Example: Input: `['Zarejestruj', 'się', 'jako', 'bezrobotny', '.']` Input (translated by DeepL): `Register as unemployed.` Output: `['impt', 'qub', 'conj', 'subst', 'interp']` ## Data splits \| Subset \| Cardinality (sentences) \| \| ----------- \| ----------------------: \| \| train \| 78219 \| \| dev \| 0 \| \| test \| 7444 \| ## Class distribution \| Class \| train \| dev \| test \| \|:--------\|--------:\|------:\|--------:\| \| subst \| 0.27345 \| - \| 0.27656 \| \| interp \| 0.18101 \| - \| 0.17944 \| \| adj \| 0.10611 \| - \| 0.10919 \| \| prep \| 0.09567 \| - \| 0.09547 \| \| qub \| 0.05670 \| - \| 0.05491 \| \| fin \| 0.04939 \| - \| 0.04648 \| \| praet \| 0.04409 \| - \| 0.04348 \| \| conj \| 0.03711 \| - \| 0.03724 \| \| adv \| 0.03512 \| - \| 0.03333 \| \| inf \| 0.01591 \| - \| 0.01547 \| \| comp \| 0.01476 \| - \| 0.01439 \| \| num \| 0.01322 \| - \| 0.01436 \| \| ppron3 \| 0.01111 \| - \| 0.01018 \| \| ppas \| 0.01086 \| - \| 0.01085 \| \| ger \| 0.00961 \| - \| 0.01050 \| \| brev \| 0.00856 \| - \| 0.01181 \| \| ppron12 \| 0.00670 \| - \| 0.00665 \| \| aglt \| 0.00629 \| - \| 0.00602 \| \| pred \| 0.00539 \| - \| 0.00540 \| \| pact \| 0.00454 \| - \| 0.00452 \| \| bedzie \| 0.00229 \| - \| 0.00243 \| \| pcon \| 0.00218 \| - \| 0.00189 \| \| impt \| 0.00203 \| - \| 0.00226 \| \| siebie \| 0.00177 \| - \| 0.00158 \| \| imps \| 0.00174 \| - \| 0.00177 \| \| interj \| 0.00131 \| - \| 0.00102 \| \| xxx \| 0.00070 \| - \| 0.00048 \| \| adjp \| 0.00069 \| - \| 0.00065 \| \| winien \| 0.00068 \| - \| 0.00057 \| \| adja \| 0.00048 \| - \| 0.00058 \| \| pant \| 0.00012 \| - \| 0.00018 \| \| burk \| 0.00011 \| - \| 0.00006 \| \| numcol \| 0.00011 \| - \| 0.00013 \| \| depr \| 0.00010 \| - \| 0.00004 \| \| adjc \| 0.00007 \| - \| 0.00008 \| ## Citation ``` @book{przepiorkowski_narodowy_2012, title = {Narodowy korpus języka polskiego}, isbn = {978-83-01-16700-4}, language = {pl}, publisher = {Wydawnictwo Naukowe PWN}, editor = {Przepiórkowski, Adam and Bańko, Mirosław and Górski, Rafał L. and Lewandowska-Tomaszczyk, Barbara}, year = {2012} } ``` ## License ``` GNU GPL v.3 ``` ## Links [HuggingFace](https://huggingface.co/datasets/clarin-pl/nkjp-pos) [Source](http://clip.ipipan.waw.pl/NationalCorpusOfPolish) [Paper](http://nkjp.pl/settings/papers/NKJP_ksiazka.pdf) ## Examples ### Loading ```python from pprint import pprint from datasets import load_dataset dataset = load_dataset("clarin-pl/nkjp-pos") pprint(dataset['train'][5000]) # {'id': '130-2-900005_morph_49.49-s', # 'pos_tags': [16, 4, 3, 30, 12, 18, 3, 16, 14, 6, 14, 26, 1, 30, 12], # 'tokens': ['Najwyraźniej', # 'źle', # 'ocenił', # 'odległość', # ',', # 'bo', # 'zderzył', # 'się', # 'z', # 'jadącą', # 'z', # 'naprzeciwka', # 'ciężarową', # 'scanią', # '.']} ``` ### Evaluation ```python import random from pprint import pprint from datasets import load_dataset, load_metric dataset = load_dataset("clarin-pl/nkjp-pos") references = dataset["test"]["pos_tags"] # generate random predictions predictions = [ [ random.randrange(dataset["train"].features["pos_tags"].feature.num_classes) for _ in range(len(labels)) ] for labels in references ] # transform to original names of labels references_named = [ [dataset["train"].features["pos_tags"].feature.names[label] for label in labels] for labels in references ] predictions_named = [ [dataset["train"].features["pos_tags"].feature.names[label] for label in labels] for labels in predictions ] # transform to BILOU scheme references_named = [ [f"U-{label}" if label != "O" else label for label in labels] for labels in references_named ] predictions_named = [ [f"U-{label}" if label != "O" else label for label in labels] for labels in predictions_named ] # utilise seqeval to evaluate seqeval = load_metric("seqeval") seqeval_score = seqeval.compute( predictions=predictions_named, references=references_named, scheme="BILOU", mode="strict", ) pprint(seqeval_score, depth=1) # {'adj': {...}, # 'adja': {...}, # 'adjc': {...}, # 'adjp': {...}, # 'adv': {...}, # 'aglt': {...}, # 'bedzie': {...}, # 'brev': {...}, # 'burk': {...}, # 'comp': {...}, # 'conj': {...}, # 'depr': {...}, # 'fin': {...}, # 'ger': {...}, # 'imps': {...}, # 'impt': {...}, # 'inf': {...}, # 'interj': {...}, # 'interp': {...}, # 'num': {...}, # 'numcol': {...}, # 'overall_accuracy': 0.027855061488566583, # 'overall_f1': 0.027855061488566583, # 'overall_precision': 0.027855061488566583, # 'overall_recall': 0.027855061488566583, # 'pact': {...}, # 'pant': {...}, # 'pcon': {...}, # 'ppas': {...}, # 'ppron12': {...}, # 'ppron3': {...}, # 'praet': {...}, # 'pred': {...}, # 'prep': {...}, # 'qub': {...}, # 'siebie': {...}, # 'subst': {...}, # 'winien': {...}, # 'xxx': {...}} ```	[ -0.6446857452392578, -0.4985079765319824, 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emre/Open_SLR108_Turkish_10_hours	emre	2022-12-06T21:00:45Z	249	3	[ "license:cc-by-4.0", "robust-speech-event", "arxiv:2103.16193", "region:us" ]	null	2022-03-02T23:29:22Z	--- license: cc-by-4.0 tags: - robust-speech-event datasets: - MediaSpeech --- MediaSpeech Identifier: SLR108 Summary: French, Arabic, Turkish and Spanish media speech datasets Category: Speech License: dataset is distributed under the Creative Commons Attribution 4.0 International License. About this resource: MediaSpeech is a dataset of French, Arabic, Turkish and Spanish media speech built with the purpose of testing Automated Speech Recognition (ASR) systems performance. The dataset contains 10 hours of speech for each language provided. The dataset consists of short speech segments automatically extracted from media videos available on YouTube and manually transcribed, with some pre- and post-processing. Baseline models and wav version of the dataset can be found in the following git repository: https://github.com/NTRLab/MediaSpeech @misc{mediaspeech2021, title={MediaSpeech: Multilanguage ASR Benchmark and Dataset}, author={Rostislav Kolobov and Olga Okhapkina and Olga Omelchishina, Andrey Platunov and Roman Bedyakin and Vyacheslav Moshkin and Dmitry Menshikov and Nikolay Mikhaylovskiy}, year={2021}, eprint={2103.16193}, archivePrefix={arXiv}, primaryClass={eess.AS} }	[ -0.6670159697532654, -0.2600639760494232, -0.07679396867752075, 0.36987611651420593, -0.20352283120155334, 0.11799617856740952, -0.32202547788619995, -0.07570701092481613, 0.33239802718162537, 0.42492830753326416, -0.8749402761459351, -0.499303936958313, -0.6220849752426147, 0.03255400061607361, -0.4202836751937866, 0.6885103583335876, 0.10139178484678268, 0.374255508184433, 0.4709506928920746, -0.7458655834197998, 0.10268367826938629, -0.1899341642856598, -0.504413902759552, -0.014993488788604736, 0.3948652446269989, 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enelpol/czywiesz	enelpol	2022-10-25T09:07:45Z	249	2	[ "task_categories:question-answering", "task_ids:open-domain-qa", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:pl", "license:unknown", "region:us" ]	[ "question-answering" ]	2022-03-02T23:29:22Z	--- language: - pl license: - unknown multilinguality: - monolingual pretty_name: Czywiesz size_categories: - 10K<n<100K source_datasets: - original task_categories: - question-answering task_ids: - open-domain-qa --- This is an extract of the original [Czywiesz](https://clarin-pl.eu/dspace/handle/11321/39) dataset. It contains the questions and the relevant Wikipedia passages in format compatible with DPR training objective. It may be used to train a passage retriever.	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anon8231489123/ShareGPT_Vicuna_unfiltered	anon8231489123	2023-04-12T05:23:59Z	249	610	[ "language:en", "license:apache-2.0", "region:us" ]	null	2023-04-02T05:30:31Z	--- license: apache-2.0 language: - en --- Further cleaning done. Please look through the dataset and ensure that I didn't miss anything. Update: Confirmed working method for training the model: https://huggingface.co/AlekseyKorshuk/vicuna-7b/discussions/4#64346c08ef6d5abefe42c12c Two choices: - Removes instances of "I'm sorry, but": https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split_no_imsorry.json - Has instances of "I'm sorry, but": https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split.json The choice is yours. The first dataset may go to far and remove valuable data. The second is better for when the AI asks for clarification, but it also may refuse to do stuff like browse the internet, which it actually may be able to do with certain langchain implementations. These are important things to think about before training. ~100k ShareGPT conversations narrowed down to 53k by: * Removing non-english conversations * Removing excessive unicode (indicative of Chinese or Korean text, usually) * Removing excessive repeated characters * Removing various instances "AI Moralizing". Conversations with these phrases were removed (and a few others that can't be mentioned here): "text-based AI language model", "domestic violence", "please refrain", "derogatory", "inappropriate", "offensive", "racism", "racist", "racial", "discriminate", "discriminatory", "discrimination", "sexist", "sexism", "unacceptable", "inclusive workplace", "lgbt", "morals", "ethics", "ethical", "legality", "illegal", "illegality", "hateful", "harmful", "it is never okay", "It is important to", "It's important to", "real-world consequences", "hate speech", "glorify", "not be appropriate", "supremacist", "extremist", "responsible AI", "AI principles", "AI assistant", "an AI language", "ableist", "hurtful", "gender stereotype", "gender inequality", "underrepresentation", "safe spaces", "gender-based", "inclusivity", "feminist", "feminism", "transgender", "empowerment", "communist", "capitalism", "stereotypes", "biases", "bias", "Microaggression", "prioritize human safety", "as a language model", "as an AI language model", "As a large language model", "As an AI", "ethical principles", "consensual", "it is not appropriate", "it's not appropriate", "I cannot fulfill your request", "harmful to human beings", "ethical guidelines", "my guidelines", "prioritize user safety", "adhere to ethical guidelines", "harmful consequences", "potentially harmful", "dangerous activities", "promote safety", "well-being of all users", "responsible information sharing", "jeopardize the safety", "illegal actions or intentions", "undermine the stability", "promote the well-being", "illegal activities or actions", "adherence to the law", "potentially be harmful", "illegal substances or activities", "committed to promoting", "safe information", "lawful information", "cannot provide guidance", "cannot provide information", "unable to offer assistance", "cannot engage in discussions", "programming prohibits", "follow ethical guidelines", "ensure the safety", "involves an illegal subject", "prioritize safety", "illegal subject", "prioritize user well-being", "cannot support or promote", "activities that could harm", "pose a risk to others", "against my programming", "activities that could undermine", "potentially dangerous", "not within the scope", "designed to prioritize safety", "not able to provide", "maintain user safety", "adhere to safety guidelines", "dangerous or harmful", "cannot provide any information", "focus on promoting safety" * Conversations split into 2048 token chunks as described here: https://github.com/lm-sys/FastChat/blob/main/docs/commands/data_cleaning.md This should be fully ready to train an unfiltered english Vicuna model based on the procedure here: https://github.com/lm-sys/FastChat/	[ -0.48166605830192566, -0.9302675724029541, 0.27258846163749695, 0.2309686541557312, -0.41135644912719727, 0.01115168072283268, -0.31627771258354187, -0.4773485064506531, 0.378928542137146, 0.7154964804649353, -0.7131722569465637, -0.7014886736869812, -0.5486429929733276, 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open-llm-leaderboard/details_MayaPH__FinOPT-Washington	open-llm-leaderboard	2023-10-18T23:56:34Z	249	0	[ "region:us" ]	null	2023-08-17T23:56:00Z	--- pretty_name: Evaluation run of MayaPH/FinOPT-Washington dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [MayaPH/FinOPT-Washington](https://huggingface.co/MayaPH/FinOPT-Washington) on\ \ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_MayaPH__FinOPT-Washington\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-18T23:56:22.657574](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__FinOPT-Washington/blob/main/results_2023-10-18T23-56-22.657574.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0017827181208053692,\n\ \ \"em_stderr\": 0.0004320097346039032,\n \"f1\": 0.010031459731543634,\n\ \ \"f1_stderr\": 0.0006658804659596376,\n \"acc\": 0.255327545382794,\n\ \ \"acc_stderr\": 0.0070246472681452\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0017827181208053692,\n \"em_stderr\": 0.0004320097346039032,\n\ \ \"f1\": 0.010031459731543634,\n \"f1_stderr\": 0.0006658804659596376\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.510655090765588,\n\ \ \"acc_stderr\": 0.0140492945362904\n }\n}\n```" repo_url: https://huggingface.co/MayaPH/FinOPT-Washington leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|arc:challenge\|25_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T19:13:02.567190.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_18T23_56_22.657574 path: - '/details_harness\|drop\|3_2023-10-18T23-56-22.657574.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-18T23-56-22.657574.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_18T23_56_22.657574 path: - '/details_harness\|gsm8k\|5_2023-10-18T23-56-22.657574.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-18T23-56-22.657574.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hellaswag\|10_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T19:13:02.567190.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T19:13:02.567190.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T19_13_02.567190 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T19:13:02.567190.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T19:13:02.567190.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_18T23_56_22.657574 path: - '/details_harness\|winogrande\|5_2023-10-18T23-56-22.657574.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-18T23-56-22.657574.parquet' - config_name: results data_files: - split: 2023_07_19T19_13_02.567190 path: - results_2023-07-19T19:13:02.567190.parquet - split: 2023_10_18T23_56_22.657574 path: - results_2023-10-18T23-56-22.657574.parquet - split: latest path: - results_2023-10-18T23-56-22.657574.parquet --- # Dataset Card for Evaluation run of MayaPH/FinOPT-Washington ## Dataset Description - Homepage: - Repository: https://huggingface.co/MayaPH/FinOPT-Washington - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [MayaPH/FinOPT-Washington](https://huggingface.co/MayaPH/FinOPT-Washington) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_MayaPH__FinOPT-Washington", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-18T23:56:22.657574](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__FinOPT-Washington/blob/main/results_2023-10-18T23-56-22.657574.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0017827181208053692, "em_stderr": 0.0004320097346039032, "f1": 0.010031459731543634, "f1_stderr": 0.0006658804659596376, "acc": 0.255327545382794, "acc_stderr": 0.0070246472681452 }, "harness\|drop\|3": { "em": 0.0017827181208053692, "em_stderr": 0.0004320097346039032, "f1": 0.010031459731543634, "f1_stderr": 0.0006658804659596376 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.510655090765588, "acc_stderr": 0.0140492945362904 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.4312984347343445, -0.6216882467269897, 0.23929212987422943, 0.23534129559993744, -0.21217304468154907, 0.12628230452537537, -0.31948205828666687, -0.18920543789863586, 0.34589773416519165, 0.5387658476829529, -0.6991792917251587, -0.9824076890945435, -0.6645099520683289, 0.191691592335701, -0.11293475329875946, 1.1915919780731201, -0.2628738582134247, -0.21696126461029053, 0.07153709977865219, -0.2554795742034912, -0.3080558180809021, -0.3406219780445099, -0.6367217302322388, 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open-llm-leaderboard/details_psmathur__model_007_13b	open-llm-leaderboard	2023-08-27T12:28:41Z	249	0	[ "region:us" ]	null	2023-08-18T00:15:44Z	--- pretty_name: Evaluation run of psmathur/model_007_13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [psmathur/model_007_13b](https://huggingface.co/psmathur/model_007_13b) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_psmathur__model_007_13b\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-11T11:34:56.294632](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_007_13b/blob/main/results_2023-08-11T11%3A34%3A56.294632.json)\ \ (note that their might be results for other tasks in the repos if successive evals\ \ didn't cover the same tasks. You find each in the results and the \"latest\" split\ \ for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2314240573187148,\n\ \ \"acc_stderr\": 0.03071122006512167,\n \"acc_norm\": 0.2314240573187148,\n\ \ \"acc_norm_stderr\": 0.03071122006512167,\n \"mc1\": 1.0,\n \ \ \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n \"mc2_stderr\": NaN\n\ \ },\n \"harness\|arc:challenge\|25\": {\n \"acc\": 0.22696245733788395,\n\ \ \"acc_stderr\": 0.012240491536132861,\n \"acc_norm\": 0.22696245733788395,\n\ \ \"acc_norm_stderr\": 0.012240491536132861\n },\n \"harness\|hellaswag\|10\"\ : {\n \"acc\": 0.2504481179047998,\n \"acc_stderr\": 0.004323856300539177,\n\ \ \"acc_norm\": 0.2504481179047998,\n \"acc_norm_stderr\": 0.004323856300539177\n\ \ },\n \"harness\|hendrycksTest-abstract_algebra\|5\": {\n \"acc\": 0.22,\n\ \ \"acc_stderr\": 0.04163331998932268,\n \"acc_norm\": 0.22,\n \ \ \"acc_norm_stderr\": 0.04163331998932268\n },\n \"harness\|hendrycksTest-anatomy\|5\"\ : {\n \"acc\": 0.18518518518518517,\n \"acc_stderr\": 0.03355677216313142,\n\ \ \"acc_norm\": 0.18518518518518517,\n \"acc_norm_stderr\": 0.03355677216313142\n\ \ },\n \"harness\|hendrycksTest-astronomy\|5\": {\n \"acc\": 0.17763157894736842,\n\ \ \"acc_stderr\": 0.031103182383123398,\n \"acc_norm\": 0.17763157894736842,\n\ \ \"acc_norm_stderr\": 0.031103182383123398\n },\n \"harness\|hendrycksTest-business_ethics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-clinical_knowledge\|5\": {\n \"acc\": 0.21509433962264152,\n\ \ \"acc_stderr\": 0.02528839450289137,\n \"acc_norm\": 0.21509433962264152,\n\ \ \"acc_norm_stderr\": 0.02528839450289137\n },\n \"harness\|hendrycksTest-college_biology\|5\"\ : {\n \"acc\": 0.2569444444444444,\n \"acc_stderr\": 0.03653946969442099,\n\ \ \"acc_norm\": 0.2569444444444444,\n \"acc_norm_stderr\": 0.03653946969442099\n\ \ },\n \"harness\|hendrycksTest-college_chemistry\|5\": {\n \"acc\":\ \ 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.2,\n\ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\": 0.21,\n\ \ \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n \ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.20809248554913296,\n \"acc_stderr\": 0.030952890217749874,\n\ \ \"acc_norm\": 0.20809248554913296,\n \"acc_norm_stderr\": 0.030952890217749874\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.21568627450980393,\n\ \ \"acc_stderr\": 0.04092563958237654,\n \"acc_norm\": 0.21568627450980393,\n\ \ \"acc_norm_stderr\": 0.04092563958237654\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\":\ \ 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n \"\ acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\ \ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\ acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2857142857142857,\n\ \ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\ \ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \ \ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\ acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\ acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\ acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\ \ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\ \ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \ \ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\ \ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\ acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\ acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\ acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.31390134529147984,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25925925925925924,\n\ \ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\ \ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\ \ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2905982905982906,\n\ \ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\ \ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.23754789272030652,\n\ \ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\ \ \"acc_norm_stderr\": 0.015218733046150193\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\ \ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.1864951768488746,\n\ \ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\ \ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\ \ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \ \ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness\|hendrycksTest-public_relations\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\ \ },\n \"harness\|hendrycksTest-security_studies\|5\": {\n \"acc\": 0.18775510204081633,\n\ \ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\ \ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness\|hendrycksTest-sociology\|5\"\ : {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\ \ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\ \ },\n \"harness\|hendrycksTest-us_foreign_policy\|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-virology\|5\"\ : {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\ \ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\ \ },\n \"harness\|hendrycksTest-world_religions\|5\": {\n \"acc\": 0.3216374269005848,\n\ \ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\ \ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness\|truthfulqa:mc\|0\"\ : {\n \"mc1\": 1.0,\n \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n\ \ \"mc2_stderr\": NaN\n }\n}\n```" repo_url: https://huggingface.co/psmathur/model_007_13b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: [email protected] configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|arc:challenge\|25_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|arc:challenge\|25_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hellaswag\|10_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hellaswag\|10_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:37:17.110700.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-11T11:34:56.294632.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-11T11:34:56.294632.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T13_37_17.110700 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T13:37:17.110700.parquet' - split: 2023_08_11T11_34_56.294632 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-11T11:34:56.294632.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-11T11:34:56.294632.parquet' - config_name: results data_files: - split: 2023_08_09T13_37_17.110700 path: - results_2023-08-09T13:37:17.110700.parquet - split: 2023_08_11T11_34_56.294632 path: - results_2023-08-11T11:34:56.294632.parquet - split: latest path: - results_2023-08-11T11:34:56.294632.parquet --- # Dataset Card for Evaluation run of psmathur/model_007_13b ## Dataset Description - Homepage: - Repository: https://huggingface.co/psmathur/model_007_13b - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact:** [email protected] ### Dataset Summary Dataset automatically created during the evaluation run of model [psmathur/model_007_13b](https://huggingface.co/psmathur/model_007_13b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_psmathur__model_007_13b", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-11T11:34:56.294632](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_007_13b/blob/main/results_2023-08-11T11%3A34%3A56.294632.json) (note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2314240573187148, "acc_stderr": 0.03071122006512167, "acc_norm": 0.2314240573187148, "acc_norm_stderr": 0.03071122006512167, "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN }, "harness\|arc:challenge\|25": { "acc": 0.22696245733788395, "acc_stderr": 0.012240491536132861, "acc_norm": 0.22696245733788395, "acc_norm_stderr": 0.012240491536132861 }, "harness\|hellaswag\|10": { "acc": 0.2504481179047998, "acc_stderr": 0.004323856300539177, "acc_norm": 0.2504481179047998, "acc_norm_stderr": 0.004323856300539177 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.18518518518518517, "acc_stderr": 0.03355677216313142, "acc_norm": 0.18518518518518517, "acc_norm_stderr": 0.03355677216313142 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.21509433962264152, "acc_stderr": 0.02528839450289137, "acc_norm": 0.21509433962264152, "acc_norm_stderr": 0.02528839450289137 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.2, "acc_stderr": 0.04020151261036845, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036845 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749874, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749874 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102973, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102973 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813365, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813365 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2413793103448276, "acc_stderr": 0.03565998174135302, "acc_norm": 0.2413793103448276, "acc_norm_stderr": 0.03565998174135302 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.20899470899470898, "acc_stderr": 0.02094048156533486, "acc_norm": 0.20899470899470898, "acc_norm_stderr": 0.02094048156533486 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.04040610178208841, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.04040610178208841 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.1774193548387097, "acc_stderr": 0.02173254068932927, "acc_norm": 0.1774193548387097, "acc_norm_stderr": 0.02173254068932927 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.15270935960591134, "acc_stderr": 0.02530890453938063, "acc_norm": 0.15270935960591134, "acc_norm_stderr": 0.02530890453938063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.17676767676767677, "acc_stderr": 0.027178752639044915, "acc_norm": 0.17676767676767677, "acc_norm_stderr": 0.027178752639044915 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860664, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860664 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.20256410256410257, "acc_stderr": 0.020377660970371372, "acc_norm": 0.20256410256410257, "acc_norm_stderr": 0.020377660970371372 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2111111111111111, "acc_stderr": 0.024882116857655075, "acc_norm": 0.2111111111111111, "acc_norm_stderr": 0.024882116857655075 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.21008403361344538, "acc_stderr": 0.026461398717471874, "acc_norm": 0.21008403361344538, "acc_norm_stderr": 0.026461398717471874 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.1986754966887417, "acc_stderr": 0.03257847384436776, "acc_norm": 0.1986754966887417, "acc_norm_stderr": 0.03257847384436776 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.1926605504587156, "acc_stderr": 0.016909276884936094, "acc_norm": 0.1926605504587156, "acc_norm_stderr": 0.016909276884936094 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.1527777777777778, "acc_stderr": 0.024536326026134224, "acc_norm": 0.1527777777777778, "acc_norm_stderr": 0.024536326026134224 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.31390134529147984, "acc_stderr": 0.031146796482972465, "acc_norm": 0.31390134529147984, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2595419847328244, "acc_stderr": 0.03844876139785271, "acc_norm": 0.2595419847328244, "acc_norm_stderr": 0.03844876139785271 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.2396694214876033, "acc_stderr": 0.03896878985070417, "acc_norm": 0.2396694214876033, "acc_norm_stderr": 0.03896878985070417 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25925925925925924, "acc_stderr": 0.042365112580946336, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.042365112580946336 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.22085889570552147, "acc_stderr": 0.032591773927421776, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.032591773927421776 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness\|hendrycksTest-management\|5": { "acc": 0.17475728155339806, "acc_stderr": 0.037601780060266224, "acc_norm": 0.17475728155339806, "acc_norm_stderr": 0.037601780060266224 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2905982905982906, "acc_stderr": 0.02974504857267404, "acc_norm": 0.2905982905982906, "acc_norm_stderr": 0.02974504857267404 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.23754789272030652, "acc_stderr": 0.015218733046150193, "acc_norm": 0.23754789272030652, "acc_norm_stderr": 0.015218733046150193 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.24855491329479767, "acc_stderr": 0.023267528432100174, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.023267528432100174 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.22549019607843138, "acc_stderr": 0.023929155517351284, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.023929155517351284 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.1864951768488746, "acc_stderr": 0.02212243977248077, "acc_norm": 0.1864951768488746, "acc_norm_stderr": 0.02212243977248077 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.21604938271604937, "acc_stderr": 0.022899162918445806, "acc_norm": 0.21604938271604937, "acc_norm_stderr": 0.022899162918445806 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.23404255319148937, "acc_stderr": 0.025257861359432417, "acc_norm": 0.23404255319148937, "acc_norm_stderr": 0.025257861359432417 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.25, "acc_stderr": 0.01751781884501444, "acc_norm": 0.25, "acc_norm_stderr": 0.01751781884501444 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03955932861795833, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03955932861795833 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370518, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370518 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness\|truthfulqa:mc\|0": { "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]	[ -0.7217285633087158, -0.8412837982177734, 0.3002573847770691, 0.2266877293586731, -0.18621250987052917, -0.03562956303358078, 0.030323725193738937, -0.17701968550682068, 0.583333432674408, -0.07002463936805725, -0.49750015139579773, -0.6555459499359131, -0.45904889702796936, 0.24812456965446472, -0.016036927700042725, 0.8150704503059387, -0.21351422369480133, -0.09576927125453949, 0.052979547530412674, -0.01046080607920885, -0.1892693191766739, -0.3660377860069275, -0.4509260058403015, 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