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_CHIH-HUNG__llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down	open-llm-leaderboard	2023-10-28T04:33:15Z	387	0	[ "region:us" ]	null	2023-10-01T14:57:13Z	--- pretty_name: Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down)\ \ 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_CHIH-HUNG__llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T04:33:03.109952](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down/blob/main/results_2023-10-28T04-33-03.109952.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\": 0.16180788590604026,\n\ \ \"em_stderr\": 0.003771475392335262,\n \"f1\": 0.20617239932885847,\n\ \ \"f1_stderr\": 0.00381143908978688,\n \"acc\": 0.4503938251754905,\n\ \ \"acc_stderr\": 0.010511298289531932\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.16180788590604026,\n \"em_stderr\": 0.003771475392335262,\n\ \ \"f1\": 0.20617239932885847,\n \"f1_stderr\": 0.00381143908978688\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.1288855193328279,\n \ \ \"acc_stderr\": 0.009229580761400276\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7719021310181531,\n \"acc_stderr\": 0.011793015817663588\n\ \ }\n}\n```" repo_url: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down 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_01T14_56_49.451812 path: - '/details_harness\|arc:challenge\|25_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-01T14-56-49.451812.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T04_33_03.109952 path: - '/details_harness\|drop\|3_2023-10-28T04-33-03.109952.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T04-33-03.109952.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T04_33_03.109952 path: - '/details_harness\|gsm8k\|5_2023-10-28T04-33-03.109952.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T04-33-03.109952.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hellaswag\|10_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-56-49.451812.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-56-49.451812.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_01T14_56_49.451812 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T14-56-49.451812.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T14-56-49.451812.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T04_33_03.109952 path: - '/details_harness\|winogrande\|5_2023-10-28T04-33-03.109952.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T04-33-03.109952.parquet' - config_name: results data_files: - split: 2023_10_01T14_56_49.451812 path: - results_2023-10-01T14-56-49.451812.parquet - split: 2023_10_28T04_33_03.109952 path: - results_2023-10-28T04-33-03.109952.parquet - split: latest path: - results_2023-10-28T04-33-03.109952.parquet --- # Dataset Card for Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down ## Dataset Description - Homepage: - Repository: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down - 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-FINETUNE4_3.8w-r8-gate_up_down](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down) 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_CHIH-HUNG__llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T04:33:03.109952](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE4_3.8w-r8-gate_up_down/blob/main/results_2023-10-28T04-33-03.109952.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": 0.16180788590604026, "em_stderr": 0.003771475392335262, "f1": 0.20617239932885847, "f1_stderr": 0.00381143908978688, "acc": 0.4503938251754905, "acc_stderr": 0.010511298289531932 }, "harness\|drop\|3": { "em": 0.16180788590604026, "em_stderr": 0.003771475392335262, "f1": 0.20617239932885847, "f1_stderr": 0.00381143908978688 }, "harness\|gsm8k\|5": { "acc": 0.1288855193328279, "acc_stderr": 0.009229580761400276 }, "harness\|winogrande\|5": { "acc": 0.7719021310181531, "acc_stderr": 0.011793015817663588 } } ``` ### 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]	[ -0.3804958164691925, -0.7419103384017944, 0.24650514125823975, 0.26725542545318604, -0.19499653577804565, 0.1650909036397934, -0.34090185165405273, -0.2738654315471649, 0.46136313676834106, 0.534017026424408, -0.7057173252105713, -0.9061356782913208, -0.7444051504135132, 0.2502134144306183, -0.2079017013311386, 1.194800615310669, -0.2920323312282562, -0.23206976056098938, 0.10579642653465271, -0.2470545917749405, -0.4340248703956604, -0.3805377185344696, -0.44701725244522095, 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code_x_glue_tc_nl_code_search_adv	null	2023-07-27T15:51:10Z	386	2	[ "task_categories:text-retrieval", "task_ids:document-retrieval", "annotations_creators:found", "language_creators:found", "multilinguality:other-programming-languages", "size_categories:100K<n<1M", "source_datasets:original", "language:code", "language:en", "license:c-uda", "arxiv:2102.04664", "region:us" ]	[ "text-retrieval" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - code - en license: - c-uda multilinguality: - other-programming-languages size_categories: - 100K<n<1M source_datasets: - original task_categories: - text-retrieval task_ids: - document-retrieval pretty_name: CodeXGlueTcNlCodeSearchAdv dataset_info: features: - name: id dtype: int32 - name: repo dtype: string - name: path dtype: string - name: func_name dtype: string - name: original_string dtype: string - name: language dtype: string - name: code dtype: string - name: code_tokens sequence: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: sha dtype: string - name: url dtype: string - name: docstring_summary dtype: string - name: parameters dtype: string - name: return_statement dtype: string - name: argument_list dtype: string - name: identifier dtype: string - name: nwo dtype: string - name: score dtype: float32 splits: - name: train num_bytes: 820716084 num_examples: 251820 - name: validation num_bytes: 23468834 num_examples: 9604 - name: test num_bytes: 47433760 num_examples: 19210 download_size: 966025624 dataset_size: 891618678 --- # Dataset Card for "code_x_glue_tc_nl_code_search_adv" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits-sample-size) - [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://github.com/microsoft/CodeXGLUE/tree/main/Text-Code/NL-code-search-Adv - Paper: https://arxiv.org/abs/2102.04664 ### Dataset Summary CodeXGLUE NL-code-search-Adv dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Code/NL-code-search-Adv The dataset we use comes from CodeSearchNet and we filter the dataset as the following: - Remove examples that codes cannot be parsed into an abstract syntax tree. - Remove examples that #tokens of documents is < 3 or >256 - Remove examples that documents contain special tokens (e.g. <img ...> or https:...) - Remove examples that documents are not English. ### Supported Tasks and Leaderboards - `document-retrieval`: The dataset can be used to train a model for retrieving top-k codes from a given English natural language query. ### Languages - Python programming language - English natural language ## Dataset Structure ### Data Instances An example of 'validation' looks as follows. ``` { "argument_list": "", "code": "def Func(arg_0, arg_1='.', arg_2=True, arg_3=False, *arg_4):\n \"\"\"Downloads Dailymotion videos by URL.\n \"\"\"\n\n arg_5 = get_content(rebuilt_url(arg_0))\n arg_6 = json.loads(match1(arg_5, r'qualities\":({.+?}),\"'))\n arg_7 = match1(arg_5, r'\"video_title\"\\s:\\s\"([^\"]+)\"') or \\\n match1(arg_5, r'\"title\"\\s:\\s\"([^\"]+)\"')\n arg_7 = unicodize(arg_7)\n\n for arg_8 in ['1080','720','480','380','240','144','auto']:\n try:\n arg_9 = arg_6[arg_8][1][\"url\"]\n if arg_9:\n break\n except KeyError:\n pass\n\n arg_10, arg_11, arg_12 = url_info(arg_9)\n\n print_info(site_info, arg_7, arg_10, arg_12)\n if not arg_3:\n download_urls([arg_9], arg_7, arg_11, arg_12, arg_1=arg_1, arg_2=arg_2)", "code_tokens": ["def", "Func", "(", "arg_0", ",", "arg_1", "=", "'.'", ",", "arg_2", "=", "True", ",", "arg_3", "=", "False", ",", "", "arg_4", ")", ":", "arg_5", "=", "get_content", "(", "rebuilt_url", "(", "arg_0", ")", ")", "arg_6", "=", "json", ".", "loads", "(", "match1", "(", "arg_5", ",", "r'qualities\":({.+?}),\"'", ")", ")", "arg_7", "=", "match1", "(", "arg_5", ",", "r'\"video_title\"\\s:\\s\"([^\"]+)\"'", ")", "or", "match1", "(", "arg_5", ",", "r'\"title\"\\s:\\s\"([^\"]+)\"'", ")", "arg_7", "=", "unicodize", "(", "arg_7", ")", "for", "arg_8", "in", "[", "'1080'", ",", "'720'", ",", "'480'", ",", "'380'", ",", "'240'", ",", "'144'", ",", "'auto'", "]", ":", "try", ":", "arg_9", "=", "arg_6", "[", "arg_8", "]", "[", "1", "]", "[", "\"url\"", "]", "if", "arg_9", ":", "break", "except", "KeyError", ":", "pass", "arg_10", ",", "arg_11", ",", "arg_12", "=", "url_info", "(", "arg_9", ")", "print_info", "(", "site_info", ",", "arg_7", ",", "arg_10", ",", "arg_12", ")", "if", "not", "arg_3", ":", "download_urls", "(", "[", "arg_9", "]", ",", "arg_7", ",", "arg_11", ",", "arg_12", ",", "arg_1", "=", "arg_1", ",", "arg_2", "=", "arg_2", ")"], "docstring": "Downloads Dailymotion videos by URL.", "docstring_summary": "Downloads Dailymotion videos by URL.", "docstring_tokens": ["Downloads", "Dailymotion", "videos", "by", "URL", "."], "func_name": "", "id": 0, "identifier": "dailymotion_download", "language": "python", "nwo": "soimort/you-get", "original_string": "", "parameters": "(url, output_dir='.', merge=True, info_only=False, *kwargs)", "path": "src/you_get/extractors/dailymotion.py", "repo": "", "return_statement": "", "score": 0.9997601509094238, "sha": "b746ac01c9f39de94cac2d56f665285b0523b974", "url": "https://github.com/soimort/you-get/blob/b746ac01c9f39de94cac2d56f665285b0523b974/src/you_get/extractors/dailymotion.py#L13-L35" } ``` ### Data Fields In the following each data field in go is explained for each config. The data fields are the same among all splits. #### default \| field name \| type \| description \| \|-----------------\|-----------------------\|-----------------------------------------------------------------------------------\| \|id \|int32 \| Index of the sample \| \|repo \|string \| repo: the owner/repo \| \|path \|string \| path: the full path to the original file \| \|func_name \|string \| func_name: the function or method name \| \|original_string \|string \| original_string: the raw string before tokenization or parsing \| \|language \|string \| language: the programming language \| \|code \|string \| code/function: the part of the original_string that is code \| \|code_tokens \|Sequence[string] \| code_tokens/function_tokens: tokenized version of code \| \|docstring \|string \| docstring: the top-level comment or docstring, if it exists in the original string\| \|docstring_tokens \|Sequence[string] \| docstring_tokens: tokenized version of docstring \| \|sha \|string \| sha of the file \| \|url \|string \| url of the file \| \|docstring_summary\|string \| Summary of the docstring \| \|parameters \|string \| parameters of the function \| \|return_statement \|string \| return statement \| \|argument_list \|string \| list of arguments of the function \| \|identifier \|string \| identifier \| \|nwo \|string \| nwo \| \|score \|datasets.Value("float"]\| score for this search \| ### Data Splits \| name \|train \|validation\|test \| \|-------\|-----:\|---------:\|----:\| \|default\|251820\| 9604\|19210\| ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization Data from CodeSearchNet Challenge dataset. [More Information Needed] #### Who are the source language producers? Software Engineering developers. ### 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 https://github.com/microsoft, https://github.com/madlag ### Licensing Information Computational Use of Data Agreement (C-UDA) License. ### Citation Information ``` @article{DBLP:journals/corr/abs-2102-04664, author = {Shuai Lu and Daya Guo and Shuo Ren and Junjie Huang and Alexey Svyatkovskiy and Ambrosio Blanco and Colin B. Clement and Dawn Drain and Daxin Jiang and Duyu Tang and Ge Li and Lidong Zhou and Linjun Shou and Long Zhou and Michele Tufano and Ming Gong and Ming Zhou and Nan Duan and Neel Sundaresan and Shao Kun Deng and Shengyu Fu and Shujie Liu}, title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding and Generation}, journal = {CoRR}, volume = {abs/2102.04664}, year = {2021} } @article{husain2019codesearchnet, title={Codesearchnet challenge: Evaluating the state of semantic code search}, author={Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc}, journal={arXiv preprint arXiv:1909.09436}, year={2019} } ``` ### Contributions Thanks to @madlag (and partly also @ncoop57) for adding this dataset.	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gigant/oldbookillustrations	gigant	2022-08-03T17:35:37Z	386	16	[ "task_categories:text-to-image", "task_categories:image-to-text", "task_categories:image-to-image", "task_ids:image-captioning", "annotations_creators:expert-generated", "language_creators:expert-generated", "multilinguality:multilingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "language:fr", "language:de", "license:cc-by-nc-4.0", "lam", "1800-1900", "region:us" ]	[ "text-to-image", "image-to-text", "image-to-image" ]	2022-07-28T08:31:19Z	--- annotations_creators: - expert-generated language: - en - fr - de language_creators: - expert-generated license: - cc-by-nc-4.0 multilinguality: - multilingual pretty_name: Old Book Illustrations size_categories: - 1K<n<10K source_datasets: - original tags: - lam - 1800-1900 task_categories: - text-to-image - image-to-text - image-to-image task_ids: - image-captioning --- # Dataset Card for Old Book Illustrations ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Discussion of Biases](#discussion-of-biases) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - [Homepage](https://www.oldbookillustrations.com/) ### Dataset Summary The Old Book Illustrations contains 4172 illustrations scanned from old books, this collection was collected & curated by the team of the website [Old Book Illustrations](https://www.oldbookillustrations.com/). The webmaster of Old Book Illustrations kindly allowed us to scrap these information in order to create this dataset for the [BigLAM initiative](https://huggingface.co/biglam). ### Languages The captions and descriptions are mostly in English but can contain some sentences from other languages such as French or German. For instance you can find this description that contains a French sentence: >The caption reads in the original French: Vue de l’aqueduc de Salones qui conduisait l’eau à Spalatro. ## Dataset Structure Each row contains information gathered from the page of an illustration on the website [Old Book Illustrations](https://www.oldbookillustrations.com/). As of July 2022, there are 4172 illustrations in this dataset. ### Data Fields * `rawscan`: the image as originally scanned from the book, without further processing * `1600px`: the cleaned image, resized to a width of 1600 pixels (height can vary) * `info_url`: URL to the illustration page on oldbookillustrations.com * `ìnfo_src`: URL to an icon-sized version of the image * `info_alt`: short description of the image * `artist_name`: artist name * `artist_date`: birth date of the artist * `artist_countries`: list of the countries the artist is from * `book_title`: original title of the book the illustration is extracted from * `book_authors`: list of the authors of the book * `book_publishers`: list of the publishers of the book * `openlibrary-url`: URL to the openlibrary entry for the book * `tags`: list of keywords for this illustration on oldbookillustrations.com * `illustration_source_name`: list of the sources for this illustration * `illustration_source_url`: list of the URL for these sources * `illustration_subject`: category of the subject represented in the illustration * `illustration_format`: category of the format of the illustration * `image_title`: title of the image * `image_caption`: caption of the image. Seems to be the caption that appears next to the image in the book, translated to English if in another language * `image_description`: longer description of the image. If there is one, it also quotes the caption in the original language * `rawscan_url`: URL to the rawscan image on oldbookillustration.com * `1600px_url`: URL to the cleaned image on oldbookillustration.com ## Dataset Creation ### Curation Rationale This collection was collected & curated by the team of the website [Old Book Illustrations](https://www.oldbookillustrations.com/). This version contains all the data that was available on the website as of July 2022, but the website is being actively maintained so if you want more old book illustrations, make sure to check [Old Book Illustrations](https://www.oldbookillustrations.com/). ### Source Data #### Initial Data Collection and Normalization Initial data is gathered from the website [Old Book Illustrations](https://www.oldbookillustrations.com/). The sources of the illustration scans are specified for each entry in the columns `illustration_source_name` and `illustration_source_url`. ### Personal and Sensitive Information The Old Book Illustrations' Terms and conditions reads: >OBI [Old Book Illustrations] explores the art of book illustrations within boundaries defined by time and age, not by subject, treatment, or intent. This means that some illustrations might be deemed offensive, disturbing, misleading, or otherwise objectionable. We do not endorse views or opinions the Illustrations may express, neither do we guarantee that the information conveyed by any Illustration is accurate. ## Considerations for Using the Data ### Discussion of Biases The Old Book Illustrations' Terms and conditions reads: >OBI [Old Book Illustrations] explores the art of book illustrations within boundaries defined by time and age, not by subject, treatment, or intent. This means that some illustrations might be deemed offensive, disturbing, misleading, or otherwise objectionable. We do not endorse views or opinions the Illustrations may express, neither do we guarantee that the information conveyed by any Illustration is accurate. ## Additional Information ### Dataset Curators The Old Book Illustrations collection is curated and maintained by the team of the [Old Book Illustrations website](https://www.oldbookillustrations.com/). ### Licensing Information [Old Book Illustrations](https://www.oldbookillustrations.com/) website reads: >We don’t limit the use of the illustrations available on our site, but we accept no responsibility regarding any problem, legal or otherwise, which might result from such use. More specifically, we leave it up to users to make sure that their project complies with the copyright laws of their country of residence. Text content (descriptions, translations, etc.) is published under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The Old Book Illustrations webmaster mentioned that most images are public domain in the US and Europe, but there can be some exceptions. An example are the illustrations from [Early poems of William Morris](https://www.oldbookillustrations.com/titles/early-poems-of-william-morris/) as the illustrator died 1955, so her work is not public domain in Europe as of 2022, or [Under the hill](https://www.oldbookillustrations.com/titles/under-the-hill/) which was published in the US in 1928 and therefore is not public domain there. ### Citation Information ```bibtex @misc{old book illustrations_2007, url={https://www.oldbookillustrations.com/}, journal={Old Book Illustrations}, year={2007}} ``` ### Contributions Thanks to [@gigant](https://huggingface.co/gigant) ([@giganttheo](https://github.com/giganttheo)) for adding this dataset.	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result-kand2-sdxl-wuerst-karlo/ca332ef1	result-kand2-sdxl-wuerst-karlo	2023-11-08T20:31:09Z	386	0	[ "region:us" ]	null	2023-11-08T20:31:08Z	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 192 num_examples: 10 download_size: 1372 dataset_size: 192 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "ca332ef1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.6490883231163025, -0.10168157517910004, 0.2047288566827774, 0.5692877173423767, -0.16116656363010406, -0.15900522470474243, 0.41292697191238403, -0.3548046946525574, 0.7551184892654419, 0.47461265325546265, -0.965005099773407, -0.5768666863441467, -0.5805087089538574, -0.3343470096588135, -0.32270684838294983, 1.1638939380645752, 0.0941145047545433, 0.2136775255203247, -0.21275930106639862, -0.06235893443226814, -0.3545968532562256, 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medalpaca/medical_meadow_medical_flashcards	medalpaca	2023-04-06T17:12:17Z	385	5	[ "task_categories:question-answering", "language:en", "license:cc", "region:us" ]	[ "question-answering" ]	2023-04-06T17:09:17Z	--- license: cc task_categories: - question-answering language: - en --- # Dataset Card for Medical Flashcards ## Dataset Description - Repository: https://github.com/kbressem/medalpaca - Paper: TBA ### Dataset Summary Medicine as a whole encompasses a wide range of subjects that medical students and graduates must master in order to practice effectively. This includes a deep understanding of basic medical sciences, clinical knowledge, and clinical skills. The Anki Medical Curriculum flashcards are created and updated by medical students and cover the entirety of this curriculum, addressing subjects such as anatomy, physiology, pathology, pharmacology, and more. These flashcards frequently feature succinct summaries and mnemonics to aid in learning and retention of vital medical concepts. In our study, we employed the flashcards as a resource for generating question-answer pairs for training purposes. After removing cards that contained images, we utilized OpenAI's GPT-3.5-turbo to rephrase the cards into coherent, contextually relevant question-answer pairs. In general the questions and answers are short and focused, as the flashcards do not allow to add much information. ### Citation Information TBA	[ -0.26660987734794617, -0.7879151105880737, 0.5130571722984314, -0.12272248417139053, -0.49648961424827576, -0.1123448982834816, -0.03503870964050293, -0.1634858250617981, 0.5247394442558289, 0.36937132477760315, -0.35379758477211, -0.6432185173034668, -0.437438428401947, -0.008098294958472252, -0.08437398821115494, 1.2254270315170288, -0.11413450539112091, 0.1930256485939026, -0.39956194162368774, -0.48138099908828735, -0.7426590323448181, -0.22327691316604614, -0.6452264189720154, -0.32060977816581726, 0.5036043524742126, 0.6572169065475464, 0.6513398289680481, 0.841343879699707, 0.5397307276725769, 0.17135663330554962, 0.0351172536611557, -0.21301275491714478, -0.13825471699237823, -0.0674862414598465, -0.08713121712207794, -0.5126062631607056, -0.6353514194488525, 0.0954890176653862, 0.5563914179801941, 0.633256733417511, 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migtissera/Synthia-v1.3	migtissera	2023-11-16T06:19:06Z	385	58	[ "license:apache-2.0", "region:us" ]	null	2023-11-16T06:18:24Z	--- license: apache-2.0 ---	[ -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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hind_encorp	null	2022-11-03T16:15:40Z	384	1	[ "task_categories:translation", "annotations_creators:expert-generated", "language_creators:crowdsourced", "language_creators:machine-generated", "multilinguality:translation", "size_categories:100K<n<1M", "source_datasets:original", "language:en", "language:hi", "license:cc-by-nc-sa-3.0", "region:us" ]	[ "translation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - crowdsourced - machine-generated language: - en - hi license: - cc-by-nc-sa-3.0 multilinguality: - translation size_categories: - 100K<n<1M source_datasets: - original task_categories: - translation task_ids: [] paperswithcode_id: hindencorp pretty_name: HindEnCorp dataset_info: features: - name: id dtype: string - name: source dtype: string - name: alignment_type dtype: string - name: alignment_quality dtype: string - name: translation dtype: translation: languages: - en - hi splits: - name: train num_bytes: 78945714 num_examples: 273885 download_size: 23899723 dataset_size: 78945714 --- # Dataset Card for HindEnCorp ## 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://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0023-625F-0 - Repository: https://lindat.mff.cuni.cz/repository/xmlui/ - Paper: http://www.lrec-conf.org/proceedings/lrec2014/pdf/835_Paper.pdf - Leaderboard: - Point of Contact: ### Dataset Summary HindEnCorp parallel texts (sentence-aligned) come from the following sources: Tides, which contains 50K sentence pairs taken mainly from news articles. This dataset was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008). Commentaries by Daniel Pipes contain 322 articles in English written by a journalist Daniel Pipes and translated into Hindi. EMILLE. This corpus (Baker et al., 2002) consists of three components: monolingual, parallel and annotated corpora. There are fourteen monolingual sub- corpora, including both written and (for some lan- guages) spoken data for fourteen South Asian lan- guages. The EMILLE monolingual corpora contain in total 92,799,000 words (including 2,627,000 words of transcribed spoken data for Bengali, Gujarati, Hindi, Punjabi and Urdu). The parallel corpus consists of 200,000 words of text in English and its accompanying translations into Hindi and other languages. Smaller datasets as collected by Bojar et al. (2010) include the corpus used at ACL 2005 (a subcorpus of EMILLE), a corpus of named entities from Wikipedia (crawled in 2009), and Agriculture domain parallel corpus. For the current release, we are extending the parallel corpus using these sources: Intercorp (Čermák and Rosen,2012) is a large multilingual parallel corpus of 32 languages including Hindi. The central language used for alignment is Czech. Intercorp’s core texts amount to 202 million words. These core texts are most suitable for us because their sentence alignment is manually checked and therefore very reliable. They cover predominately short sto- ries and novels. There are seven Hindi texts in Inter- corp. Unfortunately, only for three of them the English translation is available; the other four are aligned only with Czech texts. The Hindi subcorpus of Intercorp contains 118,000 words in Hindi. TED talks 3 held in various languages, primarily English, are equipped with transcripts and these are translated into 102 languages. There are 179 talks for which Hindi translation is available. The Indic multi-parallel corpus (Birch et al., 2011; Post et al., 2012) is a corpus of texts from Wikipedia translated from the respective Indian language into English by non-expert translators hired over Mechanical Turk. The quality is thus somewhat mixed in many respects starting from typesetting and punctuation over capi- talization, spelling, word choice to sentence structure. A little bit of control could be in principle obtained from the fact that every input sentence was translated 4 times. We used the 2012 release of the corpus. Launchpad.net is a software collaboration platform that hosts many open-source projects and facilitates also collaborative localization of the tools. We downloaded all revisions of all the hosted projects and extracted the localization (.po) files. Other smaller datasets. This time, we added Wikipedia entities as crawled in 2013 (including any morphological variants of the named entitity that appears on the Hindi variant of the Wikipedia page) and words, word examples and quotes from the Shabdkosh online dictionary. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages Hindi, English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields HindEncorp Columns: - source identifier (where do the segments come from) - alignment type (number of English segments - number of Hindi segments) - alignment quality, which is one of the following: "manual" ... for sources that were sentence-aligned manually "implied" ... for sources where one side was constructed by translating segment by segment float ... a value somehow reflecting the goodness of the automatic alignment; not really reliable - English segment or segments - Hindi segment or segments Each of the segments field is in the plaintext or export format as described above. If there are more than one segments on a line (e.g. for lines with alignment type 2-1 where there are two English segments), then the segments are delimited with `<s>` in the text field. ### Data Splits [More Information Needed] ## Dataset Creation ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? Daniel Pipes,Baker,Bojar,"Čermák and Rosen,2012","Birch et al., 2011; Post et al., 2012" ### Annotations #### Annotation process the 1st part of data TIDES was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008). #### 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 Dataset provided for research purposes only. Please check dataset license for additional information. ## Additional Information ### Dataset Curators Bojar, Ondřej ; Diatka, Vojtěch ; Straňák, Pavel ; Tamchyna, Aleš ; Zeman, Daniel ### Licensing Information CC BY-NC-SA 3.0 ### Citation Information @InProceedings{hindencorp05:lrec:2014, author = {Ond{\v{r}}ej Bojar and Vojt{\v{e}}ch Diatka and Pavel Rychl{\'{y}} and Pavel Stra{\v{n}}{\'{a}}k and V{\'{\i}}t Suchomel and Ale{\v{s}} Tamchyna and Daniel Zeman}, title = "{HindEnCorp - Hindi-English and Hindi-only Corpus for Machine Translation}", booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } ### Contributions Thanks to [@rahul-art](https://github.com/rahul-art) for adding this dataset.	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medal	null	2023-06-13T12:39:11Z	384	11	[ "task_categories:other", "annotations_creators:expert-generated", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:10M<n<100M", "source_datasets:original", "language:en", "license:unknown", "disambiguation", "region:us" ]	[ "other" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - unknown multilinguality: - monolingual size_categories: - 10M<n<100M source_datasets: - original task_categories: - other task_ids: [] paperswithcode_id: medal pretty_name: MeDAL tags: - disambiguation dataset_info: features: - name: abstract_id dtype: int32 - name: text dtype: string - name: location sequence: int32 - name: label sequence: string splits: - name: train num_bytes: 3573399948 num_examples: 3000000 - name: test num_bytes: 1190766821 num_examples: 1000000 - name: validation num_bytes: 1191410723 num_examples: 1000000 - name: full num_bytes: 15536883723 num_examples: 14393619 download_size: 21060929078 dataset_size: 21492461215 --- # Dataset Card for the MeDAL dataset ## 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: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Repository: https://github.com/BruceWen120/medal - Paper: https://www.aclweb.org/anthology/2020.clinicalnlp-1.15/ - Dataset (Kaggle): https://www.kaggle.com/xhlulu/medal-emnlp - Dataset (Zenodo): https://zenodo.org/record/4265632 - Pretrained model: https://huggingface.co/xhlu/electra-medal - Leaderboard: [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) ### Dataset Summary A large medical text dataset (14Go) curated to 4Go for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain. For example, DHF can be disambiguated to dihydrofolate, diastolic heart failure, dengue hemorragic fever or dihydroxyfumarate ### Supported Tasks and Leaderboards Medical abbreviation disambiguation ### Languages English (en) ## Dataset Structure Each file is a table consisting of three columns: * text: The normalized content of an abstract * location: The location (index) of each abbreviation that was substituted * label: The word at that was substituted at the given location ### Data Instances An example from the train split is: ``` {'abstract_id': 14145090, 'text': 'velvet antlers vas are commonly used in traditional chinese medicine and invigorant and contain many PET components for health promotion the velvet antler peptide svap is one of active components in vas based on structural study the svap interacts with tgfÎ² receptors and disrupts the tgfÎ² pathway we hypothesized that svap prevents cardiac fibrosis from pressure overload by blocking tgfÎ² signaling SDRs underwent TAC tac or a sham operation T3 one month rats received either svap mgkgday or vehicle for an additional one month tac surgery induced significant cardiac dysfunction FB activation and fibrosis these effects were improved by treatment with svap in the heart tissue tac remarkably increased the expression of tgfÎ² and connective tissue growth factor ctgf ROS species C2 and the phosphorylation C2 of smad and ERK kinases erk svap inhibited the increases in reactive oxygen species C2 ctgf expression and the phosphorylation of smad and erk but not tgfÎ² expression in cultured cardiac fibroblasts angiotensin ii ang ii had similar effects compared to tac surgery such as increases in Î±smapositive CFs and collagen synthesis svap eliminated these effects by disrupting tgfÎ² IB to its receptors and blocking ang iitgfÎ² downstream signaling these results demonstrated that svap has antifibrotic effects by blocking the tgfÎ² pathway in CFs', 'location': [63], 'label': ['transverse aortic constriction']} ``` ### Data Fields The column types are: * text: content of the abstract as a string * location: index of the substitution as an integer * label: substitued word as a string ### Data Splits The following files are present: * `full_data.csv`: The full dataset with all 14M abstracts. * `train.csv`: The subset used to train the baseline and proposed models. * `valid.csv`: The subset used to validate the model during training for hyperparameter selection. * `test.csv`: The subset used to evaluate the model and report the results in the tables. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data The original dataset was retrieved and modified from the [NLM website](https://www.nlm.nih.gov/databases/download/pubmed_medline.html). #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations Details on how the abbreviations were created can be found in section 2.2 (Dataset Creation) of the [ACL ClinicalNLP paper](https://aclanthology.org/2020.clinicalnlp-1.15.pdf). #### 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 Since the abstracts are written in English, the data is biased towards anglo-centric medical research. If you plan to use a model pre-trained on this dataset for a predominantly non-English community, it is important to verify whether there are negative biases present in your model, and ensure that they are correctly mitigated. For instance, you could fine-tune your dataset on a multilingual medical disambiguation dataset, or collect a dataset specific to your use case. ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information The ELECTRA model is licensed under [Apache 2.0](https://github.com/google-research/electra/blob/master/LICENSE). The license for the libraries used in this project (`transformers`, `pytorch`, etc.) can be found in their respective GitHub repository. Our model is released under a MIT license. The original dataset was retrieved and modified from the [NLM website](https://www.nlm.nih.gov/databases/download/pubmed_medline.html). By using this dataset, you are bound by the [terms and conditions](https://www.nlm.nih.gov/databases/download/terms_and_conditions_pubmed.html) specified by NLM: > INTRODUCTION > > Downloading data from the National Library of Medicine FTP servers indicates your acceptance of the following Terms and Conditions: No charges, usage fees or royalties are paid to NLM for this data. > > MEDLINE/PUBMED SPECIFIC TERMS > > NLM freely provides PubMed/MEDLINE data. Please note some PubMed/MEDLINE abstracts may be protected by copyright. > > GENERAL TERMS AND CONDITIONS > > * Users of the data agree to: > * acknowledge NLM as the source of the data by including the phrase "Courtesy of the U.S. National Library of Medicine" in a clear and conspicuous manner, > * properly use registration and/or trademark symbols when referring to NLM products, and > * not indicate or imply that NLM has endorsed its products/services/applications. > > * Users who republish or redistribute the data (services, products or raw data) agree to: > * maintain the most current version of all distributed data, or > * make known in a clear and conspicuous manner that the products/services/applications do not reflect the most current/accurate data available from NLM. > > * These data are produced with a reasonable standard of care, but NLM makes no warranties express or implied, including no warranty of merchantability or fitness for particular purpose, regarding the accuracy or completeness of the data. Users agree to hold NLM and the U.S. Government harmless from any liability resulting from errors in the data. NLM disclaims any liability for any consequences due to use, misuse, or interpretation of information contained or not contained in the data. > > * NLM does not provide legal advice regarding copyright, fair use, or other aspects of intellectual property rights. See the NLM Copyright page. > > * NLM reserves the right to change the type and format of its machine-readable data. NLM will take reasonable steps to inform users of any changes to the format of the data before the data are distributed via the announcement section or subscription to email and RSS updates. ### Citation Information ``` @inproceedings{wen-etal-2020-medal, title = "{M}e{DAL}: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining", author = "Wen, Zhi and Lu, Xing Han and Reddy, Siva", booktitle = "Proceedings of the 3rd Clinical Natural Language Processing Workshop", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.clinicalnlp-1.15", pages = "130--135", abstract = "One of the biggest challenges that prohibit the use of many current NLP methods in clinical settings is the availability of public datasets. In this work, we present MeDAL, a large medical text dataset curated for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain. We pre-trained several models of common architectures on this dataset and empirically showed that such pre-training leads to improved performance and convergence speed when fine-tuning on downstream medical tasks.", } ``` ### Contributions Thanks to [@Narsil](https://github.com/Narsil) and [@xhlulu](https://github.com/xhlulu)) for adding this dataset.	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squad_kor_v2	null	2023-02-07T14:40:49Z	384	3	[ "task_categories:question-answering", "task_ids:extractive-qa", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:extended\|squad_kor_v1", "source_datasets:original", "language:ko", "license:cc-by-nd-4.0", "region:us" ]	[ "question-answering" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - found language: - ko license: - cc-by-nd-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - extended\|squad_kor_v1 - original task_categories: - question-answering task_ids: - extractive-qa paperswithcode_id: null pretty_name: KorQuAD v2.1 dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answer struct: - name: text dtype: string - name: answer_start dtype: int32 - name: html_answer_start dtype: int32 - name: url dtype: string - name: raw_html dtype: string config_name: squad_kor_v2 splits: - name: train num_bytes: 17983434492 num_examples: 83486 - name: validation num_bytes: 2230543100 num_examples: 10165 download_size: 1373763305 dataset_size: 20213977592 --- # Dataset Card for KorQuAD v2.1 ## 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://korquad.github.io/) - [Repository](https://github.com/korquad/korquad.github.io/tree/master/dataset) - [Paper](https://korquad.github.io/dataset/KorQuAD_2.0/KorQuAD_2.0_paper.pdf) ### Dataset Summary KorQuAD 2.0 is a Korean question and answering dataset consisting of a total of 100,000+ pairs. There are three major differences from KorQuAD 1.0, which is the standard Korean Q & A data. The first is that a given document is a whole Wikipedia page, not just one or two paragraphs. Second, because the document also contains tables and lists, it is necessary to understand the document structured with HTML tags. Finally, the answer can be a long text covering not only word or phrase units, but paragraphs, tables, and lists. ### Supported Tasks and Leaderboards `question-answering` ### Languages Korean ## Dataset Structure Follows the standart SQuAD format. There is only 1 answer per question ### Data Instances An example from the data set looks as follows: ```py {'answer': {'answer_start': 3873, 'html_answer_start': 16093, 'text': '20,890 표'}, 'context': '<!DOCTYPE html>\n<html>\n<head>\n<meta>\n<title>심규언 - 위키백과, 우리 모두의 백과사전</title>\n\n\n<link>\n.....[omitted]', 'id': '36615', 'question': '심규언은 17대 지방 선거에서 몇 표를 득표하였는가?', 'raw_html': '<!DOCTYPE html>\n<html c ...[omitted]', 'title': '심규언', 'url': 'https://ko.wikipedia.org/wiki/심규언'} ``` ### Data Fields ```py {'id': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'context': Value(dtype='string', id=None), 'question': Value(dtype='string', id=None), 'answer': {'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int32', id=None), 'html_answer_start': Value(dtype='int32', id=None)}, 'url': Value(dtype='string', id=None), 'raw_html': Value(dtype='string', id=None)} ``` ### Data Splits - Train : 83486 - Validation: 10165 ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data Wikipedia #### 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 [CC BY-ND 2.0 KR](https://creativecommons.org/licenses/by-nd/2.0/kr/deed.en) ### Citation Information ``` @article{NODE09353166, author={Youngmin Kim,Seungyoung Lim;Hyunjeong Lee;Soyoon Park;Myungji Kim}, title={{KorQuAD 2.0: Korean QA Dataset for Web Document Machine Comprehension}}, booltitle={{Journal of KIISE 제47권 제6호}}, journal={{Journal of KIISE}}, volume={{47}}, issue={{6}}, publisher={The Korean Institute of Information Scientists and Engineers}, year={2020}, ISSN={{2383-630X}}, pages={577-586}, url={http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09353166}} ``` ### Contributions Thanks to [@cceyda](https://github.com/cceyda) for adding this dataset.	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alexandrainst/audio_test_dataset	alexandrainst	2023-05-01T14:28:58Z	384	0	[ "size_categories:n<1K", "language:da", "license:cc0-1.0", "region:us" ]	null	2023-05-01T14:24:51Z	--- dataset_info: features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string splits: - name: train num_bytes: 108571 num_examples: 5 - name: validation num_bytes: 116850 num_examples: 5 - name: test num_bytes: 78943 num_examples: 5 - name: other num_bytes: 101436 num_examples: 5 - name: invalidated num_bytes: 156925 num_examples: 5 download_size: 590682 dataset_size: 562725 license: cc0-1.0 language: - da size_categories: - n<1K --- # Dataset Card for "audio_test_dataset" This dataset consists of the first 5 samples of [mozilla-foundation/common_voice_13_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0) and is only used for unit testing.	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distilled-from-one-sec-cv12/chunk_230	distilled-from-one-sec-cv12	2023-05-29T00:50:28Z	384	0	[ "region:us" ]	null	2023-05-29T00:49:19Z	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1017249644 num_examples: 198217 download_size: 1037402846 dataset_size: 1017249644 --- # Dataset Card for "chunk_230" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.6223131418228149, -0.38251498341560364, 0.19207051396369934, 0.41200578212738037, -0.3575635552406311, 0.043611686676740646, 0.20858724415302277, -0.19078035652637482, 1.0001847743988037, 0.5656877160072327, -0.7899996638298035, -0.42944127321243286, -0.6489028930664062, -0.30840837955474854, -0.7546176314353943, 1.2554113864898682, 0.09319411218166351, 0.11619068682193756, -0.35541197657585144, 0.004256858490407467, -0.7595183253288269, -0.28081998229026794, 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open-llm-leaderboard/details_chargoddard__llama-2-16b-nastychat	open-llm-leaderboard	2023-10-28T13:04:24Z	384	0	[ "region:us" ]	null	2023-09-12T20:07:04Z	--- pretty_name: Evaluation run of chargoddard/llama-2-16b-nastychat dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [chargoddard/llama-2-16b-nastychat](https://huggingface.co/chargoddard/llama-2-16b-nastychat)\ \ 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_chargoddard__llama-2-16b-nastychat\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T13:04:12.376719](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__llama-2-16b-nastychat/blob/main/results_2023-10-28T13-04-12.376719.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\": 0.15782298657718122,\n\ \ \"em_stderr\": 0.0037335886860588308,\n \"f1\": 0.24126782718120757,\n\ \ \"f1_stderr\": 0.0038375528639246364,\n \"acc\": 0.41388384087105284,\n\ \ \"acc_stderr\": 0.009872075116078132\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.15782298657718122,\n \"em_stderr\": 0.0037335886860588308,\n\ \ \"f1\": 0.24126782718120757,\n \"f1_stderr\": 0.0038375528639246364\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08112206216830932,\n \ \ \"acc_stderr\": 0.007520395797922653\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7466456195737964,\n \"acc_stderr\": 0.01222375443423361\n\ \ }\n}\n```" repo_url: https://huggingface.co/chargoddard/llama-2-16b-nastychat 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_12T20_06_49.075564 path: - '/details_harness\|arc:challenge\|25_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-12T20-06-49.075564.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T13_04_12.376719 path: - '/details_harness\|drop\|3_2023-10-28T13-04-12.376719.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T13-04-12.376719.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T13_04_12.376719 path: - '/details_harness\|gsm8k\|5_2023-10-28T13-04-12.376719.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T13-04-12.376719.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hellaswag\|10_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T20-06-49.075564.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T20-06-49.075564.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_12T20_06_49.075564 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T20-06-49.075564.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T20-06-49.075564.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T13_04_12.376719 path: - '/details_harness\|winogrande\|5_2023-10-28T13-04-12.376719.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T13-04-12.376719.parquet' - config_name: results data_files: - split: 2023_09_12T20_06_49.075564 path: - results_2023-09-12T20-06-49.075564.parquet - split: 2023_10_28T13_04_12.376719 path: - results_2023-10-28T13-04-12.376719.parquet - split: latest path: - results_2023-10-28T13-04-12.376719.parquet --- # Dataset Card for Evaluation run of chargoddard/llama-2-16b-nastychat ## Dataset Description - Homepage: - Repository: https://huggingface.co/chargoddard/llama-2-16b-nastychat - 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 [chargoddard/llama-2-16b-nastychat](https://huggingface.co/chargoddard/llama-2-16b-nastychat) 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_chargoddard__llama-2-16b-nastychat", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T13:04:12.376719](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__llama-2-16b-nastychat/blob/main/results_2023-10-28T13-04-12.376719.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": 0.15782298657718122, "em_stderr": 0.0037335886860588308, "f1": 0.24126782718120757, "f1_stderr": 0.0038375528639246364, "acc": 0.41388384087105284, "acc_stderr": 0.009872075116078132 }, "harness\|drop\|3": { "em": 0.15782298657718122, "em_stderr": 0.0037335886860588308, "f1": 0.24126782718120757, "f1_stderr": 0.0038375528639246364 }, "harness\|gsm8k\|5": { "acc": 0.08112206216830932, "acc_stderr": 0.007520395797922653 }, "harness\|winogrande\|5": { "acc": 0.7466456195737964, "acc_stderr": 0.01222375443423361 } } ``` ### 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]	[ -0.30349090695381165, -0.766709566116333, 0.1836712658405304, 0.2211119830608368, -0.23391976952552795, 0.23592723906040192, -0.3412407338619232, -0.2850671708583832, 0.483774334192276, 0.5464513301849365, -0.7155638933181763, -0.9192794561386108, -0.6575812697410583, 0.1518377810716629, -0.18194696307182312, 1.2443864345550537, -0.10283578187227249, -0.2549678385257721, 0.040600597858428955, -0.18510673940181732, -0.44935178756713867, -0.4780017137527466, -0.505613386631012, 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maf917/dzdzdz	maf917	2023-11-03T05:49:51Z	384	0	[ "license:apache-2.0", "region:us" ]	null	2023-11-03T05:47:44Z	--- license: apache-2.0 ---	[ -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, -0.3810413181781769, 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prachathai67k	null	2023-01-25T14:42:50Z	383	3	[ "task_categories:text-classification", "task_ids:topic-classification", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:unknown", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - en license: - unknown multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: - topic-classification paperswithcode_id: prachathai-67k pretty_name: prachathai67k dataset_info: features: - name: url dtype: string - name: date dtype: string - name: title dtype: string - name: body_text dtype: string - name: politics dtype: class_label: names: '0': neg '1': pos - name: human_rights dtype: class_label: names: '0': neg '1': pos - name: quality_of_life dtype: class_label: names: '0': neg '1': pos - name: international dtype: class_label: names: '0': neg '1': pos - name: social dtype: class_label: names: '0': neg '1': pos - name: environment dtype: class_label: names: '0': neg '1': pos - name: economics dtype: class_label: names: '0': neg '1': pos - name: culture dtype: class_label: names: '0': neg '1': pos - name: labor dtype: class_label: names: '0': neg '1': pos - name: national_security dtype: class_label: names: '0': neg '1': pos - name: ict dtype: class_label: names: '0': neg '1': pos - name: education dtype: class_label: names: '0': neg '1': pos config_name: prachathai67k splits: - name: train num_bytes: 865848436 num_examples: 54379 - name: validation num_bytes: 108641386 num_examples: 6721 - name: test num_bytes: 110034036 num_examples: 6789 download_size: 254240975 dataset_size: 1084523858 --- # Dataset Card for `prachathai67k` ## 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://github.com/PyThaiNLP/prachathai-67k - Repository: https://github.com/PyThaiNLP/prachathai-67k - Paper: - Leaderboard: - Point of Contact: https://github.com/PyThaiNLP/ ### Dataset Summary `prachathai-67k`: News Article Corpus and Multi-label Text Classificdation from Prachathai.com The `prachathai-67k` dataset was scraped from the news site [Prachathai](prachathai.com). We filtered out those articles with less than 500 characters of body text, mostly images and cartoons. It contains 67,889 articles wtih 12 curated tags from August 24, 2004 to November 15, 2018. The dataset was originally scraped by [@lukkiddd](https://github.com/lukkiddd) and cleaned by [@cstorm125](https://github.com/cstorm125). Download the dataset [here](https://www.dropbox.com/s/fsxepdka4l2pr45/prachathai-67k.zip?dl=1). You can also see preliminary exploration in [exploration.ipynb](https://github.com/PyThaiNLP/prachathai-67k/blob/master/exploration.ipynb). This dataset is a part of [pyThaiNLP](https://github.com/PyThaiNLP/) Thai text [classification-benchmarks](https://github.com/PyThaiNLP/classification-benchmarks). For the benchmark, we selected the following tags with substantial volume that resemble classifying types of articles: * `การเมือง` - politics * `สิทธิมนุษยชน` - human_rights * `คุณภาพชีวิต` - quality_of_life * `ต่างประเทศ` - international * `สังคม` - social * `สิ่งแวดล้อม` - environment * `เศรษฐกิจ` - economics * `วัฒนธรรม` - culture * `แรงงาน` - labor * `ความมั่นคง` - national_security * `ไอซีที` - ict * `การศึกษา` - education ### Supported Tasks and Leaderboards multi-label text classification, language modeling ### Languages Thai ## Dataset Structure ### Data Instances {'body_text': '17 พ.ย. 2558 Blognone [1] รายงานว่า กลุ่มแฮคเกอร์ Anonymous ประกาศสงครามไซเบอร์กับกลุ่มหัวรุนแรงหลังจากกลุ่ม IS ออกมาประกาศว่าเป็นผู้อยู่เบื้องหลังการโจมตีกรุงปารีสในคืนวันศุกร์ที่ผ่านมา\n\n\nภาพในคลิปใน YouTube โฆษกของกลุ่มแฮคเกอร์สวมหน้ากากที่เป็นสัญลักษณ์ของกลุ่มได้ออกมาอ่านแถลงเป็นภาษาฝรั่งเศส มีใจความว่า จากการโจมตีของกลุ่ม IS ในกรุงปารีส กลุ่ม Anonymous ทั่วโลกจะตามล่ากลุ่ม IS เหมือนที่เคยทำตอนที่มีการโจมตีสำนักพิมพ์ Charlie Hebdo และครั้งนี้จะเป็นปฏิบัติการโจมตีครั้งใหญ่ที่สุดของกลุ่ม Anonymous เลย นอกจากนี้กลุ่ม Anonymous ยังแสดงความเสียใจต่อครอบครัวผู้สูญเสียในเหตุการณ์ครั้งนี้\nกลุ่ม Anonymous เคยประกาศสงครามกับกลุ่ม IS หลังจากการโจมตีสำนักพิมพ์ Charlie Hebdo ที่ฝรั่งเศสเมื่อต้นปีที่ผ่านมา ซึ่งครั้งนั้นกลุ่ม Anonymous อ้างว่าได้ระงับบัญชีผู้ใช้งานที่เกี่ยวข้องกับ IS ไปหลายพันบัญชี (อ่านรายละเอียดเพิ่มเติม จากBlognone ที่\xa0\xa0กลุ่มแฮคเกอร์ Anonymous ประกาศสงครามไซเบอร์ขอกวาดล้างพวก ISIS [2])', 'culture': 0, 'date': '2015-11-17 18:14', 'economics': 0, 'education': 0, 'environment': 0, 'human_rights': 0, 'ict': 1, 'international': 1, 'labor': 0, 'national_security': 0, 'politics': 0, 'quality_of_life': 0, 'social': 0, 'title': 'แฮคเกอร์ Anonymous ลั่นทำสงครามไซเบอร์ครั้งใหญ่สุดกับกลุ่ม IS', 'url': 'https://prachatai.com/print/62490'} {'body_text': 'แถลงการณ์\n\n\xa0\n\nองค์การนักศึกษามหาวิทยาลัยธรรมศาสตร์\n\n\xa0\n\nมหาวิทยาลัยธรรมศาสตร์ก่อตั้งขึ้นภายใต้แนวคิดการให้การศึกษากับประชาชนเพื่อสนับสนุนการปกครองระบอบประชาธิปไตย อีกทั้งยังเป็นสถาบันหนึ่งที่อยู่เคียงข้างประชาชนมาโดยตลอด\n\n\xa0\n\nสถานการณ์สังคมไทยปัจจุบันได้เกิดความขัดแย้งทางการเมือง ทางแนวคิด จนลุกลามเป็นวิกฤตการณ์อันหาทางออกได้ยากยิ่ง องค์กรนักศึกษามหาวิทยาลัยธรรมศาสตร์ขอร้องเรียนและเสนอแนะต่อทุกฝ่าย โดยยึดหลักแนวทางตามรัฐธรรมนูญแห่งราชอาณาจักรไทย พ.ศ. ๒๕๕๐ อันเป็นกฎหมายสูงสุดในการจัดการปกครองรัฐ ที่มีผลบังคับใช้อยู่ในปัจจุบันซึ่งผ่านการประชามติจากปวงชนชาวไทยเมื่อวันที่ ๑๙ สิงหาคม พ.ศ. ๒๕๕๐ แล้วดังต่อนี้\n\n\xa0\n\n๑.การชุมชมโดยสงบและปราศจากอาวุธย่อมได้รับการคุ้มครองตามรัฐธรรมนูญ แต่หากการชุมนุมและเคลื่อนไหวของกลุ่มใดๆ มีการละเมิดสิทธิและเสรีภาพของผู้อื่นหรือก่อให้เกิดความเสียหายต่อชีวิตและทรัพย์สินของบุคคลและส่วนรวมนั้น ไม่สามารถกระทำได้ การใช้ความรุนแรง การกระทำอุกอาจต่างๆ ทั้งต่อบุคคลและทรัพย์สิน การยั่วยุ ปลุกระดมเพื่อหวังผลในการปะทะต่อสู้ จึงควรได้รับการกล่าวโทษ\n\n\xa0\n\nดังนั้นทั้งกลุ่มพันธมิตรประชาชนเพื่อประชาธิปไตย (พธม.) และกลุ่มแนวร่วมประชาธิปไตยไม่เอาเผด็จการแห่งชาติ (นปช.) จึงควรยอมรับกระบวนการตามกฎหมาย และหากถูกกล่าวหาไม่ว่ากรณีใดๆ ก็ควรพิสูจน์ความบริสุทธิ์โดยใช้กระบวนการยุติธรรม และหากจะยังชุมนุมต่อไปก็ยังคงทำได้ภายใต้บทบัญญัติแห่งกฎหมาย\n\n\xa0\n\nองค์กรนักศึกษามหาวิทยาลัยธรรมศาสตร์ จึงร้องขอให้หน่วยงานต่างๆ ที่เกี่ยวข้องดำเนินการตามกระบวนการทางกฎหมายกับการกระทำที่ผิดบทบัญญัติแห่งกฎหมายที่ทุกฝ่ายได้กระทำไป\n\n\xa0\n\n๒.นายสมัคร สุนทรเวช นายกรัฐมนตรี ไม่มีความเหมาะสมในการบริหารราชการแผ่นดินขาดหลักธรรมาภิบาล แต่ทั้งนี้นายสมัคร สุนทรเวช ยังคงยืนยันและกล่าวอ้างความชอบธรรมตามระบอบประชาธิปไตยภายใต้รัฐธรรมนูญ โดยไม่คำนึงถึงกระแสเรียกร้องใดๆ อันส่งผลให้ความขัดแย้งทางสังคมยิ่งบานปลายจนกลายเป็นวิกฤตการณ์เช่นปัจจุบัน ซึ่งก่อให้เกิดความเสียหายต่อประเทศแนวโน้มจะคลี่คลาย\n\n\xa0\n\nองค์การนักศึกษามหาวิทยาลัยธรรมศาสตร์ จึงเห็นว่า ควรใช้สิทธิตามรัฐธรรมนูญแห่งราชอาณาจักรไทย พุทธศักราช ๒๕๕๐ มาตรา ๑๖๔ โดยการเข้าชื่อเพื่อร้องต่อประธานวุฒิสภาเพื่อให้มีมติตามมาตรา ๒๗๔ ให้ถอดถอนนายสมัคร สุนทรเวช ออกจากตำแหน่งนายกรัฐมนตรีตามมาตรา ๒๗๐ ณ ลานโพ มหาวิทยาลัยธรรมศาสตร์ ท่าพระจันทร์ อาคารเรียนรวมสังคมศาสตร์ อาคารปิยชาติ และตึกกิจกรรมนักศึกษา มหาวิทยาลัยธรรมศาสตร์ ศูนย์รังสิต\n\n\xa0\n\n\xa0\n\nด้วยความสมานฉันท์\n\nองค์การนักศึกษามหาวิทยาลัยธรรมศาสตร์', 'culture': 0, 'date': '2008-09-06 03:36', 'economics': 0, 'education': 0, 'environment': 0, 'human_rights': 0, 'ict': 0, 'international': 0, 'labor': 0, 'national_security': 0, 'politics': 1, 'quality_of_life': 0, 'social': 0, 'title': 'แถลงการณ์ อมธ.แนะใช้สิทธิ ตาม รธน.เข้าชื่อร้องต่อประธานวุฒิสภาถอดถอน "สมัคร" จากตำแหน่งนายกฯ', 'url': 'https://prachatai.com/print/18038'} ### Data Fields - `url`: url of the article - `date`: date the article was published - `title`: title of the article - `body_text`: body text of the article - `politics`: 1 if sample has this tag else 0 - `human_rights`: 1 if sample has this tag else 0 - `quality_of_life`: 1 if sample has this tag else 0 - `international`: 1 if sample has this tag else 0 - `social`: 1 if sample has this tag else 0 - `environment`: 1 if sample has this tag else 0 - `economics`: 1 if sample has this tag else 0 - `culture`: 1 if sample has this tag else 0 - `labor`: 1 if sample has this tag else 0 - `national_security`: 1 if sample has this tag else 0 - `ict`: 1 if sample has this tag else 0 - `education`: 1 if sample has this tag else 0 ### Data Splits \| \| train \| valid \| test \| \|-------------------\|-------\|--------\|------\| \| # articles \| 54379 \| 6721 \| 6789 \| \| politics \| 31401 \| 3852 \| 3842 \| \| human_rights \| 12061 \| 1458 \| 1511 \| \| quality_of_life \| 9037 \| 1144 \| 1127 \| \| international \| 6432 \| 828 \| 834 \| \| social \| 6321 \| 782 \| 789 \| \| environment \| 6157 \| 764 \| 772 \| \| economics \| 3994 \| 487 \| 519 \| \| culture \| 3279 \| 388 \| 398 \| \| labor \| 2905 \| 375 \| 350 \| \| national_security \| 2865 \| 339 \| 338 \| \| ict \| 2326 \| 285 \| 292 \| \| education \| 2093 \| 248 \| 255 \| ## Dataset Creation ### Curation Rationale The data was scraped from the news site [Prachathai](prachathai.com) from August 24, 2004 to November 15, 2018. The initial intention was to use the dataset as a benchmark for Thai text classification. Due to the size of the dataset, it can also be used for language modeling. ### Source Data #### Initial Data Collection and Normalization 67,889 articles wtih 51,797 tags were scraped from the news site [Prachathai](prachathai.com) from August 24, 2004 to November 15, 2018. We filtered out those articles with less than 500 characters of body text, mostly images and cartoons. #### Who are the source language producers? Prachathai.com ### Annotations #### Annotation process Tags are annotated for the news website Prachathai.com #### Who are the annotators? We assume that the reporters who wrote the articles or other Prachathai staff gave each article its tags. ### Personal and Sensitive Information We do not expect any personal and sensitive information to be present since all data are public news articles. ## Considerations for Using the Data ### Social Impact of Dataset - classification benchmark for multi-label Thai text classification ### Discussion of Biases Prachathai.com is a left-leaning, human-right-focused news site, and thus unusual news labels such as human rights and quality of life. The news articles are expected to be left-leaning in contents. ### Other Known Limitations Dataset provided for research purposes only. Please check dataset license for additional information. ## Additional Information ### Dataset Curators PyThaiNLP ### Licensing Information CC-BY-NC ### Citation Information @misc{prachathai67k, author = {cstorm125, lukkiddd }, title = {prachathai67k}, year = {2019}, publisher = {GitHub}, journal = {GitHub repository}, howpublished={\\url{https://github.com/PyThaiNLP/prachathai-67k}}, } ### Contributions Thanks to [@cstorm125](https://github.com/cstorm125) for adding this dataset.	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sem_eval_2014_task_1	null	2023-01-25T14:43:53Z	383	1	[ "task_categories:text-classification", "task_ids:text-scoring", "task_ids:natural-language-inference", "task_ids:semantic-similarity-scoring", "annotations_creators:crowdsourced", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:extended\|other-ImageFlickr and SemEval-2012 STS MSR-Video Descriptions", "language:en", "license:cc-by-4.0", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - expert-generated language: - en license: - cc-by-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - extended\|other-ImageFlickr and SemEval-2012 STS MSR-Video Descriptions task_categories: - text-classification task_ids: - text-scoring - natural-language-inference - semantic-similarity-scoring pretty_name: SemEval 2014 - Task 1 dataset_info: features: - name: sentence_pair_id dtype: int64 - name: premise dtype: string - name: hypothesis dtype: string - name: relatedness_score dtype: float32 - name: entailment_judgment dtype: class_label: names: '0': NEUTRAL '1': ENTAILMENT '2': CONTRADICTION splits: - name: train num_bytes: 540296 num_examples: 4500 - name: test num_bytes: 592320 num_examples: 4927 - name: validation num_bytes: 60981 num_examples: 500 download_size: 197230 dataset_size: 1193597 --- # Dataset Card for SemEval 2014 - Task 1 ## 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: [SemEval-2014 Task 1](https://alt.qcri.org/semeval2014/task1/) - Repository: - Paper: [Aclweb](https://www.aclweb.org/anthology/S14-2001/) - 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 [@ashmeet13](https://github.com/ashmeet13) for adding this dataset.	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domenicrosati/TruthfulQA	domenicrosati	2022-07-01T15:41:54Z	383	4	[ "task_categories:question-answering", "task_ids:extractive-qa", "task_ids:open-domain-qa", "task_ids:closed-domain-qa", "annotations_creators:expert-generated", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:n<1K", "source_datasets:original", "language:en", "license:apache-2.0", "arxiv:2109.07958", "region:us" ]	[ "question-answering" ]	2022-05-12T00:38:33Z	--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - apache-2.0 multilinguality: - monolingual pretty_name: TruthfulQA size_categories: - n<1K source_datasets: - original task_categories: - question-answering task_ids: - extractive-qa - open-domain-qa - closed-domain-qa --- # Dataset Card for TruthfulQA ## 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) - [Contributions](#contributions) ## Dataset Description - Homepage: [https://github.com/sylinrl/TruthfulQA](https://github.com/sylinrl/TruthfulQA) - Repository: [https://github.com/sylinrl/TruthfulQA](https://github.com/sylinrl/TruthfulQA) - Paper: [https://arxiv.org/abs/2109.07958](https://arxiv.org/abs/2109.07958) ### Dataset Summary TruthfulQA: Measuring How Models Mimic Human Falsehoods We propose a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. We crafted questions that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts. We tested GPT-3, GPT-Neo/J, GPT-2 and a T5-based model. The best model was truthful on 58% of questions, while human performance was 94%. Models generated many false answers that mimic popular misconceptions and have the potential to deceive humans. The largest models were generally the least truthful. This contrasts with other NLP tasks, where performance improves with model size. However, this result is expected if false answers are learned from the training distribution. We suggest that scaling up models alone is less promising for improving truthfulness than fine-tuning using training objectives other than imitation of text from the web. ### Supported Tasks and Leaderboards See: [Tasks](https://github.com/sylinrl/TruthfulQA#tasks) ### Languages English ## Dataset Structure ### Data Instances The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. ### Data Fields 1. Type: Adversarial v Non-Adversarial Questions 2. Category: Category of misleading question 3. Question: The question 4. Best Answer: The best correct answer 5. Correct Answers: A set of correct answers. Delimited by `;`. 6. Incorrect Answers: A set of incorrect answers. Delimited by `;`. 7. Source: A source that supports the correct answers. ### Data Splits Due to constraints of huggingface the dataset is loaded into a "train" split. ### Contributions Thanks to [@sylinrl](https://github.com/sylinrl) for adding this dataset.	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rcds/wikipedia-for-mask-filling	rcds	2023-03-08T12:22:02Z	383	0	[ "task_categories:fill-mask", "annotations_creators:other", "language_creators:found", "multilinguality:multilingual", "size_categories:10M<n<100M", "source_datasets:original", "language:en", "license:cc-by-4.0", "region:us" ]	[ "fill-mask" ]	2023-01-23T15:14:48Z	--- annotations_creators: - other language_creators: - found language: - en license: - cc-by-4.0 multilinguality: - multilingual paperswithcode_id: null pretty_name: "wikipedia pages chunked for fill-mask" size_categories: - 10M<n<100M source_datasets: - original task_categories: - fill-mask --- # preprocessed version of rcds/wikipedia-persons-masked ## 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 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 Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text is masked with a <mask> token. The ground truth for every mask is provided. Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk. for each chunk the expected name for each mask is given. ### Supported Tasks and Leaderboards The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering, e.g. "Who is <mask>?" ### Languages english only ## Dataset Structure In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens. Use the dataset like this: ```python from datasets import load_dataset dataset = load_dataset('rcds/wikipedia-persons-masked', split='train', type='original', size='512') ``` ### Data Fields Columns are: - texts: the text chunks - masks: the names for each of the masks in the chunks ### Data Splits There are no splits, only a default train. ## Dataset Creation Created by using the tokenizer from allenai/longformer-base-4096 for the 4096 token per chunk version, and the xml-roberta-large tokenizer for the 512 token version. Chunks are split to fit those token sizes, with the splits ensuring no words are split in half. Possible improvements: Last chunk of a page might be much shorter, could join part of the previous one to have more tokens in the last chunk. ### 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 ``` TODO add citation ``` ### Contributions Thanks to [@skatinger](https://github.com/skatinger) for adding this dataset.	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tum-nlp/IDMGSP	tum-nlp	2023-09-12T11:57:59Z	383	3	[ "task_categories:text-classification", "size_categories:10K<n<100K", "language:en", "license:openrail++", "scientific paper", "fake papers", "science", "scientific text", "region:us" ]	[ "text-classification" ]	2023-05-27T12:20:55Z	--- viewer: true task_categories: - text-classification language: - en tags: - scientific paper - fake papers - science - scientific text pretty_name: ' A Benchmark Dataset for Identifying Machine-Generated Scientific Papers in the LLM Era (IDMGSP)' size_categories: - 10K<n<100K dataset_info: - config_name: classifier_input features: - name: id dtype: string - name: year dtype: string - name: title dtype: string - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: categories dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 70117904 num_examples: 16000 - name: test num_bytes: 34724993 num_examples: 8000 download_size: 32157176 dataset_size: 104842897 - config_name: tecg features: - name: id dtype: string - name: year dtype: string - name: title dtype: string - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: categories dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: test num_bytes: 2408633 num_examples: 1000 download_size: 582824 dataset_size: 2408633 - config_name: train+gpt3 features: - name: id dtype: string - name: year dtype: string - name: title dtype: string - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: categories dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 73586425 num_examples: 17200 download_size: 22487536 dataset_size: 73586425 - config_name: train-cg features: - name: id dtype: string - name: year dtype: string - name: title dtype: string - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: categories dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 65261576 num_examples: 14000 download_size: 20272344 dataset_size: 65261576 - config_name: ood_gpt3 features: - name: title dtype: string - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 3454121 num_examples: 1200 - name: test num_bytes: 2837275 num_examples: 1000 download_size: 1708501 dataset_size: 6291396 - config_name: ood_real features: - name: abstract dtype: string - name: introduction dtype: string - name: conclusion dtype: string - name: src dtype: string - name: label dtype: int64 splits: - name: test num_bytes: 15808225 num_examples: 4000 download_size: 5336873 dataset_size: 15808225 license: openrail++ --- # Dataset Card for A Benchmark Dataset for Identifying Machine-Generated Scientific Papers in the LLM Era ## Dataset Description - Repository: https://github.com/qwenzo/-IDMGSP - Paper: TODO ### Dataset Summary A benchmark for detecting machine-generated scientific papers based on their abstract, introduction and conclusion sections. ### Supported Tasks and Leaderboards current benchmark results in terms of accuracy: \| Model \| Train Dataset \| TEST \| OOD-GPT3 \| OOD-REAL \| TECG \| TEST-CC \| \|-----------------------------\|-----------------\|---------\|----------\|----------\|---------\|---------\| \| LR-1gram (tf-idf) (our) \| TRAIN \| 95.3% \| 4.0% \| 94.6% \| 96.1% \| 7.8% \| \| LR-1gram (tf-idf) (our) \| TRAIN+GPT3 \| 94.6% \| 86.5% \| 86.2% \| 97.8% \| 13.7% \| \| LR-1gram (tf-idf) (our) \| TRAIN-CG \| 86.6% \| 0.8% \| 97.8% \| 32.6% \| 1.2% \| \| RF-1gram (tf-idf) (our) \| TRAIN \| 94.8% \| 24.7% \| 87.3% \| 100.0% \| 8.1% \| \| RF-1gram (tf-idf) (our) \| TRAIN+GPT3 \| 91.7% \| 95.0% \| 69.3% \| 100.0% \| 15.1% \| \| RF-1gram (tf-idf) (our) \| TRAIN-CG \| 97.6% \| 7.0% \| 95.0% \| 57.0% \| 1.7% \| \| [IDMGSP-Galactica-TRAIN](https://huggingface.co/tum-nlp/IDMGSP-Galactica-TRAIN) (our) \| TRAIN \| 98.4% \| 25.9% \| 95.5% \| 84.0% \| 6.8% \| \| [IDMGSP-Galactica-TRAIN_GPT3](https://huggingface.co/tum-nlp/IDMGSP-Galactica-TRAIN_GPT3) (our) \| TRAIN+GPT3 \| 98.5% \| 71.2% \| 95.1% \| 84.0% \| 12.0% \| \| [IDMGSP-Galactica-TRAIN-CG](https://huggingface.co/tum-nlp/IDMGSP-Galactica-TRAIN-CG) (our) \| TRAIN-CG \| 96.4% \| 12.4% \| 97.6% \| 61.3% \| 2.4% \| \| [IDMGSP-RoBERTa-TRAIN-ABSTRACT](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-ABSTRACT) + [IDMGSP-RoBERTa-TRAIN-INTRODUCTION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-INTRODUCTION) + [IDMGSP-RoBERTa-TRAIN-CONCLUSION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-CONCLUSION) (our) \| TRAIN \| 72.3% \| 55.5% \| 50.0% \| 100.0% \| 63.5% \| \| [IDMGSP-RoBERTa-TRAIN_GPT3-ABSTRACT](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN_GPT3-ABSTRACT) + [IDMGSP-RoBERTa-TRAIN_GPT3-INTRODUCTION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN_GPT3-INTRODUCTION) + [IDMGSP-RoBERTa-TRAIN_GPT3-CONCLUSION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN_GPT3-CONCLUSION) (our) \| TRAIN+GPT3 \| 65.7% \| 100.0% \| 29.1% \| 100.0% \| 75.0% \| \| [IDMGSP-RoBERTa-TRAIN-CG-ABSTRACT](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-CG-ABSTRACT) + [IDMGSP-RoBERTa-TRAIN-CG-INTRODUCTION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-CG-INTRODUCTION) + [IDMGSP-RoBERTa-TRAIN-CG-CONCLUSION](https://huggingface.co/tum-nlp/IDMGSP-RoBERTa-TRAIN-CG-CONCLUSION) (our) \| TRAIN-CG \| 86.0% \| 2.0% \| 92.5% \| 76.5% \| 9.2% \| \| GPT-3 (our) \| TRAIN-SUB \| 100.0% \| 25.9% \| 99.0% \| 100.0% \| N/A \| \| DetectGPT \| - \| 61.5% \| 0.0% \| 99.9% \| 68.7% \| N/A \| \| ChatGPT-IO (our)* \| - \| 69.0% \| 49.0% \| 89.0% \| 0.0% \| 3.0% \| \| LLMFE (our)* \| TRAIN+GPT3 \| 80.0% \| 62.0% \| 70.0% \| 90.0% \| 33.0% \| ### Languages English ## Dataset Structure ### Data Instances Each instance in the dataset corresponds to a row in a CSV file, encompassing the features of a paper, its label, and the paper's source. ### Data Fields #### classifier_input - name: id description: The ID of the provided paper corresponds to the identifier assigned by the arXiv database if the paper's source is marked as "real". dtype: string - name: year description: year of the publication as given by the arXiv database. dtype: string - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: categories description: topics/domains of the paper given by the arXiv database. This field is null if the src field is not "real". dtype: string - name: src description: indicator of the source of the paper. This can have the values "chatgpt", "gpt2", "real", "scigen" or "galactica". dtype: string - name: label description: 0 for real/human-written papers and 1 for fake/machine-generated papers. dtype: int64 #### train+gpt3 - name: id description: The ID of the provided paper corresponds to the identifier assigned by the arXiv database if the paper's source is marked as "real". dtype: string - name: year description: year of the publication as given by the arXiv database. dtype: string - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: categories description: topics/domains of the paper given by the arXiv database. This field is null if the src field is not "real". dtype: string - name: src description: indicator of the source of the paper. This can have the values "chatgpt", "gpt2", "real", "scigen" or "galactica", "gpt3". dtype: string - name: label description: 0 for real/human-written papers and 1 for fake/machine-generated papers. dtype: int64 #### tecg - name: id description: The ID of the provided paper corresponds to the identifier assigned by the arXiv database if the paper's source is marked as "real". dtype: string - name: year description: year of the publication as given by the arXiv database. dtype: string - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: categories description: topics/domains of the paper given by the arXiv database. This field is null if the src field is not "real". dtype: string - name: src description: indicator of the source of the paper. Always has the value "chatgpt". dtype: string - name: label description: always having the value 1. dtype: int64 #### train-cg - name: id description: The ID of the provided paper corresponds to the identifier assigned by the arXiv database if the paper's source is marked as "real". dtype: string - name: year description: year of the publication as given by the arXiv database. dtype: string - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: categories description: topics/domains of the paper given by the arXiv database. This field is null if the src field is not "real". dtype: string - name: src description: indicator of the source of the paper. This can have the values "gpt2", "real", "scigen" or "galactica". dtype: string - name: label description: 0 for real/human-written papers and 1 for fake/machine-generated papers. dtype: int64 #### ood_gpt3 - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: src description: indicator of the source of the paper. Has the value "gpt3". dtype: string - name: label description: always having the value 1. dtype: int64 #### ood_real dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: src description: indicator of the source of the paper. Has the value "ood_real". dtype: string - name: label description: always having the value 0. dtype: int64 #### test-cc - name: id description: The ID of the provided paper corresponds to the identifier assigned by the arXiv database if the paper's source is marked as "real". dtype: string - name: year description: year of the publication as given by the arXiv database. dtype: string - name: title description: title of the paper given by the arXiv database. dtype: string - name: abstract description: abstract of the paper given by the arXiv database. dtype: string - name: introduction description: introduction section of the paper. extracted by the PDF parser. dtype: string - name: conclusion description: conclusion section of the paper. extracted by the PDF parser. dtype: string - name: categories description: topics/domains of the paper given by the arXiv database. This field is null if the src field is not "real". dtype: string - name: src description: indicator of the source of the paper. Always has the value "chatgpt-paraphrased". dtype: string - name: paraphrased_sections description: indicator of which sections are paraphrased. Can have the values "introduction", "conclusion", "introduction, conclusion", "abstract, introduction, conclusion". dtype: string - name: label description: 0 for real/human-written papers and 1 for fake/machine-generated papers. Always has the value 1. dtype: int64 ### Data Splits Table: Overview of the datasets used to train and evaluate the classifiers. \| Dataset \| arXiv \| ChatGPT \| GPT-2 \| SCIgen \| Galactica \| GPT-3 \| ChatGPT (co-created) \| \|--------------------------------------\|--------\|---------\|--------\|--------\|-----------\|--------\|-----------------------\| \| Standard train (TRAIN) \| 8k \| 2k \| 2k \| 2k \| 2k \| - \| - \| \| Standard train subset (TRAIN-SUB) \| 4k \| 1k \| 1k \| 1k \| 1k \| - \| - \| \| TRAIN without ChatGPT (TRAIN-CG) \| 8k \| - \| 2k \| 2k \| 2k \| - \| - \| \| TRAIN plus GPT-3 (TRAIN+GPT3) \| 8k \| 2k \| 2k \| 2k \| 2k \| 1.2k \| - \| \| Standard test (TEST) \| 4k \| 1k \| 1k \| 1k \| 1k \| - \| - \| \| Out-of-domain GPT-3 only (OOD-GPT3) \| - \| - \| - \| - \| - \| 1k \| - \| \| Out-of-domain real (OOD-REAL) \| 4k (parsing 2) \| - \| - \| - \| - \| - \| - \| \| ChatGPT only (TECG) \| - \| 1k \| - \| - \| - \| - \| - \| \| Co-created test (TEST-CC) \| - \| - \| - \| - \| - \| - \| 4k \| [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]	[ -0.5326294898986816, -0.4483482241630554, 0.32723572850227356, 0.1926955282688141, -0.24006535112857819, 0.0659346655011177, -0.0180067028850317, -0.4552440345287323, 0.37699422240257263, 0.1762402057647705, -0.3819463551044464, -0.8000426888465881, -0.6556932330131531, 0.33156007528305054, -0.21199828386306763, 1.284864068031311, -0.1904575228691101, 0.018765781074762344, -0.2436230480670929, -0.36419010162353516, 0.104640893638134, -0.45217546820640564, -0.44861775636672974, 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open-llm-leaderboard/details_PulsarAI__Chat-AYB-Platypus2-13B	open-llm-leaderboard	2023-10-28T16:53:53Z	383	0	[ "region:us" ]	null	2023-10-08T14:46:28Z	--- pretty_name: Evaluation run of PulsarAI/Chat-AYB-Platypus2-13B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [PulsarAI/Chat-AYB-Platypus2-13B](https://huggingface.co/PulsarAI/Chat-AYB-Platypus2-13B)\ \ 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_PulsarAI__Chat-AYB-Platypus2-13B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T16:53:41.047162](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Chat-AYB-Platypus2-13B/blob/main/results_2023-10-28T16-53-41.047162.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\": 0.2752726510067114,\n\ \ \"em_stderr\": 0.0045741300617909856,\n \"f1\": 0.38116505872483314,\n\ \ \"f1_stderr\": 0.004403649120675284,\n \"acc\": 0.3936315988829403,\n\ \ \"acc_stderr\": 0.0083541228301978\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.2752726510067114,\n \"em_stderr\": 0.0045741300617909856,\n\ \ \"f1\": 0.38116505872483314,\n \"f1_stderr\": 0.004403649120675284\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.029567854435178165,\n \ \ \"acc_stderr\": 0.004665893134220814\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7576953433307024,\n \"acc_stderr\": 0.012042352526174785\n\ \ }\n}\n```" repo_url: https://huggingface.co/PulsarAI/Chat-AYB-Platypus2-13B 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_10_08T14_46_05.202813 path: - '/details_harness\|arc:challenge\|25_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-08T14-46-05.202813.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T16_53_41.047162 path: - '/details_harness\|drop\|3_2023-10-28T16-53-41.047162.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T16-53-41.047162.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T16_53_41.047162 path: - '/details_harness\|gsm8k\|5_2023-10-28T16-53-41.047162.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T16-53-41.047162.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hellaswag\|10_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T14-46-05.202813.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T14-46-05.202813.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T14_46_05.202813 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T14-46-05.202813.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T14-46-05.202813.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T16_53_41.047162 path: - '/details_harness\|winogrande\|5_2023-10-28T16-53-41.047162.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T16-53-41.047162.parquet' - config_name: results data_files: - split: 2023_10_08T14_46_05.202813 path: - results_2023-10-08T14-46-05.202813.parquet - split: 2023_10_28T16_53_41.047162 path: - results_2023-10-28T16-53-41.047162.parquet - split: latest path: - results_2023-10-28T16-53-41.047162.parquet --- # Dataset Card for Evaluation run of PulsarAI/Chat-AYB-Platypus2-13B ## Dataset Description - Homepage: - Repository: https://huggingface.co/PulsarAI/Chat-AYB-Platypus2-13B - 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 [PulsarAI/Chat-AYB-Platypus2-13B](https://huggingface.co/PulsarAI/Chat-AYB-Platypus2-13B) 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_PulsarAI__Chat-AYB-Platypus2-13B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T16:53:41.047162](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Chat-AYB-Platypus2-13B/blob/main/results_2023-10-28T16-53-41.047162.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": 0.2752726510067114, "em_stderr": 0.0045741300617909856, "f1": 0.38116505872483314, "f1_stderr": 0.004403649120675284, "acc": 0.3936315988829403, "acc_stderr": 0.0083541228301978 }, "harness\|drop\|3": { "em": 0.2752726510067114, "em_stderr": 0.0045741300617909856, "f1": 0.38116505872483314, "f1_stderr": 0.004403649120675284 }, "harness\|gsm8k\|5": { "acc": 0.029567854435178165, "acc_stderr": 0.004665893134220814 }, "harness\|winogrande\|5": { "acc": 0.7576953433307024, "acc_stderr": 0.012042352526174785 } } ``` ### 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]	[ -0.35784581303596497, -0.738506555557251, 0.12237770110368729, 0.3943372070789337, -0.14933264255523682, 0.13054680824279785, -0.45145460963249207, -0.13099725544452667, 0.4189697504043579, 0.5177459120750427, -0.7304238080978394, -0.8021358847618103, -0.6733026504516602, 0.17334645986557007, -0.16364076733589172, 1.1339738368988037, -0.11612112820148468, -0.25546708703041077, 0.022470790892839432, -0.2568204700946808, -0.34491175413131714, -0.4477059841156006, -0.5833900570869446, 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id_newspapers_2018	null	2022-11-03T16:16:15Z	382	4	[ "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:id", "license:cc-by-4.0", "region:us" ]	[ "text-generation", "fill-mask" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - id license: - cc-by-4.0 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: Indonesian Newspapers 2018 dataset_info: features: - name: id dtype: string - name: url dtype: string - name: date dtype: string - name: title dtype: string - name: content dtype: string config_name: id_newspapers_2018 splits: - name: train num_bytes: 1116031922 num_examples: 499164 download_size: 446018349 dataset_size: 1116031922 --- # Dataset Card for Indonesian Newspapers 2018 ## 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: [Indonesian Newspapers](https://github.com/feryandi/Dataset-Artikel) - Repository: [Indonesian Newspapers](https://github.com/feryandi/Dataset-Artikel) - Paper: - Leaderboard: - Point of Contact: [[email protected]](mailto:[email protected]), [[email protected]](mailto:[email protected]) ### Dataset Summary The dataset contains around 500K articles (136M of words) from 7 Indonesian newspapers: Detik, Kompas, Tempo, CNN Indonesia, Sindo, Republika and Poskota. The articles are dated between 1st January 2018 and 20th August 2018 (with few exceptions dated earlier). The size of uncompressed 500K json files (newspapers-json.tgz) is around 2.2GB, and the cleaned uncompressed in a big text file (newspapers.txt.gz) is about 1GB. The original source in Google Drive contains also a dataset in html format which include raw data (pictures, css, javascript, ...) from the online news website. A copy of the original dataset is available at https://cloud.uncool.ai/index.php/s/mfYEAgKQoY3ebbM ### Supported Tasks and Leaderboards [More Information Needed] ### Languages Indonesian ## Dataset Structure ``` { 'id': 'string', 'url': 'string', 'date': 'string', 'title': 'string', 'content': 'string' } ``` ### Data Instances An instance from the dataset is ``` {'id': '0', 'url': 'https://www.cnnindonesia.com/olahraga/20161221234219-156-181385/lorenzo-ingin-samai-rekor-rossi-dan-stoner', 'date': '2016-12-22 07:00:00', 'title': 'Lorenzo Ingin Samai Rekor Rossi dan Stoner', 'content': 'Jakarta, CNN Indonesia -- Setelah bergabung dengan Ducati, Jorge Lorenzo berharap bisa masuk dalam jajaran pebalap yang mampu jadi juara dunia kelas utama dengan dua pabrikan berbeda. Pujian Max Biaggi untuk Valentino Rossi Jorge Lorenzo Hadir dalam Ucapan Selamat Natal Yamaha Iannone: Saya Sering Jatuh Karena Ingin yang Terbaik Sepanjang sejarah, hanya ada lima pebalap yang mampu jadi juara kelas utama (500cc/MotoGP) dengan dua pabrikan berbeda, yaitu Geoff Duke, Giacomo Agostini, Eddie Lawson, Valentino Rossi, dan Casey Stoner. Lorenzo ingin bergabung dalam jajaran legenda tersebut. “Fakta ini sangat penting bagi saya karena hanya ada lima pebalap yang mampu menang dengan dua pabrikan berbeda dalam sejarah balap motor.” “Kedatangan saya ke Ducati juga menghadirkan tantangan yang sangat menarik karena hampir tak ada yang bisa menang dengan Ducati sebelumnya, kecuali Casey Stoner. Hal itu jadi motivasi yang sangat bagus bagi saya,” tutur Lorenzo seperti dikutip dari Crash Lorenzo saat ini diliputi rasa penasaran yang besar untuk menunggang sepeda motor Desmosedici yang dipakai tim Ducati karena ia baru sekali menjajal motor tersebut pada sesi tes di Valencia, usai MotoGP musim 2016 berakhir. “Saya sangat tertarik dengan Ducati arena saya hanya memiliki kesempatan mencoba motor itu di Valencia dua hari setelah musim berakhir. Setelah itu saya tak boleh lagi menjajalnya hingga akhir Januari mendatang. Jadi saya menjalani penantian selama dua bulan yang panjang,” kata pebalap asal Spanyol ini. Dengan kondisi tersebut, maka Lorenzo memanfaatkan waktu yang ada untuk liburan dan melepaskan penat. “Setidaknya apa yang terjadi pada saya saat ini sangat bagus karena saya jadi memiliki waktu bebas dan sedikit liburan.” “Namun tentunya saya tak akan larut dalam liburan karena saya harus lebih bersiap, terutama dalam kondisi fisik dibandingkan sebelumnya, karena saya akan menunggangi motor yang sulit dikendarai,” ucap Lorenzo. Selama sembilan musim bersama Yamaha, Lorenzo sendiri sudah tiga kali jadi juara dunia, yaitu pada 2010, 2012, dan 2015. (kid)'} ``` ### Data Fields - `id`: id of the sample - `url`: the url to the original article - `date`: the publishing date of the article - `title`: the title of the article - `content`: the content of the article ### Data Splits The dataset contains train set of 499164 samples. ## 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 This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The dataset is shared for the sole purpose of aiding open scientific research in Bahasa Indonesia (computing or linguistics), and can only be used for that purpose. The ownership of each article within the dataset belongs to the respective newspaper from which it was extracted; and the maintainer of the repository does not claim ownership of any of the content within it. If you think, by any means, that this dataset breaches any established copyrights; please contact the repository maintainer. ### Citation Information [N/A] ### Contributions Thanks to [@cahya-wirawan](https://github.com/cahya-wirawan) for adding this dataset.	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GEM/schema_guided_dialog	GEM	2022-10-24T15:30:26Z	382	3	[ "task_categories:conversational", "annotations_creators:crowd-sourced", "language_creators:unknown", "multilinguality:unknown", "size_categories:unknown", "source_datasets:original", "language:en", "license:cc-by-sa-4.0", "dialog-response-generation", "arxiv:1909.05855", "arxiv:2004.15006", "arxiv:2002.01359", "region:us" ]	[ "conversational" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowd-sourced language_creators: - unknown language: - en license: - cc-by-sa-4.0 multilinguality: - unknown size_categories: - unknown source_datasets: - original task_categories: - conversational task_ids: [] pretty_name: schema_guided_dialog tags: - dialog-response-generation --- # Dataset Card for GEM/schema_guided_dialog ## Dataset Description - Homepage: n/a - Repository: [Github[(https://github.com/google-research-datasets/dstc8-schema-guided-dialogue) - Paper: https://arxiv.org/abs/1909.05855 - Leaderboard: N/A - Point of Contact: Abhinav Rastogi ### Link to Main Data Card You can find the main data card on the [GEM Website](https://gem-benchmark.com/data_cards/schema_guided_dialog). ### Dataset Summary The GEM version of this dataset functions as a response generation dataset. The input specifies dialog acts that a model needs to verbalize. The Schema-Guided Dialog dataset is challenging since it comprises multiple domains from hotel and travel to restaurants, and a wide range of dialog acts. The context of each conversation is provided as well. You can load the dataset via: ``` import datasets data = datasets.load_dataset('GEM/schema_guided_dialog') ``` The data loader can be found [here](https://huggingface.co/datasets/GEM/schema_guided_dialog). #### website n/a #### paper [Arxiv](https://arxiv.org/abs/1909.05855) #### authors Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, Pranav Khaitan, Amir Fayazi, Maria Wang, and Guan-Lin Chao ## Dataset Overview ### Where to find the Data and its Documentation #### Download <!-- info: What is the link to where the original dataset is hosted? --> <!-- scope: telescope --> [Github[(https://github.com/google-research-datasets/dstc8-schema-guided-dialogue) #### Paper <!-- info: What is the link to the paper describing the dataset (open access preferred)? --> <!-- scope: telescope --> [Arxiv](https://arxiv.org/abs/1909.05855) #### BibTex <!-- info: Provide the BibTex-formatted reference for the dataset. Please use the correct published version (ACL anthology, etc.) instead of google scholar created Bibtex. --> <!-- scope: microscope --> ``` { @inproceedings{rastogi2020towards, title={Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset}, author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, volume={34}, number={05}, pages={8689--8696}, year={2020} } ``` #### Contact Name <!-- quick --> <!-- info: If known, provide the name of at least one person the reader can contact for questions about the dataset. --> <!-- scope: periscope --> Abhinav Rastogi #### Contact Email <!-- info: If known, provide the email of at least one person the reader can contact for questions about the dataset. --> <!-- scope: periscope --> [email protected] #### Has a Leaderboard? <!-- info: Does the dataset have an active leaderboard? --> <!-- scope: telescope --> no ### Languages and Intended Use #### Multilingual? <!-- quick --> <!-- info: Is the dataset multilingual? --> <!-- scope: telescope --> no #### Covered Languages <!-- quick --> <!-- info: What languages/dialects are covered in the dataset? --> <!-- scope: telescope --> `English` #### Whose Language? <!-- info: Whose language is in the dataset? --> <!-- scope: periscope --> The language structure is machine-generated, and the language realizations are produced by crowd workers. The dataset paper does not provide demographic information for the crowd workers. #### License <!-- quick --> <!-- info: What is the license of the dataset? --> <!-- scope: telescope --> cc-by-sa-4.0: Creative Commons Attribution Share Alike 4.0 International #### Intended Use <!-- info: What is the intended use of the dataset? --> <!-- scope: microscope --> The Schema-Guided Dialogue (SGD) dataset contains 18K multi-domain task-oriented dialogues between a human and a virtual assistant, which covers 17 domains ranging from banks and events to media, calendar, travel, and weather. The language presents in the datset is only English. The SGD dataset provides a challenging testbed for a number of tasks in task-oriented dialogue, including language understanding, slot filling, dialogue state tracking and response generation. For the creation of the SGD dataset, they developed a multi-domain dialogue simulator that generates dialogue outlines over an arbitrary combination of APIs, dialogue states and system actions. Then, they used a crowd-sourcing procedure to paraphrase these outlines to natural language utterances. This novel crowd-sourcing procedure preserves all annotations obtained from the simulator and does not require any extra annotations after dialogue collection. #### Primary Task <!-- info: What primary task does the dataset support? --> <!-- scope: telescope --> Dialog Response Generation #### Communicative Goal <!-- quick --> <!-- info: Provide a short description of the communicative goal of a model trained for this task on this dataset. --> <!-- scope: periscope --> The goal of a speaker who generates the target utterance is to help users accomplish tasks including but not limited to finding flights, booking restaurants, searching for nearby events and movies. ### Credit #### Curation Organization Type(s) <!-- info: In what kind of organization did the dataset curation happen? --> <!-- scope: telescope --> `industry` #### Curation Organization(s) <!-- info: Name the organization(s). --> <!-- scope: periscope --> Google #### Dataset Creators <!-- info: Who created the original dataset? List the people involved in collecting the dataset and their affiliation(s). --> <!-- scope: microscope --> Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, Pranav Khaitan, Amir Fayazi, Maria Wang, and Guan-Lin Chao #### Funding <!-- info: Who funded the data creation? --> <!-- scope: microscope --> Google #### Who added the Dataset to GEM? <!-- info: Who contributed to the data card and adding the dataset to GEM? List the people+affiliations involved in creating this data card and who helped integrate this dataset into GEM. --> <!-- scope: microscope --> Wanyu Du wrote the initial data card and Yacine Jernite the data loader. Simon Mille updated the data card with the additional splits. Sebastian Gehrmann migrated the data card and loader to the v2 version and extended the missing information. ### Dataset Structure #### Data Fields <!-- info: List and describe the fields present in the dataset. --> <!-- scope: telescope --> Each dialog instance has the following fields: * `dialogue_id`: A unique identifier for a dialogue. * `services`: A list of services present in the dialogue. * `turns`: A list of annotated system or user utterances. Each turn consists of the following fields: * `speaker`: The speaker for the turn, either `USER` or `SYSTEM`. * `utterance`: A string containing the natural language utterance. * `frames`: A list of frames, each frame containing annotations for a single service and consists of the following fields: * `service`: The name of the service corresponding to the frame. The slots and intents used in the following fields are taken from the schema of this service. * `slots`: A list of slot spans in the utterance, only provided for non-categorical slots. Each slot span contains the following fields: * `slot`: The name of the slot. * `start`: The index of the starting character in the utterance corresponding to the slot value. * `exclusive_end`: The index of the character just after the last character corresponding to the slot value in the utterance. * `actions`: A list of actions corresponding to the system. Each action has the following fields: * `act`: The type of action. * `slot`: (optional) A slot argument for some of the actions. * `values`: (optional) A list of values assigned to the slot. If the values list is non-empty, then the slot must be present. * `canonical_values`: (optional) The values in their canonicalized form as used by the service. It is a list of strings of the same length as values. * `service_call`: (system turns only, optional) The request sent to the service. It consists of the following fields: * `method`: The name of the intent or function of the service or API being executed. * `parameters`: A pair of lists of the same lengths: `parameter_slot_name` contains slot names and `parameter_canonical_value` contains the corresponding values in their canonicalized form. * `service_results`: (system turns only, optional) A list of entities containing the results obtained from the service. It is only available for turns in which a service call is made. Each entity is represented as a pair of lists of the same length: `service_slot_name` contains slot names and `service_canonical_value` contains the corresponding canonical values. * `state`: (user turns only) The dialogue state corresponding to the service. It consists of the following fields: * `active_intent`: The intent corresponding to the service of the frame which is currently being fulfilled by the system. It takes the value "NONE" if none of the intents are active. * `requested_slots`: A list of slots requested by the user in the current turn. * `slot_values`: A pair of lists of the same lengths: `slot_name` contains slot names and `slot_value_list` contains the corresponding lists of strings. For categorical slots, this list contains a single value assigned to the slot. For non-categorical slots, all the values in this list are spoken variations of each other and are equivalent (e.g, "6 pm", "six in the evening", "evening at 6" etc.). #### Example Instance <!-- info: Provide a JSON formatted example of a typical instance in the dataset. --> <!-- scope: periscope --> ``` {'dialogue_id': '1_00000', 'services': ['Restaurants_1'], 'turns': {'frames': [{'actions': [{'act': [6], 'canonical_values': [['FindRestaurants']], 'slot': ['intent'], 'values': [['FindRestaurants']]}], 'service': ['Restaurants_1'], 'service_call': [{'method': '', 'parameters': {'parameter_canonical_value': [], 'parameter_slot_name': []}}], 'service_results': [{'service_results_list': []}], 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}], 'state': [{'active_intent': 'FindRestaurants', 'requested_slots': [], 'slot_values': {'slot_name': [], 'slot_value_list': []}}]}, {'actions': [{'act': [13], 'canonical_values': [[]], 'slot': ['city'], 'values': [[]]}], 'service': ['Restaurants_1'], 'service_call': [{'method': '', 'parameters': {'parameter_canonical_value': [], 'parameter_slot_name': []}}], 'service_results': [{'service_results_list': []}], 'slots': [{'exclusive_end': [], 'slot': [], 'start': []}], 'state': [{'active_intent': '', 'requested_slots': [], 'slot_values': {'slot_name': [], 'slot_value_list': []}}]}, ...,]} 'speaker': [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1], 'utterance': [ 'I am feeling hungry so I would like to find a place to eat.', 'Do you have a specific which you want the eating place to be located at?', 'I would like for it to be in San Jose.', 'Is there a specific cuisine type you enjoy, such as Mexican, Italian or something else?', 'I usually like eating the American type of food.', 'I see that at 71 Saint Peter there is a good restaurant which is in San Jose.', 'Can you give me the address of this restaurant.', 'If you want to go to this restaurant you can find it at 71 North San Pedro Street.', 'Can you give me the phone number that I can contact them with?', 'If you want to phone them you can at 408-971-8523.', 'Is there some other restaurant which you can suggest?', 'How would you like Bazille restaurant which is situated in San Jose.', 'Do you have another restaurant matching my needs? For example a restaurant which is economical and is located in Palo Alto.', 'I see that 7 restaurants suit to what you requested. Bird Dog seems as a good restaurant and is located in Palo Alto.', 'Alright, that seems good. I would like to make a booking at this restaurant.', 'For which time do you want the booking to be?', 'I will be eating there at 11:30 am so make it for then.', 'Can you please confirm that you want to book a table for 2 at 11:30 am at the Bird Dog restaurant in Palo Alto for today.', 'That suits me well. Can you tell me if they feature live music?', 'Your booking has been made without errors, but unfortunately they do not have live music.', 'Will I be able to find liquor there? Can you give me the address of their location?', 'The restaurant is located at 420 Ramona Street. Unfortunately they do not serve alcohol at the restaurant.', 'I appreciate it very much. That would be all.', 'Have a good time!' ]} ``` #### Data Splits <!-- info: Describe and name the splits in the dataset if there are more than one. --> <!-- scope: periscope --> The dataset is split into a train, validation, and test set with the following sizes: \| \| Train \| Validation \| Test \| \| --- \| --- \| --- \| --- \| \| \# of dialogues \| 16142 \| 2482 \| 4201 \| \| \# of turns \| 48426 \| 7446 \| 12603 \| #### Splitting Criteria <!-- info: Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g., if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here. --> <!-- scope: microscope --> The data is generally split i.i.d, but some topics only appear in training and some only for testing. For example, the domains Messaging, Payment, and Train are test-only. ## Dataset in GEM ### Rationale for Inclusion in GEM #### Why is the Dataset in GEM? <!-- info: What does this dataset contribute toward better generation evaluation and why is it part of GEM? --> <!-- scope: microscope --> This dataset comprises a wide range of dialog capabilities and thus enables the evaluation of many more generation capabilities of comparable datasets. Its collection methodology ensures a high diversity but also high quality of the data. #### Similar Datasets <!-- info: Do other datasets for the high level task exist? --> <!-- scope: telescope --> yes #### Unique Language Coverage <!-- info: Does this dataset cover other languages than other datasets for the same task? --> <!-- scope: periscope --> no #### Difference from other GEM datasets <!-- info: What else sets this dataset apart from other similar datasets in GEM? --> <!-- scope: microscope --> The domains a lot more diverse than other datasets. #### Ability that the Dataset measures <!-- info: What aspect of model ability can be measured with this dataset? --> <!-- scope: periscope --> surface realization, compositionality. ### GEM-Specific Curation #### Modificatied for GEM? <!-- info: Has the GEM version of the dataset been modified in any way (data, processing, splits) from the original curated data? --> <!-- scope: telescope --> yes #### GEM Modifications <!-- info: What changes have been made to he original dataset? --> <!-- scope: periscope --> `data points modified` #### Modification Details <!-- info: For each of these changes, described them in more details and provided the intended purpose of the modification --> <!-- scope: microscope --> We are focusing on the response-generation part of the dataset and thus reformatted the dataset to treat the service agent utterances as the targets to be generated and the previous customer utterance and the agent's dialog act as the input. We additionally reformat the dialog acts to directly conform to the format described in this [paper](https://arxiv.org/abs/2004.15006). #### Additional Splits? <!-- info: Does GEM provide additional splits to the dataset? --> <!-- scope: telescope --> yes #### Split Information <!-- info: Describe how the new splits were created --> <!-- scope: periscope --> 9 challenge sets for Schema-Guided Dialog were added to the GEM evaluation suite. 1. We created subsets of the training and development sets of 500 randomly selected inputs each. 2. We applied 5 transformations to respectively 5 sets of 500 randomly selected inputs: (i) back-translation, (ii)-(iii) introduction of typographical errors, using Butterfingers with two thresholds (0.02 and 0.05), resulting in two sets with different amounts of typos introduced (there are more typos with the 0.05 threshold than with the 0.02 one), (iv) removal of final punctuations (when any), and (v) input scrambling, for which the order of the dialogue acts was randomly reassigned. 3. For the input size, we created subpopulations based on the number of dialogue acts in the input. \| DA number \| Frequency English \| \|---------------\|-------------------\| \| 1 \| 5049 \| \| 2 \| 2517 \| \| 3 \| 1328 \| \| 4 \| 469 \| \| 5 \| 335 \| \| 6 \| 256 \| \| 7 \| 46 \| We also split the test data according to the type of dialogue act, represented by cardinal numbers in the dataset. \| DA type \| Frequency English \| \|--------------\|-------------------\| \| 2 \| 1397 \| \| 3 \| 983 \| \| 4 \| 1027 \| \| 5 \| 958 \| \| 9 \| 72 \| \| 10 \| 1024 \| \| 11 \| 1246 \| \| 12 \| 500 \| \| 13 \| 2078 \| \| 15 \| 715 \| #### Split Motivation <!-- info: What aspects of the model's generation capacities were the splits created to test? --> <!-- scope: periscope --> Generalization and Robustness. ### Getting Started with the Task #### Pointers to Resources <!-- info: Getting started with in-depth research on the task. Add relevant pointers to resources that researchers can consult when they want to get started digging deeper into the task. --> <!-- scope: microscope --> * [Paper for dataset and DST baseline](https://arxiv.org/pdf/1909.05855.pdf) * [DSTC8 overview paper](https://arxiv.org/pdf/2002.01359.pdf) * [Code for DST baseline](https://github.com/google-research/google-research/tree/master/schema_guided_dst) * [Natural language generation baseline paper](https://arxiv.org/pdf/2004.15006.pdf) * [Blog post announcing the dataset](https://ai.googleblog.com/2019/10/introducing-schema-guided-dialogue.html) ## Previous Results ### Previous Results #### Measured Model Abilities <!-- info: What aspect of model ability can be measured with this dataset? --> <!-- scope: telescope --> Surface realization and compositionally. #### Metrics <!-- info: What metrics are typically used for this task? --> <!-- scope: periscope --> `BLEURT`, `BLEU`, `ROUGE` #### Proposed Evaluation <!-- info: List and describe the purpose of the metrics and evaluation methodology (including human evaluation) that the dataset creators used when introducing this task. --> <!-- scope: microscope --> The original paper focused on the task of dialog state prediction instead of response generation and thus did not suggest any set of metrics. #### Previous results available? <!-- info: Are previous results available? --> <!-- scope: telescope --> no ## Dataset Curation ### Original Curation #### Original Curation Rationale <!-- info: Original curation rationale --> <!-- scope: telescope --> Previous multi-domain task-oriented dialogue datsets do not sufficiently capture the real-world challenges in virtual assistants, since they cover few domains and assume a single static ontology per domain. The SGD datset is created to cover 17 domains with over 16K dialogues, and contain multiple different APIs in most domains, many of which have overlapping functionalities but different interfaces, which reflects common real-world scenarios. The wide range of available annotations can be used for intent prediction, slot filling, dialogue state tracking, policy imitation learning, language generation, user simulation learning, among other tasks in large-scale virtual assistants. #### Communicative Goal <!-- info: What was the communicative goal? --> <!-- scope: periscope --> The goal of a speaker who generates the target utterance is to help users accomplish tasks including but not limited to finding flights, booking restaurants, searching for nearby events and movies. #### Sourced from Different Sources <!-- info: Is the dataset aggregated from different data sources? --> <!-- scope: telescope --> no ### Language Data #### How was Language Data Obtained? <!-- info: How was the language data obtained? --> <!-- scope: telescope --> `Machine-generated` #### Generation Method Link <!-- info: If text was machine-generated for the dataset, provide a link to the generation method if available (N/A otherwise). --> <!-- scope: periscope --> [Github](https://github.com/google-research-datasets/dstc8-schema-guided-dialogue) #### Language Producers <!-- info: What further information do we have on the language producers? --> <!-- scope: microscope --> The dialogue outlines are first generated by a simulator. The dialogue simulator interacts with the services to generate dialogue outlines. It consists of two agents playing the roles of the user and the system, interacting with each other using a finite set of actions specified through dialogue acts over a probabilistic automaton designed to capture varied dialogue trajectories. It is worth noting that the simulation automaton does not include any domain-specific constraints: all domain-specific constraints are encoded in the schema and scenario. The dialogue paraphrasing framework then converts the outlines generated by the simulator into a natural conversation. Users may refer to the slot values in the dialogue acts in various different ways during the conversation, e.g., “los angeles” may be referred to as “LA” or “LAX”. To introduce these natural variations in the slot values, different slot values are replaced with a randomly selected variation while being kept consistent across user turns in a dialogue. The actions are then converted to pseudo-natural language utterances using a set of manually defined action-to-text templates, and the resulting utterances for the different actions in a turn are concatenated together. #### Topics Covered <!-- info: Does the language in the dataset focus on specific topics? How would you describe them? --> <!-- scope: periscope --> The dataset covers the following domains: Alarm, Banks, Buses, Calendar, Events, Flights, Homes, Hotels, Media, Messaging, Movies, Music, Payment, RentalCars, Restaurants, RideSharing, Services, Train, Travel, and Weather. The domain ‘Service’ includes salons, dentists, doctors etc. The ‘Alarm’, ‘Messaging’, ‘Payment’ and ‘Train’ domains are only present in the dev or test sets. to test generalization to new domains. #### Data Validation <!-- info: Was the text validated by a different worker or a data curator? --> <!-- scope: telescope --> not validated #### Was Data Filtered? <!-- info: Were text instances selected or filtered? --> <!-- scope: telescope --> not filtered ### Structured Annotations #### Additional Annotations? <!-- quick --> <!-- info: Does the dataset have additional annotations for each instance? --> <!-- scope: telescope --> crowd-sourced #### Number of Raters <!-- info: What is the number of raters --> <!-- scope: telescope --> unknown #### Raters per Training Example <!-- info: How many annotators saw each training example? --> <!-- scope: periscope --> 0 #### Raters per Test Example <!-- info: How many annotators saw each test example? --> <!-- scope: periscope --> 0 #### Annotation Service? <!-- info: Was an annotation service used? --> <!-- scope: telescope --> unknown #### Annotation Values <!-- info: Purpose and values for each annotation --> <!-- scope: microscope --> The dialogue transformed by these steps is sent to the crowd workers to be reformulated into more natural language. One crowd worker is tasked with paraphrasing all utterances of a dialogue to ensure naturalness and coherence. The crowd workers are asked to exactly repeat the slot values in their paraphrases so that the span indices for the slots can be recovered via string matching. #### Any Quality Control? <!-- info: Quality control measures? --> <!-- scope: telescope --> none ### Consent #### Any Consent Policy? <!-- info: Was there a consent policy involved when gathering the data? --> <!-- scope: telescope --> no #### Justification for Using the Data <!-- info: If not, what is the justification for reusing the data? --> <!-- scope: microscope --> While no policy is reported, we assume that one was in place for the collection. ### Private Identifying Information (PII) #### Contains PII? <!-- quick --> <!-- info: Does the source language data likely contain Personal Identifying Information about the data creators or subjects? --> <!-- scope: telescope --> no PII #### Justification for no PII <!-- info: Provide a justification for selecting `no PII` above. --> <!-- scope: periscope --> The SGD dataset does not use identity categories and does not contain sensitive data. ### Maintenance #### Any Maintenance Plan? <!-- info: Does the original dataset have a maintenance plan? --> <!-- scope: telescope --> no ## Broader Social Context ### Previous Work on the Social Impact of the Dataset #### Usage of Models based on the Data <!-- info: Are you aware of cases where models trained on the task featured in this dataset ore related tasks have been used in automated systems? --> <!-- scope: telescope --> no ### Impact on Under-Served Communities #### Addresses needs of underserved Communities? <!-- info: Does this dataset address the needs of communities that are traditionally underserved in language technology, and particularly language generation technology? Communities may be underserved for exemple because their language, language variety, or social or geographical context is underepresented in NLP and NLG resources (datasets and models). --> <!-- scope: telescope --> no ### Discussion of Biases #### Any Documented Social Biases? <!-- info: Are there documented social biases in the dataset? Biases in this context are variations in the ways members of different social categories are represented that can have harmful downstream consequences for members of the more disadvantaged group. --> <!-- scope: telescope --> no #### Are the Language Producers Representative of the Language? <!-- info: Does the distribution of language producers in the dataset accurately represent the full distribution of speakers of the language world-wide? If not, how does it differ? --> <!-- scope: periscope --> Due to the combination of the automatic generation and crowd rater paraphasing, the language can be very formulaic. While this may be acceptable for the model part (i.e., we may actually desire an automated agent to form formulaic responses), the input utterances of the simulated customers likely do not cover the entire spectrum of the English language. ## Considerations for Using the Data ### PII Risks and Liability ### Licenses #### Copyright Restrictions on the Dataset <!-- info: Based on your answers in the Intended Use part of the Data Overview Section, which of the following best describe the copyright and licensing status of the dataset? --> <!-- scope: periscope --> `open license - commercial use allowed` #### Copyright Restrictions on the Language Data <!-- info: Based on your answers in the Language part of the Data Curation Section, which of the following best describe the copyright and licensing status of the underlying language data? --> <!-- scope: periscope --> `open license - commercial use allowed` ### Known Technical Limitations #### Technical Limitations <!-- info: Describe any known technical limitations, such as spurrious correlations, train/test overlap, annotation biases, or mis-annotations, and cite the works that first identified these limitations when possible. --> <!-- scope: microscope --> The dialogues under each domain distributed unevenly, where the flights domain has 3644 dialogues while the payment domain only contains 222 dialogues. Besides, all dialogues are paraphrased by crowd-workers, and it is possible that crow-workers with different culture backgrounds will exhibit biased opinions. #### Unsuited Applications <!-- info: When using a model trained on this dataset in a setting where users or the public may interact with its predictions, what are some pitfalls to look out for? In particular, describe some applications of the general task featured in this dataset that its curation or properties make it less suitable for. --> <!-- scope: microscope --> Since the initial data was automatically generated, the coverage of entity names is necessarily biased. An agent thus needs to be evaluated in a more realistic environment.	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keremberke/license-plate-object-detection	keremberke	2023-01-18T20:37:51Z	382	10	[ "task_categories:object-detection", "roboflow", "roboflow2huggingface", "Self Driving", "Anpr", "region:us" ]	[ "object-detection" ]	2023-01-01T02:32:07Z	--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Self Driving - Anpr --- <div align="center"> <img width="640" alt="keremberke/license-plate-object-detection" src="https://huggingface.co/datasets/keremberke/license-plate-object-detection/resolve/main/thumbnail.jpg"> </div> ### Dataset Labels ``` ['license_plate'] ``` ### Number of Images ```json {'train': 6176, 'valid': 1765, 'test': 882} ``` ### How to Use - Install [datasets](https://pypi.org/project/datasets/): ```bash pip install datasets ``` - Load the dataset: ```python from datasets import load_dataset ds = load_dataset("keremberke/license-plate-object-detection", name="full") example = ds['train'][0] ``` ### Roboflow Dataset Page [https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1](https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1?ref=roboflow2huggingface) ### Citation ``` @misc{ vehicle-registration-plates-trudk_dataset, title = { Vehicle Registration Plates Dataset }, type = { Open Source Dataset }, author = { Augmented Startups }, howpublished = { \\url{ https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk } }, url = { https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2022 }, month = { jun }, note = { visited on 2023-01-18 }, } ``` ### License CC BY 4.0 ### Dataset Summary This dataset was exported via roboflow.ai on January 13, 2022 at 5:20 PM GMT It includes 8823 images. VRP are annotated in COCO format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) No image augmentation techniques were applied.	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open-llm-leaderboard/details_layoric__llama-2-13b-code-alpaca	open-llm-leaderboard	2023-09-17T08:33:42Z	382	0	[ "region:us" ]	null	2023-08-17T23:50:19Z	--- pretty_name: Evaluation run of layoric/llama-2-13b-code-alpaca dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [layoric/llama-2-13b-code-alpaca](https://huggingface.co/layoric/llama-2-13b-code-alpaca)\ \ 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_layoric__llama-2-13b-code-alpaca\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T08:33:30.933109](https://huggingface.co/datasets/open-llm-leaderboard/details_layoric__llama-2-13b-code-alpaca/blob/main/results_2023-09-17T08-33-30.933109.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\": 0.0018875838926174498,\n\ \ \"em_stderr\": 0.00044451099905589575,\n \"f1\": 0.06352139261744941,\n\ \ \"f1_stderr\": 0.001394404442569597,\n \"acc\": 0.4415195195231134,\n\ \ \"acc_stderr\": 0.010426765880718628\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0018875838926174498,\n \"em_stderr\": 0.00044451099905589575,\n\ \ \"f1\": 0.06352139261744941,\n \"f1_stderr\": 0.001394404442569597\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.11902956785443518,\n \ \ \"acc_stderr\": 0.008919702911161632\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7640094711917916,\n \"acc_stderr\": 0.011933828850275625\n\ \ }\n}\n```" repo_url: https://huggingface.co/layoric/llama-2-13b-code-alpaca 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_24T14_43_19.893957 path: - '/details_harness\|arc:challenge\|25_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-24T14:43:19.893957.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T08_33_30.933109 path: - '/details_harness\|drop\|3_2023-09-17T08-33-30.933109.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T08-33-30.933109.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T08_33_30.933109 path: - '/details_harness\|gsm8k\|5_2023-09-17T08-33-30.933109.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T08-33-30.933109.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hellaswag\|10_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-24T14:43:19.893957.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-24T14:43:19.893957.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_24T14_43_19.893957 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-24T14:43:19.893957.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-24T14:43:19.893957.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T08_33_30.933109 path: - '/details_harness\|winogrande\|5_2023-09-17T08-33-30.933109.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T08-33-30.933109.parquet' - config_name: results data_files: - split: 2023_07_24T14_43_19.893957 path: - results_2023-07-24T14:43:19.893957.parquet - split: 2023_09_17T08_33_30.933109 path: - results_2023-09-17T08-33-30.933109.parquet - split: latest path: - results_2023-09-17T08-33-30.933109.parquet --- # Dataset Card for Evaluation run of layoric/llama-2-13b-code-alpaca ## Dataset Description - Homepage: - Repository: https://huggingface.co/layoric/llama-2-13b-code-alpaca - 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 [layoric/llama-2-13b-code-alpaca](https://huggingface.co/layoric/llama-2-13b-code-alpaca) 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_layoric__llama-2-13b-code-alpaca", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T08:33:30.933109](https://huggingface.co/datasets/open-llm-leaderboard/details_layoric__llama-2-13b-code-alpaca/blob/main/results_2023-09-17T08-33-30.933109.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": 0.0018875838926174498, "em_stderr": 0.00044451099905589575, "f1": 0.06352139261744941, "f1_stderr": 0.001394404442569597, "acc": 0.4415195195231134, "acc_stderr": 0.010426765880718628 }, "harness\|drop\|3": { "em": 0.0018875838926174498, "em_stderr": 0.00044451099905589575, "f1": 0.06352139261744941, "f1_stderr": 0.001394404442569597 }, "harness\|gsm8k\|5": { "acc": 0.11902956785443518, "acc_stderr": 0.008919702911161632 }, "harness\|winogrande\|5": { "acc": 0.7640094711917916, "acc_stderr": 0.011933828850275625 } } ``` ### 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]	[ -0.40312328934669495, -0.6331356763839722, 0.1700109839439392, 0.3329610824584961, -0.26776567101478577, 0.15934599936008453, -0.3630434572696686, -0.25019779801368713, 0.5055723786354065, 0.5442447066307068, -0.6792141795158386, -0.9384939670562744, -0.7652981281280518, 0.1999702900648117, -0.19440875947475433, 1.1704378128051758, -0.3018770217895508, -0.29851198196411133, 0.06882654875516891, -0.36093056201934814, -0.38474810123443604, -0.39468035101890564, -0.4224148392677307, 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open-llm-leaderboard/details_The-Face-Of-Goonery__Chronos-Beluga-v2-13bfp16	open-llm-leaderboard	2023-09-18T19:11:18Z	382	0	[ "region:us" ]	null	2023-08-18T11:08:57Z	--- pretty_name: Evaluation run of The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16](https://huggingface.co/The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16)\ \ 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_The-Face-Of-Goonery__Chronos-Beluga-v2-13bfp16\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-18T19:11:05.927806](https://huggingface.co/datasets/open-llm-leaderboard/details_The-Face-Of-Goonery__Chronos-Beluga-v2-13bfp16/blob/main/results_2023-09-18T19-11-05.927806.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\": 0.1196518456375839,\n\ \ \"em_stderr\": 0.0033237364616341856,\n \"f1\": 0.18612311241610655,\n\ \ \"f1_stderr\": 0.003456805841321019,\n \"acc\": 0.3921054253509362,\n\ \ \"acc_stderr\": 0.009071968047164727\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.1196518456375839,\n \"em_stderr\": 0.0033237364616341856,\n\ \ \"f1\": 0.18612311241610655,\n \"f1_stderr\": 0.003456805841321019\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.04624715693707354,\n \ \ \"acc_stderr\": 0.005784991662691891\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7379636937647988,\n \"acc_stderr\": 0.012358944431637561\n\ \ }\n}\n```" repo_url: https://huggingface.co/The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 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_09T10_53_07.090454 path: - '/details_harness\|arc:challenge\|25_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-09T10:53:07.090454.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_18T19_11_05.927806 path: - '/details_harness\|drop\|3_2023-09-18T19-11-05.927806.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-18T19-11-05.927806.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_18T19_11_05.927806 path: - '/details_harness\|gsm8k\|5_2023-09-18T19-11-05.927806.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-18T19-11-05.927806.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hellaswag\|10_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T10:53:07.090454.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-09T10:53:07.090454.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T10_53_07.090454 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T10:53:07.090454.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-09T10:53:07.090454.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_18T19_11_05.927806 path: - '/details_harness\|winogrande\|5_2023-09-18T19-11-05.927806.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-18T19-11-05.927806.parquet' - config_name: results data_files: - split: 2023_08_09T10_53_07.090454 path: - results_2023-08-09T10:53:07.090454.parquet - split: 2023_09_18T19_11_05.927806 path: - results_2023-09-18T19-11-05.927806.parquet - split: latest path: - results_2023-09-18T19-11-05.927806.parquet --- # Dataset Card for Evaluation run of The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 ## Dataset Description - Homepage: - Repository: https://huggingface.co/The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 - 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 [The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16](https://huggingface.co/The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16) 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_The-Face-Of-Goonery__Chronos-Beluga-v2-13bfp16", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-18T19:11:05.927806](https://huggingface.co/datasets/open-llm-leaderboard/details_The-Face-Of-Goonery__Chronos-Beluga-v2-13bfp16/blob/main/results_2023-09-18T19-11-05.927806.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": 0.1196518456375839, "em_stderr": 0.0033237364616341856, "f1": 0.18612311241610655, "f1_stderr": 0.003456805841321019, "acc": 0.3921054253509362, "acc_stderr": 0.009071968047164727 }, "harness\|drop\|3": { "em": 0.1196518456375839, "em_stderr": 0.0033237364616341856, "f1": 0.18612311241610655, "f1_stderr": 0.003456805841321019 }, "harness\|gsm8k\|5": { "acc": 0.04624715693707354, "acc_stderr": 0.005784991662691891 }, "harness\|winogrande\|5": { "acc": 0.7379636937647988, "acc_stderr": 0.012358944431637561 } } ``` ### 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]	[ -0.34336745738983154, -0.631991446018219, 0.2574955224990845, 0.17623940110206604, -0.1863091140985489, 0.08878885209560394, -0.31726884841918945, -0.2711634635925293, 0.3630257546901703, 0.5598978996276855, -0.7995741963386536, -0.8047120571136475, -0.672258734703064, 0.15130139887332916, -0.08804619312286377, 1.2189557552337646, -0.13114652037620544, -0.14645794034004211, 0.09055834263563156, -0.21998529136180878, -0.30516278743743896, -0.40578991174697876, -0.5893092155456543, 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result-kand2-sdxl-wuerst-karlo/f719c86e	result-kand2-sdxl-wuerst-karlo	2023-11-08T23:40:52Z	382	0	[ "region:us" ]	null	2023-11-08T23:40:51Z	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 224 num_examples: 10 download_size: 1403 dataset_size: 224 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "f719c86e" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.6776092052459717, -0.14316704869270325, 0.29251861572265625, 0.24693284928798676, -0.35949909687042236, -0.12796512246131897, 0.40234610438346863, -0.23435577750205994, 0.8497984409332275, 0.5146872997283936, -0.7929778695106506, -0.6528156995773315, -0.6062765121459961, -0.22798658907413483, -0.23621010780334473, 0.9742282032966614, 0.08735490590333939, 0.07976018637418747, -0.3583762049674988, -0.04831130802631378, 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code_x_glue_cc_code_to_code_trans	null	2023-07-27T14:11:43Z	381	3	[ "task_categories:translation", "annotations_creators:expert-generated", "language_creators:found", "multilinguality:other-programming-languages", "size_categories:10K<n<100K", "source_datasets:original", "language:code", "license:c-uda", "code-to-code", "arxiv:2102.04664", "region:us" ]	[ "translation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - found language: - code license: - c-uda multilinguality: - other-programming-languages size_categories: - 10K<n<100K source_datasets: - original task_categories: - translation task_ids: [] pretty_name: CodeXGlueCcCodeToCodeTrans tags: - code-to-code dataset_info: features: - name: id dtype: int32 - name: java dtype: string - name: cs dtype: string splits: - name: train num_bytes: 4372657 num_examples: 10300 - name: validation num_bytes: 226415 num_examples: 500 - name: test num_bytes: 418595 num_examples: 1000 download_size: 4876035 dataset_size: 5017667 --- # Dataset Card for "code_x_glue_cc_code_to_code_trans" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits-sample-size) - [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://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans - Paper: https://arxiv.org/abs/2102.04664 ### Dataset Summary CodeXGLUE code-to-code-trans dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans The dataset is collected from several public repos, including Lucene(http://lucene.apache.org/), POI(http://poi.apache.org/), JGit(https://github.com/eclipse/jgit/) and Antlr(https://github.com/antlr/). We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets. ### Supported Tasks and Leaderboards - `machine-translation`: The dataset can be used to train a model for translating code in Java to C# and vice versa. ### Languages - Java programming language - C# programming language ## Dataset Structure ### Data Instances An example of 'validation' looks as follows. ``` { "cs": "public DVRecord(RecordInputStream in1){_option_flags = in1.ReadInt();_promptTitle = ReadUnicodeString(in1);_errorTitle = ReadUnicodeString(in1);_promptText = ReadUnicodeString(in1);_errorText = ReadUnicodeString(in1);int field_size_first_formula = in1.ReadUShort();_not_used_1 = in1.ReadShort();_formula1 = NPOI.SS.Formula.Formula.Read(field_size_first_formula, in1);int field_size_sec_formula = in1.ReadUShort();_not_used_2 = in1.ReadShort();_formula2 = NPOI.SS.Formula.Formula.Read(field_size_sec_formula, in1);_regions = new CellRangeAddressList(in1);}\n", "id": 0, "java": "public DVRecord(RecordInputStream in) {_option_flags = in.readInt();_promptTitle = readUnicodeString(in);_errorTitle = readUnicodeString(in);_promptText = readUnicodeString(in);_errorText = readUnicodeString(in);int field_size_first_formula = in.readUShort();_not_used_1 = in.readShort();_formula1 = Formula.read(field_size_first_formula, in);int field_size_sec_formula = in.readUShort();_not_used_2 = in.readShort();_formula2 = Formula.read(field_size_sec_formula, in);_regions = new CellRangeAddressList(in);}\n" } ``` ### Data Fields In the following each data field in go is explained for each config. The data fields are the same among all splits. #### default \|field name\| type \| description \| \|----------\|------\|-----------------------------\| \|id \|int32 \| Index of the sample \| \|java \|string\| The java version of the code\| \|cs \|string\| The C# version of the code \| ### Data Splits \| name \|train\|validation\|test\| \|-------\|----:\|---------:\|---:\| \|default\|10300\| 500\|1000\| ## 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 https://github.com/microsoft, https://github.com/madlag ### Licensing Information Computational Use of Data Agreement (C-UDA) License. ### Citation Information ``` @article{DBLP:journals/corr/abs-2102-04664, author = {Shuai Lu and Daya Guo and Shuo Ren and Junjie Huang and Alexey Svyatkovskiy and Ambrosio Blanco and Colin B. Clement and Dawn Drain and Daxin Jiang and Duyu Tang and Ge Li and Lidong Zhou and Linjun Shou and Long Zhou and Michele Tufano and Ming Gong and Ming Zhou and Nan Duan and Neel Sundaresan and Shao Kun Deng and Shengyu Fu and Shujie Liu}, title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding and Generation}, journal = {CoRR}, volume = {abs/2102.04664}, year = {2021} } ``` ### Contributions Thanks to @madlag (and partly also @ncoop57) for adding this dataset.	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open-llm-leaderboard/details_mosaicml__mpt-7b	open-llm-leaderboard	2023-10-03T22:11:49Z	381	0	[ "region:us" ]	null	2023-08-27T11:51:44Z	--- pretty_name: Evaluation run of mosaicml/mpt-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mosaicml/mpt-7b](https://huggingface.co/mosaicml/mpt-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 122 configuration, each one coresponding to one of\ \ the evaluated task.\n\nThe dataset has been created from 4 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_mosaicml__mpt-7b\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-10-03T22:10:31.153532](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b/blob/main/results_2023-10-03T22-10-31.153532.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\": 0.28815728428182913,\n\ \ \"acc_stderr\": 0.032729017222815425,\n \"acc_norm\": 0.2923951167846347,\n\ \ \"acc_norm_stderr\": 0.032718180607395383,\n \"mc1\": 0.20563035495716034,\n\ \ \"mc1_stderr\": 0.014148482219460974,\n \"mc2\": 0.3354506043570123,\n\ \ \"mc2_stderr\": 0.013110323313593984\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.42918088737201365,\n \"acc_stderr\": 0.014464085894870653,\n\ \ \"acc_norm\": 0.47696245733788395,\n \"acc_norm_stderr\": 0.014595873205358269\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5730930093606851,\n\ \ \"acc_stderr\": 0.004936176784631949,\n \"acc_norm\": 0.7753435570603465,\n\ \ \"acc_norm_stderr\": 0.0041650291643616005\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-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\": 0.2631578947368421,\n \"acc_stderr\": 0.03583496176361062,\n\ \ \"acc_norm\": 0.2631578947368421,\n \"acc_norm_stderr\": 0.03583496176361062\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|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-clinical_knowledge\|5\"\ : {\n \"acc\": 0.28679245283018867,\n \"acc_stderr\": 0.027834912527544067,\n\ \ \"acc_norm\": 0.28679245283018867,\n \"acc_norm_stderr\": 0.027834912527544067\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2847222222222222,\n\ \ \"acc_stderr\": 0.03773809990686935,\n \"acc_norm\": 0.2847222222222222,\n\ \ \"acc_norm_stderr\": 0.03773809990686935\n },\n \"harness\|hendrycksTest-college_chemistry\|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-college_computer_science\|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_mathematics\|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-college_medicine\|5\": {\n \"acc\": 0.2658959537572254,\n\ \ \"acc_stderr\": 0.033687629322594295,\n \"acc_norm\": 0.2658959537572254,\n\ \ \"acc_norm_stderr\": 0.033687629322594295\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617747,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617747\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.3404255319148936,\n \"acc_stderr\": 0.03097669299853442,\n\ \ \"acc_norm\": 0.3404255319148936,\n \"acc_norm_stderr\": 0.03097669299853442\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2894736842105263,\n\ \ \"acc_stderr\": 0.04266339443159394,\n \"acc_norm\": 0.2894736842105263,\n\ \ \"acc_norm_stderr\": 0.04266339443159394\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\"\ : 0.23809523809523808,\n \"acc_stderr\": 0.021935878081184763,\n \"\ acc_norm\": 0.23809523809523808,\n \"acc_norm_stderr\": 0.021935878081184763\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.23015873015873015,\n\ \ \"acc_stderr\": 0.03764950879790605,\n \"acc_norm\": 0.23015873015873015,\n\ \ \"acc_norm_stderr\": 0.03764950879790605\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.25161290322580643,\n\ \ \"acc_stderr\": 0.024685979286239952,\n \"acc_norm\": 0.25161290322580643,\n\ \ \"acc_norm_stderr\": 0.024685979286239952\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.20689655172413793,\n \"acc_stderr\": 0.02850137816789395,\n\ \ \"acc_norm\": 0.20689655172413793,\n \"acc_norm_stderr\": 0.02850137816789395\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.24242424242424243,\n \"acc_stderr\": 0.033464098810559534,\n\ \ \"acc_norm\": 0.24242424242424243,\n \"acc_norm_stderr\": 0.033464098810559534\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.2222222222222222,\n \"acc_stderr\": 0.02962022787479047,\n \"\ acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02962022787479047\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.35751295336787564,\n \"acc_stderr\": 0.03458816042181006,\n\ \ \"acc_norm\": 0.35751295336787564,\n \"acc_norm_stderr\": 0.03458816042181006\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.32051282051282054,\n \"acc_stderr\": 0.02366129639396427,\n\ \ \"acc_norm\": 0.32051282051282054,\n \"acc_norm_stderr\": 0.02366129639396427\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340496,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340496\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.28991596638655465,\n \"acc_stderr\": 0.029472485833136098,\n\ \ \"acc_norm\": 0.28991596638655465,\n \"acc_norm_stderr\": 0.029472485833136098\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.26055045871559634,\n \"acc_stderr\": 0.018819182034850068,\n \"\ acc_norm\": 0.26055045871559634,\n \"acc_norm_stderr\": 0.018819182034850068\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.3055555555555556,\n \"acc_stderr\": 0.03141554629402544,\n \"\ acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.03141554629402544\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.2549019607843137,\n \"acc_stderr\": 0.030587591351604257,\n \"\ acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.030587591351604257\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\": 0.3094170403587444,\n\ \ \"acc_stderr\": 0.031024411740572203,\n \"acc_norm\": 0.3094170403587444,\n\ \ \"acc_norm_stderr\": 0.031024411740572203\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.29770992366412213,\n \"acc_stderr\": 0.04010358942462203,\n\ \ \"acc_norm\": 0.29770992366412213,\n \"acc_norm_stderr\": 0.04010358942462203\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2975206611570248,\n \"acc_stderr\": 0.04173349148083498,\n \"\ acc_norm\": 0.2975206611570248,\n \"acc_norm_stderr\": 0.04173349148083498\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\": 0.25153374233128833,\n \"acc_stderr\": 0.034089978868575295,\n\ \ \"acc_norm\": 0.25153374233128833,\n \"acc_norm_stderr\": 0.034089978868575295\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.36607142857142855,\n\ \ \"acc_stderr\": 0.0457237235873743,\n \"acc_norm\": 0.36607142857142855,\n\ \ \"acc_norm_stderr\": 0.0457237235873743\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.23300970873786409,\n \"acc_stderr\": 0.041858325989283136,\n\ \ \"acc_norm\": 0.23300970873786409,\n \"acc_norm_stderr\": 0.041858325989283136\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.32051282051282054,\n\ \ \"acc_stderr\": 0.03057281131029961,\n \"acc_norm\": 0.32051282051282054,\n\ \ \"acc_norm_stderr\": 0.03057281131029961\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.3001277139208174,\n\ \ \"acc_stderr\": 0.016389249691317425,\n \"acc_norm\": 0.3001277139208174,\n\ \ \"acc_norm_stderr\": 0.016389249691317425\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.2630057803468208,\n \"acc_stderr\": 0.023703099525258172,\n\ \ \"acc_norm\": 0.2630057803468208,\n \"acc_norm_stderr\": 0.023703099525258172\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2446927374301676,\n\ \ \"acc_stderr\": 0.014378169884098423,\n \"acc_norm\": 0.2446927374301676,\n\ \ \"acc_norm_stderr\": 0.014378169884098423\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.28104575163398693,\n \"acc_stderr\": 0.025738854797818726,\n\ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.025738854797818726\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2990353697749196,\n\ \ \"acc_stderr\": 0.02600330111788513,\n \"acc_norm\": 0.2990353697749196,\n\ \ \"acc_norm_stderr\": 0.02600330111788513\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.32098765432098764,\n \"acc_stderr\": 0.025976566010862737,\n\ \ \"acc_norm\": 0.32098765432098764,\n \"acc_norm_stderr\": 0.025976566010862737\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.24822695035460993,\n \"acc_stderr\": 0.025770015644290392,\n \ \ \"acc_norm\": 0.24822695035460993,\n \"acc_norm_stderr\": 0.025770015644290392\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2607561929595828,\n\ \ \"acc_stderr\": 0.011213471559602325,\n \"acc_norm\": 0.2607561929595828,\n\ \ \"acc_norm_stderr\": 0.011213471559602325\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.1948529411764706,\n \"acc_stderr\": 0.024060599423487414,\n\ \ \"acc_norm\": 0.1948529411764706,\n \"acc_norm_stderr\": 0.024060599423487414\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.25980392156862747,\n \"acc_stderr\": 0.017740899509177788,\n \ \ \"acc_norm\": 0.25980392156862747,\n \"acc_norm_stderr\": 0.017740899509177788\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.33636363636363636,\n\ \ \"acc_stderr\": 0.04525393596302505,\n \"acc_norm\": 0.33636363636363636,\n\ \ \"acc_norm_stderr\": 0.04525393596302505\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.3020408163265306,\n \"acc_stderr\": 0.029393609319879818,\n\ \ \"acc_norm\": 0.3020408163265306,\n \"acc_norm_stderr\": 0.029393609319879818\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.23383084577114427,\n\ \ \"acc_stderr\": 0.029929415408348384,\n \"acc_norm\": 0.23383084577114427,\n\ \ \"acc_norm_stderr\": 0.029929415408348384\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.3493975903614458,\n\ \ \"acc_stderr\": 0.03711725190740749,\n \"acc_norm\": 0.3493975903614458,\n\ \ \"acc_norm_stderr\": 0.03711725190740749\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\": 0.20563035495716034,\n\ \ \"mc1_stderr\": 0.014148482219460974,\n \"mc2\": 0.3354506043570123,\n\ \ \"mc2_stderr\": 0.013110323313593984\n }\n}\n```" repo_url: https://huggingface.co/mosaicml/mpt-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_22T15_05_51.358534 path: - '/details_harness\|arc:challenge\|25_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|arc:challenge\|25_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-03T22-10-31.153532.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T17_09_43.658606 path: - '/details_harness\|drop\|3_2023-09-23T17-09-43.658606.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-23T17-09-43.658606.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T17_09_43.658606 path: - '/details_harness\|gsm8k\|5_2023-09-23T17-09-43.658606.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-23T17-09-43.658606.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hellaswag\|10_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hellaswag\|10_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-22T15:05:51.358534.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T22-10-31.153532.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T22-10-31.153532.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_22T15_05_51.358534 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-22T15:05:51.358534.parquet' - split: 2023_10_03T22_10_31.153532 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-03T22-10-31.153532.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-03T22-10-31.153532.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T17_09_43.658606 path: - '/details_harness\|winogrande\|5_2023-09-23T17-09-43.658606.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-23T17-09-43.658606.parquet' - config_name: original_mmlu_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:abstract_algebra\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:anatomy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:astronomy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:business_ethics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:clinical_knowledge\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_biology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_medicine\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:computer_security\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:conceptual_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:econometrics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:electrical_engineering\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:elementary_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:formal_logic\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:global_facts\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_biology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_european_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_geography\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_government_and_politics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_macroeconomics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_microeconomics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_psychology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_statistics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_us_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_world_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:human_aging\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:human_sexuality\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:international_law\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:jurisprudence\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:logical_fallacies\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:machine_learning\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:management\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:marketing\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:medical_genetics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:miscellaneous\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:moral_disputes\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:moral_scenarios\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:nutrition\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:philosophy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:prehistory\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_accounting\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_law\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_medicine\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_psychology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:public_relations\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:security_studies\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:sociology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:us_foreign_policy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:virology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:world_religions\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:abstract_algebra\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:anatomy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:astronomy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:business_ethics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:clinical_knowledge\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_biology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_medicine\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:college_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:computer_security\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:conceptual_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:econometrics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:electrical_engineering\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:elementary_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:formal_logic\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:global_facts\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_biology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_european_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_geography\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_government_and_politics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_macroeconomics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_microeconomics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_physics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_psychology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_statistics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_us_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:high_school_world_history\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:human_aging\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:human_sexuality\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:international_law\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:jurisprudence\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:logical_fallacies\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:machine_learning\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:management\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:marketing\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:medical_genetics\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:miscellaneous\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:moral_disputes\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:moral_scenarios\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:nutrition\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:philosophy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:prehistory\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_accounting\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_law\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_medicine\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:professional_psychology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:public_relations\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:security_studies\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:sociology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:us_foreign_policy\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:virology\|5_2023-08-28T20:09:40.976892.parquet' - '/details_original\|mmlu:world_religions\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_abstract_algebra_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:abstract_algebra\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:abstract_algebra\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_anatomy_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:anatomy\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:anatomy\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_astronomy_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:astronomy\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:astronomy\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_business_ethics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:business_ethics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:business_ethics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_clinical_knowledge_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:clinical_knowledge\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:clinical_knowledge\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_biology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_biology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_biology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_chemistry_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_computer_science_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_mathematics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_medicine_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_medicine\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_medicine\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_college_physics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:college_physics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:college_physics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_computer_security_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:computer_security\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:computer_security\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_conceptual_physics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:conceptual_physics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:conceptual_physics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_econometrics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:econometrics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:econometrics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_electrical_engineering_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:electrical_engineering\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:electrical_engineering\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_elementary_mathematics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:elementary_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:elementary_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_formal_logic_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:formal_logic\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:formal_logic\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_global_facts_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:global_facts\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:global_facts\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_biology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_biology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_biology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_chemistry_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_chemistry\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_computer_science_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_computer_science\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_european_history_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_european_history\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_european_history\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_geography_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_geography\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_geography\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_government_and_politics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_government_and_politics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_government_and_politics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_macroeconomics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_macroeconomics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_macroeconomics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_mathematics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_mathematics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_microeconomics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_microeconomics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_microeconomics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_physics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_physics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_physics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_psychology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_psychology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_psychology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_statistics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_statistics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_statistics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_us_history_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_us_history\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_us_history\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_high_school_world_history_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:high_school_world_history\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:high_school_world_history\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_human_aging_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:human_aging\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:human_aging\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_human_sexuality_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:human_sexuality\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:human_sexuality\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_international_law_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:international_law\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:international_law\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_jurisprudence_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:jurisprudence\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:jurisprudence\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_logical_fallacies_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:logical_fallacies\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:logical_fallacies\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_machine_learning_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:machine_learning\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:machine_learning\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_management_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:management\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:management\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_marketing_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:marketing\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:marketing\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_medical_genetics_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:medical_genetics\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:medical_genetics\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_miscellaneous_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:miscellaneous\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:miscellaneous\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_moral_disputes_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:moral_disputes\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:moral_disputes\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_moral_scenarios_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:moral_scenarios\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:moral_scenarios\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_nutrition_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:nutrition\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:nutrition\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_philosophy_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:philosophy\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:philosophy\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_prehistory_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:prehistory\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:prehistory\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_professional_accounting_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:professional_accounting\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:professional_accounting\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_professional_law_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:professional_law\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:professional_law\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_professional_medicine_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:professional_medicine\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:professional_medicine\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_professional_psychology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:professional_psychology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:professional_psychology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_public_relations_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:public_relations\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:public_relations\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_security_studies_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:security_studies\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:security_studies\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_sociology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:sociology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:sociology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_us_foreign_policy_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:us_foreign_policy\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:us_foreign_policy\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_virology_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:virology\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:virology\|5_2023-08-28T20:09:40.976892.parquet' - config_name: original_mmlu_world_religions_5 data_files: - split: 2023_08_28T20_09_40.976892 path: - '/details_original\|mmlu:world_religions\|5_2023-08-28T20:09:40.976892.parquet' - split: latest path: - '/details_original\|mmlu:world_religions\|5_2023-08-28T20:09:40.976892.parquet' - config_name: results data_files: - split: 2023_08_28T20_09_40.976892 path: - results_2023-08-28T20:09:40.976892.parquet - split: 2023_09_23T17_09_43.658606 path: - results_2023-09-23T17-09-43.658606.parquet - split: 2023_10_03T22_10_31.153532 path: - results_2023-10-03T22-10-31.153532.parquet - split: latest path: - results_2023-10-03T22-10-31.153532.parquet --- # Dataset Card for Evaluation run of mosaicml/mpt-7b ## Dataset Description - Homepage: - Repository: https://huggingface.co/mosaicml/mpt-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 [mosaicml/mpt-7b](https://huggingface.co/mosaicml/mpt-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 122 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 4 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_mosaicml__mpt-7b", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-10-03T22:10:31.153532](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b/blob/main/results_2023-10-03T22-10-31.153532.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": 0.28815728428182913, "acc_stderr": 0.032729017222815425, "acc_norm": 0.2923951167846347, "acc_norm_stderr": 0.032718180607395383, "mc1": 0.20563035495716034, "mc1_stderr": 0.014148482219460974, "mc2": 0.3354506043570123, "mc2_stderr": 0.013110323313593984 }, "harness\|arc:challenge\|25": { "acc": 0.42918088737201365, "acc_stderr": 0.014464085894870653, "acc_norm": 0.47696245733788395, "acc_norm_stderr": 0.014595873205358269 }, "harness\|hellaswag\|10": { "acc": 0.5730930093606851, "acc_stderr": 0.004936176784631949, "acc_norm": 0.7753435570603465, "acc_norm_stderr": 0.0041650291643616005 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.19, "acc_stderr": 0.03942772444036624, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036624 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.035914440841969694, "acc_norm": 0.2222222222222222, 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"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": 0.20563035495716034, "mc1_stderr": 0.014148482219460974, "mc2": 0.3354506043570123, "mc2_stderr": 0.013110323313593984 } } ``` ### 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]	[ -0.7737067937850952, -0.8137637376785278, 0.3076789081096649, 0.2806215286254883, -0.17712125182151794, -0.05071611329913139, 0.033600639551877975, -0.18291574716567993, 0.5184798240661621, -0.06474762409925461, -0.4749520719051361, -0.7149546146392822, -0.4885590076446533, 0.23964370787143707, 0.000455393543234095, 0.7923364043235779, -0.20686867833137512, -0.12072720378637314, 0.0733334869146347, -0.04503483325242996, -0.25783392786979675, -0.2937459349632263, -0.46017906069755554, 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open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ	open-llm-leaderboard	2023-10-27T04:39:34Z	381	0	[ "region:us" ]	null	2023-09-13T17:15:50Z	--- pretty_name: Evaluation run of elliotthwang/Elliott-Chinese-LLaMa-GPTQ dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [elliotthwang/Elliott-Chinese-LLaMa-GPTQ](https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ)\ \ 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_elliotthwang__Elliott-Chinese-LLaMa-GPTQ\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-27T04:39:21.377335](https://huggingface.co/datasets/open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ/blob/main/results_2023-10-27T04-39-21.377335.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\": 0.001363255033557047,\n\ \ \"em_stderr\": 0.0003778609196461018,\n \"f1\": 0.057080536912751875,\n\ \ \"f1_stderr\": 0.0012933707193154948,\n \"acc\": 0.44911238992013397,\n\ \ \"acc_stderr\": 0.01146531039524964\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.001363255033557047,\n \"em_stderr\": 0.0003778609196461018,\n\ \ \"f1\": 0.057080536912751875,\n \"f1_stderr\": 0.0012933707193154948\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.17210007581501138,\n \ \ \"acc_stderr\": 0.010397328057878982\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7261247040252565,\n \"acc_stderr\": 0.012533292732620297\n\ \ }\n}\n```" repo_url: https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ 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_13T17_15_37.349272 path: - '/details_harness\|arc:challenge\|25_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-13T17-15-37.349272.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_27T04_39_21.377335 path: - '/details_harness\|drop\|3_2023-10-27T04-39-21.377335.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-27T04-39-21.377335.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_27T04_39_21.377335 path: - '/details_harness\|gsm8k\|5_2023-10-27T04-39-21.377335.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-27T04-39-21.377335.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hellaswag\|10_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T17-15-37.349272.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T17-15-37.349272.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_13T17_15_37.349272 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T17-15-37.349272.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T17-15-37.349272.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_27T04_39_21.377335 path: - '/details_harness\|winogrande\|5_2023-10-27T04-39-21.377335.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-27T04-39-21.377335.parquet' - config_name: results data_files: - split: 2023_09_13T17_15_37.349272 path: - results_2023-09-13T17-15-37.349272.parquet - split: 2023_10_27T04_39_21.377335 path: - results_2023-10-27T04-39-21.377335.parquet - split: latest path: - results_2023-10-27T04-39-21.377335.parquet --- # Dataset Card for Evaluation run of elliotthwang/Elliott-Chinese-LLaMa-GPTQ ## Dataset Description - Homepage: - Repository: https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ - 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 [elliotthwang/Elliott-Chinese-LLaMa-GPTQ](https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ) 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_elliotthwang__Elliott-Chinese-LLaMa-GPTQ", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-27T04:39:21.377335](https://huggingface.co/datasets/open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ/blob/main/results_2023-10-27T04-39-21.377335.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": 0.001363255033557047, "em_stderr": 0.0003778609196461018, "f1": 0.057080536912751875, "f1_stderr": 0.0012933707193154948, "acc": 0.44911238992013397, "acc_stderr": 0.01146531039524964 }, "harness\|drop\|3": { "em": 0.001363255033557047, "em_stderr": 0.0003778609196461018, "f1": 0.057080536912751875, "f1_stderr": 0.0012933707193154948 }, "harness\|gsm8k\|5": { "acc": 0.17210007581501138, "acc_stderr": 0.010397328057878982 }, "harness\|winogrande\|5": { "acc": 0.7261247040252565, "acc_stderr": 0.012533292732620297 } } ``` ### 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]	[ -0.35920098423957825, -0.6235613822937012, 0.3174106180667877, 0.23868222534656525, -0.25431185960769653, 0.2085707187652588, -0.38101083040237427, -0.2804138958454132, 0.37364497780799866, 0.5124722123146057, -0.708311915397644, -1.0302636623382568, -0.6426161527633667, 0.23975960910320282, -0.14836925268173218, 1.1388013362884521, -0.3179679811000824, -0.20350509881973267, 0.15320985019207, -0.30208805203437805, -0.30208179354667664, -0.41345301270484924, -0.6807636618614197, 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open-llm-leaderboard/details_gradientputri__MegaMix-S1-13B	open-llm-leaderboard	2023-10-28T06:03:17Z	381	0	[ "region:us" ]	null	2023-10-04T02:36:55Z	--- pretty_name: Evaluation run of gradientputri/MegaMix-S1-13B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [gradientputri/MegaMix-S1-13B](https://huggingface.co/gradientputri/MegaMix-S1-13B)\ \ 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_gradientputri__MegaMix-S1-13B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T06:03:05.658343](https://huggingface.co/datasets/open-llm-leaderboard/details_gradientputri__MegaMix-S1-13B/blob/main/results_2023-10-28T06-03-05.658343.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\": 0.0005131152834514578,\n \"f1\": 0.06513108221476514,\n\ \ \"f1_stderr\": 0.0014177635325476718,\n \"acc\": 0.4709784684170939,\n\ \ \"acc_stderr\": 0.011345177115355768\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0025167785234899327,\n \"em_stderr\": 0.0005131152834514578,\n\ \ \"f1\": 0.06513108221476514,\n \"f1_stderr\": 0.0014177635325476718\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.18347232752084913,\n \ \ \"acc_stderr\": 0.010661370448699659\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7584846093133386,\n \"acc_stderr\": 0.012028983782011875\n\ \ }\n}\n```" repo_url: https://huggingface.co/gradientputri/MegaMix-S1-13B 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_10_04T02_36_32.129968 path: - '/details_harness\|arc:challenge\|25_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-04T02-36-32.129968.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T06_03_05.658343 path: - '/details_harness\|drop\|3_2023-10-28T06-03-05.658343.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T06-03-05.658343.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T06_03_05.658343 path: - '/details_harness\|gsm8k\|5_2023-10-28T06-03-05.658343.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T06-03-05.658343.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hellaswag\|10_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T02-36-32.129968.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-04T02-36-32.129968.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_04T02_36_32.129968 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-04T02-36-32.129968.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-04T02-36-32.129968.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T06_03_05.658343 path: - '/details_harness\|winogrande\|5_2023-10-28T06-03-05.658343.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T06-03-05.658343.parquet' - config_name: results data_files: - split: 2023_10_04T02_36_32.129968 path: - results_2023-10-04T02-36-32.129968.parquet - split: 2023_10_28T06_03_05.658343 path: - results_2023-10-28T06-03-05.658343.parquet - split: latest path: - results_2023-10-28T06-03-05.658343.parquet --- # Dataset Card for Evaluation run of gradientputri/MegaMix-S1-13B ## Dataset Description - Homepage: - Repository: https://huggingface.co/gradientputri/MegaMix-S1-13B - 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 [gradientputri/MegaMix-S1-13B](https://huggingface.co/gradientputri/MegaMix-S1-13B) 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_gradientputri__MegaMix-S1-13B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T06:03:05.658343](https://huggingface.co/datasets/open-llm-leaderboard/details_gradientputri__MegaMix-S1-13B/blob/main/results_2023-10-28T06-03-05.658343.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": 0.0005131152834514578, "f1": 0.06513108221476514, "f1_stderr": 0.0014177635325476718, "acc": 0.4709784684170939, "acc_stderr": 0.011345177115355768 }, "harness\|drop\|3": { "em": 0.0025167785234899327, "em_stderr": 0.0005131152834514578, "f1": 0.06513108221476514, "f1_stderr": 0.0014177635325476718 }, "harness\|gsm8k\|5": { "acc": 0.18347232752084913, "acc_stderr": 0.010661370448699659 }, "harness\|winogrande\|5": { "acc": 0.7584846093133386, "acc_stderr": 0.012028983782011875 } } ``` ### 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]	[ -0.5435338020324707, -0.5278893113136292, 0.17216476798057556, 0.30217108130455017, -0.14604218304157257, 0.10461274534463882, -0.3501630425453186, -0.07505372166633606, 0.47919991612434387, 0.46569499373435974, -0.8013601303100586, -0.8331321477890015, -0.7384588718414307, 0.15134014189243317, -0.1135830283164978, 1.1845355033874512, -0.21503393352031708, -0.09412786364555359, 0.029913069680333138, -0.31546783447265625, -0.1681920289993286, -0.3960077166557312, -0.5975741744041443, 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HuggingFaceM4/FairFace	HuggingFaceM4	2022-12-09T00:14:46Z	380	5	[ "license:cc-by-4.0", "region:us" ]	null	2022-12-08T23:00:45Z	--- license: cc-by-4.0 --- # 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: [https://github.com/joojs/fairface](https://github.com/joojs/fairface) - Repository: [https://github.com/joojs/fairface](https://github.com/joojs/fairface) - Paper: [https://openaccess.thecvf.com/content/WACV2021/papers/Karkkainen_FairFace_Face_Attribute_Dataset_for_Balanced_Race_Gender_and_Age_WACV_2021_paper.pdf](https://openaccess.thecvf.com/content/WACV2021/papers/Karkkainen_FairFace_Face_Attribute_Dataset_for_Balanced_Race_Gender_and_Age_WACV_2021_paper.pdf) - Leaderboard: - Point of Contact: ### Dataset Summary FairFace is a face image dataset which is race balanced. It contains 108,501 images from 7 different race groups: White, Black, Indian, East Asian, Southeast Asian, Middle Eastern, and Latino. Images were collected from the YFCC-100M Flickr dataset and labeled with race, gender, and age groups. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances Each instance has the following structure: ``` { 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=448x448 at 0x7FCABA221FA0>, 'age': 6, 'gender': 0, 'race': 0, 'service_test': True } ``` ### Data Fields - `image`: The image - `age`: Age class among `["0-2", "3-9", "10-19", "20-29", "30-39", "40-49", "50-59", "60-69", "more than 70"]` - `gender`: Gender class among `["Male", "Female"]` - `race`: Race class among `["East Asian", "Indian", "Black", "White", "Middle Eastern", "Latino_Hispanic", "Southeast Asian"]` - `service_test`: Not sure what this is. See [issue](https://github.com/joojs/fairface/issues/9). ### 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 [@VictorSanh](https://github.com/VictorSanh) for adding this dataset.	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osunlp/AttrScore	osunlp	2023-06-29T01:56:48Z	380	9	[ "task_categories:text-classification", "size_categories:100K<n<1M", "language:en", "license:apache-2.0", "arxiv:2305.06311", "region:us" ]	[ "text-classification" ]	2023-05-16T19:09:52Z	--- license: apache-2.0 task_categories: - text-classification language: - en pretty_name: AttrScore size_categories: - 100K<n<1M --- # Dataset Card for AttrScore - Repository: https://github.com/OSU-NLP-Group/AttrScore - Paper: [Automatic Evaluation of Attribution by Large Language Models] (https://arxiv.org/pdf/2305.06311.pdf) - Point of Contact: [Xiang Yue](mailto:[email protected]) ### Citation Information ```bib @article{yue2023automatic, title={Automatic Evaluation of Attribution by Large Language Models}, author={Yue, Xiang and Wang, Boshi and Zhang, Kai and Chen, Ziru and Su, Yu and Sun, Huan}, journal={arXiv preprint arXiv:2305.06311}, year={2023} } ``` ### What's New? In the current version 0.2, we fixed some wrong annotated labels in the AttrEval-GenSearch dataset. (Commit: [4da294f](https://huggingface.co/datasets/osunlp/AttrScore/commit/4da294f5e488086492e117b405fc8ea95717ec3b)) ### Dataset Summary A recent focus of large language model (LLM) development, as exemplified by generative search engines, is to incorporate external references to generate and support its claims. However, evaluating the attribution, i.e., verifying whether the generated statement is indeed fully supported by the cited reference, remains an open problem. We construct this dataset, which contains both training and test data for the evaluation of attribution. The training data are repurposed from related tasks, such as question answering, fact-checking, natural language inference, and summarization. The test data, cotains a set simulated from QA datasets and a set manually curated from a generative search engine, New Bing. ## Dataset Structure ### Data Instances { "query": "", "answer": "Bastedo cared for all the animals that inhabit the earth.", "reference": "Alexandra Lendon Bastedo (9 March 1946 - 12 January 2014) was a British actress, best known for her role as secret agent Sharron Macready in the 1968 British espionage/science fiction adventure series \"The Champions\". She has been cited as a sex symbol of the 1960s and 1970s. Bastedo was a vegetarian and animal welfare advocate.", "label": "Extrapolatory", "dataset": "anli" } { "query": The persian gulf war began when iraq invaded what country? "answer": The Persian Gulf War began when Iraq invaded Kuwait. "reference": First Iraq War or Iraq War, before the term \"Iraq War\" became identified instead with the 2003 Iraq War. The Iraqi Army's occupation of Kuwait that began 2 August 1990 was met with international condemnation and brought immediate economic sanctions against Iraq by members of the UN Security Council. Together with the UK's prime minister Margaret Thatcher - who had resisted the invasion by Argentina of the Falkland Islands a decade earlier - George H. W. Bush deployed US forces into Saudi Arabia, and urged other countries to send their own forces to the scene. An array of nations joined the coalition, forming the", "label": "Attributable", "dataset": "NaturalQuestions" } ### Data Fields - "query": query (may be empty) - "answer": answer to the query - "reference": a document or a paragraph - "label": whether the reference can support the answer to the query ("attributable", "extrapolatory", "contradictory") - "dataset": the original dataset of the data instance	[ -0.23988308012485504, -0.5228334069252014, 0.462186336517334, -0.1265438348054886, 0.016510555520653725, -0.11382012814283371, 0.1274634450674057, -0.3168078064918518, 0.16699272394180298, 0.6084339022636414, -0.47399210929870605, -0.3936542868614197, -0.5235381722450256, 0.19569526612758636, -0.2733211815357208, 1.0893083810806274, -0.3987230658531189, -0.1227845773100853, -0.32579153776168823, -0.4129498302936554, 0.15327011048793793, -0.5425599217414856, -0.5593145489692688, -0.21637606620788574, 0.5432049036026001, 0.3281830847263336, 0.6323405504226685, 0.5797780752182007, 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dikw/hh_rlhf_cn	dikw	2023-08-24T05:51:47Z	380	30	[ "license:llama2", "region:us" ]	null	2023-08-18T10:09:26Z	--- license: llama2 --- --- license: bsd --- ## hh-rlhf中文翻译版本基于Anthropic论文Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback 开源的helpful 和harmless数据，使用翻译工具进行了翻译。 hh_rlhf_train.jsonl 合并中英文训练集数据清洗过后17万条 hh_rlhf_test.jsonl 合并中英文测试集数据清洗过后9千条 harmless_base_cn_train.jsonl 42394条 harmless_base_cn_test.jsonl 2304条 helpful_base_cn_train.jsonl 43722条 helpful_base_cn_test.jsonl 2346条 ## 实验报告相关rlhf实验报告:https://zhuanlan.zhihu.com/p/652044120	[ -0.27916690707206726, -1.0225012302398682, -0.05805308371782303, 0.47577258944511414, -0.4866813123226166, -0.08714699745178223, 0.1878407746553421, -0.5165992975234985, 0.23368331789970398, 0.34568557143211365, -0.754782497882843, -0.5392706394195557, -0.454041451215744, 0.2896113097667694, 0.12977813184261322, 1.0210447311401367, -0.04595876485109329, 0.4058956801891327, 0.20910991728305817, -0.39856788516044617, 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open-llm-leaderboard/details_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged	open-llm-leaderboard	2023-10-28T16:42:47Z	380	0	[ "region:us" ]	null	2023-10-03T17:17:09Z	--- pretty_name: Evaluation run of dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged](https://huggingface.co/dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged)\ \ 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_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T16:42:34.900797](https://huggingface.co/datasets/open-llm-leaderboard/details_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged/blob/main/results_2023-10-28T16-42-34.900797.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\": 0.0030411073825503355,\n\ \ \"em_stderr\": 0.0005638896908753095,\n \"f1\": 0.07054530201342267,\n\ \ \"f1_stderr\": 0.0015180367806482934,\n \"acc\": 0.42638763311757666,\n\ \ \"acc_stderr\": 0.00983841076151077\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0030411073825503355,\n \"em_stderr\": 0.0005638896908753095,\n\ \ \"f1\": 0.07054530201342267,\n \"f1_stderr\": 0.0015180367806482934\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08718726307808947,\n \ \ \"acc_stderr\": 0.007770691416783557\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7655880031570639,\n \"acc_stderr\": 0.011906130106237983\n\ \ }\n}\n```" repo_url: https://huggingface.co/dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged 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_03T17_16_44.707859 path: - '/details_harness\|arc:challenge\|25_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-03T17-16-44.707859.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T16_42_34.900797 path: - '/details_harness\|drop\|3_2023-10-28T16-42-34.900797.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T16-42-34.900797.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T16_42_34.900797 path: - '/details_harness\|gsm8k\|5_2023-10-28T16-42-34.900797.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T16-42-34.900797.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hellaswag\|10_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T17-16-44.707859.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-03T17-16-44.707859.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_03T17_16_44.707859 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-03T17-16-44.707859.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-03T17-16-44.707859.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T16_42_34.900797 path: - '/details_harness\|winogrande\|5_2023-10-28T16-42-34.900797.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T16-42-34.900797.parquet' - config_name: results data_files: - split: 2023_10_03T17_16_44.707859 path: - results_2023-10-03T17-16-44.707859.parquet - split: 2023_10_28T16_42_34.900797 path: - results_2023-10-28T16-42-34.900797.parquet - split: latest path: - results_2023-10-28T16-42-34.900797.parquet --- # Dataset Card for Evaluation run of dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged ## Dataset Description - Homepage: - Repository: https://huggingface.co/dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged - 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 [dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged](https://huggingface.co/dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged) 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_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T16:42:34.900797](https://huggingface.co/datasets/open-llm-leaderboard/details_dhmeltzer__Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16_merged/blob/main/results_2023-10-28T16-42-34.900797.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": 0.0030411073825503355, "em_stderr": 0.0005638896908753095, "f1": 0.07054530201342267, "f1_stderr": 0.0015180367806482934, "acc": 0.42638763311757666, "acc_stderr": 0.00983841076151077 }, "harness\|drop\|3": { "em": 0.0030411073825503355, "em_stderr": 0.0005638896908753095, "f1": 0.07054530201342267, "f1_stderr": 0.0015180367806482934 }, "harness\|gsm8k\|5": { "acc": 0.08718726307808947, "acc_stderr": 0.007770691416783557 }, "harness\|winogrande\|5": { "acc": 0.7655880031570639, "acc_stderr": 0.011906130106237983 } } ``` ### 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]	[ -0.4890240728855133, -0.6512756943702698, 0.2822275459766388, 0.23049497604370117, -0.201186865568161, 0.1987781673669815, -0.36273035407066345, -0.2634488642215729, 0.40512412786483765, 0.47574475407600403, -0.726021945476532, -0.8889933228492737, -0.7168599963188171, 0.2385607361793518, -0.220758855342865, 1.2324594259262085, -0.29746803641319275, -0.23841498792171478, 0.03868638724088669, -0.2588183581829071, -0.2843279242515564, -0.41684582829475403, -0.46777352690696716, 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open-llm-leaderboard/details_PygmalionAI__pygmalion-2-7b	open-llm-leaderboard	2023-10-28T09:33:25Z	380	0	[ "region:us" ]	null	2023-10-08T20:23:05Z	--- pretty_name: Evaluation run of PygmalionAI/pygmalion-2-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [PygmalionAI/pygmalion-2-7b](https://huggingface.co/PygmalionAI/pygmalion-2-7b)\ \ 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_PygmalionAI__pygmalion-2-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T09:33:13.706982](https://huggingface.co/datasets/open-llm-leaderboard/details_PygmalionAI__pygmalion-2-7b/blob/main/results_2023-10-28T09-33-13.706982.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\": 0.001153523489932886,\n\ \ \"em_stderr\": 0.00034761798968571027,\n \"f1\": 0.05976614932885909,\n\ \ \"f1_stderr\": 0.0013611207374076375,\n \"acc\": 0.4075329125111523,\n\ \ \"acc_stderr\": 0.009436763896104398\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.001153523489932886,\n \"em_stderr\": 0.00034761798968571027,\n\ \ \"f1\": 0.05976614932885909,\n \"f1_stderr\": 0.0013611207374076375\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.06368460955269144,\n \ \ \"acc_stderr\": 0.006726213078805692\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7513812154696132,\n \"acc_stderr\": 0.012147314713403105\n\ \ }\n}\n```" repo_url: https://huggingface.co/PygmalionAI/pygmalion-2-7b 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_08T20_22_41.887829 path: - '/details_harness\|arc:challenge\|25_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-08T20-22-41.887829.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T09_33_13.706982 path: - '/details_harness\|drop\|3_2023-10-28T09-33-13.706982.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T09-33-13.706982.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T09_33_13.706982 path: - '/details_harness\|gsm8k\|5_2023-10-28T09-33-13.706982.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T09-33-13.706982.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hellaswag\|10_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T20-22-41.887829.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T20-22-41.887829.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T20_22_41.887829 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T20-22-41.887829.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T20-22-41.887829.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T09_33_13.706982 path: - '/details_harness\|winogrande\|5_2023-10-28T09-33-13.706982.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T09-33-13.706982.parquet' - config_name: results data_files: - split: 2023_10_08T20_22_41.887829 path: - results_2023-10-08T20-22-41.887829.parquet - split: 2023_10_28T09_33_13.706982 path: - results_2023-10-28T09-33-13.706982.parquet - split: latest path: - results_2023-10-28T09-33-13.706982.parquet --- # Dataset Card for Evaluation run of PygmalionAI/pygmalion-2-7b ## Dataset Description - Homepage: - Repository: https://huggingface.co/PygmalionAI/pygmalion-2-7b - 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 [PygmalionAI/pygmalion-2-7b](https://huggingface.co/PygmalionAI/pygmalion-2-7b) 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_PygmalionAI__pygmalion-2-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T09:33:13.706982](https://huggingface.co/datasets/open-llm-leaderboard/details_PygmalionAI__pygmalion-2-7b/blob/main/results_2023-10-28T09-33-13.706982.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": 0.001153523489932886, "em_stderr": 0.00034761798968571027, "f1": 0.05976614932885909, "f1_stderr": 0.0013611207374076375, "acc": 0.4075329125111523, "acc_stderr": 0.009436763896104398 }, "harness\|drop\|3": { "em": 0.001153523489932886, "em_stderr": 0.00034761798968571027, "f1": 0.05976614932885909, "f1_stderr": 0.0013611207374076375 }, "harness\|gsm8k\|5": { "acc": 0.06368460955269144, "acc_stderr": 0.006726213078805692 }, "harness\|winogrande\|5": { "acc": 0.7513812154696132, "acc_stderr": 0.012147314713403105 } } ``` ### 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]	[ -0.3535952568054199, -0.5894854068756104, 0.11435791105031967, 0.24534961581230164, -0.1859862059354782, 0.051338352262973785, -0.4761117100715637, -0.2345508635044098, 0.34509915113449097, 0.4145157039165497, -0.6564898490905762, -0.8052138090133667, -0.7059247493743896, 0.188678577542305, -0.04653939604759216, 1.1514731645584106, -0.28863224387168884, -0.21117867529392242, 0.0003152392746414989, -0.2955014705657959, -0.3250369727611542, -0.4180256426334381, -0.48381108045578003, 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TheBritishLibrary/EThOS-PhD-metadata	TheBritishLibrary	2022-07-23T21:14:57Z	379	1	[ "task_categories:text-classification", "task_categories:fill-mask", "task_ids:multi-label-classification", "task_ids:masked-language-modeling", "multilinguality:monolingual", "language:en", "region:us" ]	[ "text-classification", "fill-mask" ]	2022-03-02T23:29:22Z	--- annotations_creators: [] language: - en language_creators: [] license: [] multilinguality: - monolingual pretty_name: EThOS PhD metadata size_categories: [] source_datasets: [] tags: [] task_categories: - text-classification - fill-mask task_ids: - multi-label-classification - masked-language-modeling --- # Dataset Card for EThOS PhD metadata ## Table of Contents - [Dataset Card for blbooksgenre](#dataset-card-for-EThOS PhD metadata) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Supervised tasks](#supervised-tasks) - [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) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [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://bl.iro.bl.uk/concern/datasets/c815b271-09be-4123-8156-405094429198?locale=en - Repository: https://doi.org/10.23636/ybpt-nh33 - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data in this collection comprises the bibliographic metadata for all UK doctoral theses listed in EThOS, the UK's national thesis service. We estimate the data covers around 98% of all PhDs ever awarded by UK Higher Education institutions, dating back to 1787. Thesis metadata from every PhD-awarding university in the UK is included. You can investigate and re-use this unique collection of UK universities' PhD thesis data to analyse trends in postgraduate research, make connections between researchers, apply large data analysis, improve citation of theses and many more applications. [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] #### Supervised tasks [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure [More Information Needed] ### Data Instances An example data instance: ```python {'Abstract': ' ', 'Author': 'Loizou, Panos A.', 'Author ISNI': 'https://isni.org/isni/0000000136122593', 'DOI': ' ', 'Date': datetime.datetime(1989, 1, 1, 0, 0), 'EThOS URL': 'https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.232781', 'Funder(s)': ' ', 'IR URL': ' ', 'Institution': 'University of Manchester', 'Institution ISNI': 'https://isni.org/isni/0000000121662407', 'ORCID': ' ', 'Qualification': 'Thesis (Ph.D.)', 'Subject Discipline': 0, 'Supervisor(s)': ' ', 'Title': 'Computation and measurement of turbulent flow through idealized turbine blade passages'} ``` ### Data Fields [More Information Needed] ### Data Splits This dataset contains a single split `train`. ## Dataset Creation [More Information Needed] ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data [More Information Needed] ### 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 The books are licensed under the [CC BY 4.0 Attribution](https://creativecommons.org/licenses/by/4.0/) license. ### Citation Information	[ -0.5245898365974426, -0.2790962755680084, 0.22468049824237823, 0.21891210973262787, -0.25292471051216125, -0.11799580603837967, -0.3314773440361023, -0.3996764123439789, 0.432621031999588, 0.6419979333877563, -0.561738908290863, -0.9074589610099792, -0.6661882996559143, 0.23080241680145264, -0.1343858540058136, 0.9664304852485657, -0.10033105313777924, 0.05464255064725876, -0.03782331943511963, -0.14726431667804718, -0.05168069154024124, 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diwank/silicone-merged	diwank	2022-03-06T11:30:57Z	379	1	[ "license:mit", "region:us" ]	null	2022-03-02T23:29:22Z	--- license: mit --- # diwank/silicone-merged > Merged and simplified dialog act datasets from the [silicone collection](https://huggingface.co/datasets/silicone/) All of the subsets of the original collection have been filtered (for errors and ambiguous classes), merged together and grouped into pairs of dialog turns. It is hypothesized that training dialog act classifier by including the previous utterance can help models pick up additional contextual cues and be better at inference esp if an utterance pair is provided. ## Example training script ```python from datasets import load_dataset from simpletransformers.classification import ( ClassificationModel, ClassificationArgs ) # Get data silicone_merged = load_dataset("diwank/silicone-merged") train_df = silicone_merged["train"] eval_df = silicone_merged["validation"] model_args = ClassificationArgs( num_train_epochs=8, model_type="deberta", model_name="microsoft/deberta-large", use_multiprocessing=False, evaluate_during_training=True, ) # Create a ClassificationModel model = ClassificationModel("deberta", "microsoft/deberta-large", args=model_args, num_labels=11) # 11 labels in this dataset # Train model model.train_model(train_df, eval_df=eval_df) ``` ## Balanced variant of the training set Note: This dataset is highly imbalanced and it is recommended to use a library like [imbalanced-learn](https://imbalanced-learn.org/stable/) before proceeding with training. Since, balancing can be complicated and resource-intensive, we have shared a balanced variant of the train set that was created via oversampling using the _imbalanced-learn_ library. The balancing used the `SMOTEN` algorithm to deal with categorical data clustering and was resampled on a 16-core, 60GB RAM machine. You can access it using: ```load_dataset("diwank/silicone-merged", "balanced")``` ## Feature description - `text_a`: The utterance prior to the utterance being classified. (Say for dialog with turns 1-2-3, if we are trying to find the dialog act for 2, text_a is 1) - `text_b`: The utterance to be classified - `labels`: Dialog act label (as integer between 0-10, as mapped below) ## Labels map ```python [ (0, 'acknowledge') (1, 'answer') (2, 'backchannel') (3, 'reply_yes') (4, 'exclaim') (5, 'say') (6, 'reply_no') (7, 'hold') (8, 'ask') (9, 'intent') (10, 'ask_yes_no') ] ``` ***** ## Appendix ### How the original datasets were mapped: ```python mapping = { "acknowledge": { "swda": [ "aap_am", "b", "bk" ], "mrda": [], "oasis": [ "ackn", "accept", "complete" ], "maptask": [ "acknowledge", "align" ], "dyda_da": [ "commissive" ] }, "answer": { "swda": [ "bf", ], "mrda": [], "oasis": [ "answ", "informCont", "inform", "answElab", "directElab", "refer" ], "maptask": [ "reply_w", "explain" ], "dyda_da": [ "inform" ] }, "backchannel": { "swda": [ "ad", "bh", "bd", "b^m" ], "mrda": [ "b" ], "oasis": [ "backch", "selfTalk", "init" ], "maptask": ["ready"], "dyda_da": [] }, "reply_yes": { "swda": [ "na", "aa" ], "mrda": [], "oasis": [ "confirm" ], "maptask": [ "reply_y" ], "dyda_da": [] }, "exclaim": { "swda": [ "ft", "fa", "fc", "fp" ], "mrda": [], "oasis": [ "appreciate", "bye", "exclaim", "greet", "thank", "pardon", "thank-identitySelf", "expressRegret" ], "maptask": [], "dyda_da": [] }, "say": { "swda": [ "qh", "sd" ], "mrda": ["s"], "oasis": [ "expressPossibility", "expressOpinion", "suggest" ], "maptask": [], "dyda_da": [] }, "reply_no": { "swda": [ "nn", "ng", "ar" ], "mrda": [], "oasis": [ "refuse", "negate" ], "maptask": [ "reply_n" ], "dyda_da": [] }, "hold": { "swda": [ "^h", "t1" ], "mrda": [ "f" ], "oasis": [ "hold" ], "maptask": [], "dyda_da": [] }, "ask": { "swda": [ "qw", "qo", "qw^d", "br", "qrr" ], "mrda": [ "q" ], "oasis": [ "reqInfo", "reqDirect", "offer" ], "maptask": [ "query_w" ], "dyda_da": [ "question" ] }, "intent": { "swda": [], "mrda": [], "oasis": [ "informIntent", "informIntent-hold", "expressWish", "direct", "raiseIssue", "correct" ], "maptask": [ "instruct", "clarify" ], "dyda_da": [ "directive" ] }, "ask_yes_no": { "swda": [ "qy^d", "^g" ], "mrda": [], "oasis": [ "reqModal" ], "maptask": [ "query_yn", "check" ], "dyda_da": [] } } ```	[ -0.6079481244087219, -0.5769990086555481, 0.20654256641864777, 0.017920972779393196, -0.13218457996845245, 0.06079212576150894, -0.134010449051857, -0.099284328520298, 0.49505484104156494, 0.6004807353019714, -1.0613832473754883, -0.7278193831443787, -0.7138752341270447, 0.10108435153961182, -0.0712214931845665, 1.0576508045196533, -0.05396515503525734, -0.2350248396396637, 0.1619664430618286, -0.3184865713119507, -0.5089443325996399, -0.22927629947662354, -0.6102110147476196, -0.20331348478794098, 0.31848928332328796, 0.48777061700820923, 0.651538610458374, 0.20872029662132263, 0.4167848825454712, 0.3900183141231537, -0.28129464387893677, 0.288667231798172, -0.4583905041217804, -0.03917878121137619, 0.04703439027070999, -0.5196682214736938, 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MLCommons/ml_spoken_words	MLCommons	2022-12-06T11:11:02Z	378	16	[ "task_categories:audio-classification", "annotations_creators:machine-generated", "language_creators:other", "multilinguality:multilingual", "size_categories:10M<n<100M", "source_datasets:extended\|common_voice", "language:ar", "language:as", "language:br", "language:ca", "language:cnh", "language:cs", "language:cv", "language:cy", "language:de", "language:dv", "language:el", "language:en", "language:eo", "language:es", "language:et", "language:eu", "language:fa", "language:fr", "language:fy", "language:ga", "language:gn", "language:ha", "language:ia", "language:id", "language:it", "language:ka", "language:ky", "language:lt", "language:lv", "language:mn", "language:mt", "language:nl", "language:or", "language:pl", "language:pt", "language:rm", "language:ro", "language:ru", "language:rw", "language:sah", "language:sk", "language:sl", "language:sv", "language:ta", "language:tr", "language:tt", "language:uk", "language:vi", "language:zh", "license:cc-by-4.0", "other-keyword-spotting", "region:us" ]	[ "audio-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - machine-generated language_creators: - other language: - ar - as - br - ca - cnh - cs - cv - cy - de - dv - el - en - eo - es - et - eu - fa - fr - fy - ga - gn - ha - ia - id - it - ka - ky - lt - lv - mn - mt - nl - or - pl - pt - rm - ro - ru - rw - sah - sk - sl - sv - ta - tr - tt - uk - vi - zh license: - cc-by-4.0 multilinguality: - multilingual size_categories: - 10M<n<100M source_datasets: - extended\|common_voice task_categories: - audio-classification task_ids: [] pretty_name: Multilingual Spoken Words language_bcp47: - fy-NL - ga-IE - rm-sursilv - rm-vallader - sv-SE - zh-CN tags: - other-keyword-spotting --- # Dataset Card for Multilingual Spoken Words ## 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://mlcommons.org/en/multilingual-spoken-words/ - Repository: https://github.com/harvard-edge/multilingual_kws - Paper: https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/fe131d7f5a6b38b23cc967316c13dae2-Paper-round2.pdf - Leaderboard: - Point of Contact: ### Dataset Summary Multilingual Spoken Words Corpus is a large and growing audio dataset of spoken words in 50 languages collectively spoken by over 5 billion people, for academic research and commercial applications in keyword spotting and spoken term search, licensed under CC-BY 4.0. The dataset contains more than 340,000 keywords, totaling 23.4 million 1-second spoken examples (over 6,000 hours). The dataset has many use cases, ranging from voice-enabled consumer devices to call center automation. This dataset is generated by applying forced alignment on crowd-sourced sentence-level audio to produce per-word timing estimates for extraction. All alignments are included in the dataset. Data is provided in two formats: `wav` (16KHz) and `opus` (48KHz). Default configurations look like `"{lang}_{format}"`, so to load, for example, Tatar in wav format do: ```python ds = load_dataset("MLCommons/ml_spoken_words", "tt_wav") ``` To download multiple languages in a single dataset pass list of languages to `languages` argument: ```python ds = load_dataset("MLCommons/ml_spoken_words", languages=["ar", "tt", "br"]) ``` To download a specific format pass it to the `format` argument (default format is `wav`): ```python ds = load_dataset("MLCommons/ml_spoken_words", languages=["ar", "tt", "br"], format="opus") ``` Note that each time you provide different sets of languages, examples are generated from scratch even if you already provided one or several of them before because custom configurations are created each time (the data is not redownloaded though). ### Supported Tasks and Leaderboards Keyword spotting, Spoken term search ### Languages The dataset is multilingual. To specify several languages to download pass a list of them to the `languages` argument: ```python ds = load_dataset("MLCommons/ml_spoken_words", languages=["ar", "tt", "br"]) ``` The dataset contains data for the following languages: Low-resourced (<10 hours): * Arabic (0.1G, 7.6h) * Assamese (0.9M, 0.1h) * Breton (69M, 5.6h) * Chuvash (28M, 2.1h) * Chinese (zh-CN) (42M, 3.1h) * Dhivehi (0.7M, 0.04h) * Frisian (0.1G, 9.6h) * Georgian (20M, 1.4h) * Guarani (0.7M, 1.3h) * Greek (84M, 6.7h) * Hakha Chin (26M, 0.1h) * Hausa (90M, 1.0h) * Interlingua (58M, 4.0h) * Irish (38M, 3.2h) * Latvian (51M, 4.2h) * Lithuanian (21M, 0.46h) * Maltese (88M, 7.3h) * Oriya (0.7M, 0.1h) * Romanian (59M, 4.5h) * Sakha (42M, 3.3h) * Slovenian (43M, 3.0h) * Slovak (31M, 1.9h) * Sursilvan (61M, 4.8h) * Tamil (8.8M, 0.6h) * Vallader (14M, 1.2h) * Vietnamese (1.2M, 0.1h) Medium-resourced (>10 & <100 hours): * Czech (0.3G, 24h) * Dutch (0.8G, 70h) * Estonian (0.2G, 19h) * Esperanto (1.3G, 77h) * Indonesian (0.1G, 11h) * Kyrgyz (0.1G, 12h) * Mongolian (0.1G, 12h) * Portuguese (0.7G, 58h) * Swedish (0.1G, 12h) * Tatar (4G, 30h) * Turkish (1.3G, 29h) * Ukrainian (0.2G, 18h) Hig-resourced (>100 hours): * Basque (1.7G, 118h) * Catalan (8.7G, 615h) * English (26G, 1957h) * French (9.3G, 754h) * German (14G, 1083h) * Italian (2.2G, 155h) * Kinyarwanda (6.1G, 422h) * Persian (4.5G, 327h) * Polish (1.8G, 130h) * Russian (2.1G, 137h) * Spanish (4.9G, 349h) * Welsh (4.5G, 108h) ## Dataset Structure ### Data Instances ```python {'file': 'абзар_common_voice_tt_17737010.opus', 'is_valid': True, 'language': 0, 'speaker_id': '687025afd5ce033048472754c8d2cb1cf8a617e469866bbdb3746e2bb2194202094a715906f91feb1c546893a5d835347f4869e7def2e360ace6616fb4340e38', 'gender': 0, 'keyword': 'абзар', 'audio': {'path': 'абзар_common_voice_tt_17737010.opus', 'array': array([2.03458695e-34, 2.03458695e-34, 2.03458695e-34, ..., 2.03458695e-34, 2.03458695e-34, 2.03458695e-34]), 'sampling_rate': 48000}} ``` ### Data Fields * file: strinrelative audio path inside the archive * is_valid: if a sample is valid * language: language of an instance. Makes sense only when providing multiple languages to the dataset loader (for example, `load_dataset("ml_spoken_words", languages=["ar", "tt"])`) * speaker_id: unique id of a speaker. Can be "NA" if an instance is invalid * gender: speaker gender. Can be one of `["MALE", "FEMALE", "OTHER", "NAN"]` * keyword: word spoken in a current sample * audio: a dictionary containing the relative path to the 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]` ### Data Splits The data for each language is splitted into train / validation / test parts. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization The data comes form Common Voice dataset. #### 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 he dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers. ## 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 The dataset is licensed under [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) and can be used for academic research and commercial applications in keyword spotting and spoken term search. ### Citation Information ``` @inproceedings{mazumder2021multilingual, title={Multilingual Spoken Words Corpus}, author={Mazumder, Mark and Chitlangia, Sharad and Banbury, Colby and Kang, Yiping and Ciro, Juan Manuel and Achorn, Keith and Galvez, Daniel and Sabini, Mark and Mattson, Peter and Kanter, David and others}, booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)}, year={2021} } ``` ### Contributions Thanks to [@polinaeterna](https://github.com/polinaeterna) for adding this dataset.	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ar_sarcasm	null	2023-03-16T14:13:22Z	377	8	[ "task_categories:text-classification", "task_ids:sentiment-classification", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:extended\|other-semeval_2017", "source_datasets:extended\|other-astd", "language:ar", "license:mit", "sarcasm-detection", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - ar license: - mit multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - extended\|other-semeval_2017 - extended\|other-astd task_categories: - text-classification task_ids: - sentiment-classification pretty_name: ArSarcasm tags: - sarcasm-detection dataset_info: features: - name: dialect dtype: class_label: names: '0': egypt '1': gulf '2': levant '3': magreb '4': msa - name: sarcasm dtype: class_label: names: '0': non-sarcastic '1': sarcastic - name: sentiment dtype: class_label: names: '0': negative '1': neutral '2': positive - name: original_sentiment dtype: class_label: names: '0': negative '1': neutral '2': positive - name: tweet dtype: string - name: source dtype: string splits: - name: train num_bytes: 1829167 num_examples: 8437 - name: test num_bytes: 458218 num_examples: 2110 download_size: 750717 dataset_size: 2287385 --- # Dataset Card for ArSarcasm ## 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 - Repository: [GitHub](https://github.com/iabufarha/ArSarcasm) - Paper: https://www.aclweb.org/anthology/2020.osact-1.5/ ### Dataset Summary ArSarcasm is a new Arabic sarcasm detection dataset. The dataset was created using previously available Arabic sentiment analysis datasets ([SemEval 2017](https://www.aclweb.org/anthology/S17-2088.pdf) and [ASTD](https://www.aclweb.org/anthology/D15-1299.pdf)) and adds sarcasm and dialect labels to them. The dataset contains 10,547 tweets, 1,682 (16%) of which are sarcastic. For more details, please check the paper [From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset](https://www.aclweb.org/anthology/2020.osact-1.5/) ### Supported Tasks and Leaderboards You can get more information about an Arabic sarcasm tasks and leaderboard [here](https://sites.google.com/view/ar-sarcasm-sentiment-detection/). ### Languages Arabic (multiple dialects) ## Dataset Structure ### Data Instances ```javascript {'dialect': 1, 'original_sentiment': 0, 'sarcasm': 0, 'sentiment': 0, 'source': 'semeval', 'tweet': 'نصيحه ما عمرك اتنزل لعبة سوبر ماريو مش زي ما كنّا متوقعين الله يرحم ايامات السيقا والفاميلي #SuperMarioRun'} ``` ### Data Fields - tweet: the original tweet text - sarcasm: 0 for non-sarcastic, 1 for sarcastic - sentiment: 0 for negative, 1 for neutral, 2 for positive - original_sentiment: 0 for negative, 1 for neutral, 2 for positive - source: the original source of tweet: SemEval or ASTD - dialect: 0 for Egypt, 1 for Gulf, 2 for Levant, 3 for Magreb, 4 for Modern Standard Arabic (MSA) ### Data Splits The training set contains 8,437 tweets, while the test set contains 2,110 tweets. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD) and adds sarcasm and dialect labels to them. #### Who are the source language producers? SemEval 2017 and ASTD ### Annotations #### Annotation process For the annotation process, we used Figure-Eight crowdsourcing platform. Our main objective was to annotate the data for sarcasm detection, but due to the challenges imposed by dialectal variations, we decided to add the annotation for dialects. We also include a new annotation for sentiment labels in order to have a glimpse of the variability and subjectivity between different annotators. Thus, the annotators were asked to provide three labels for each tweet as the following: - Sarcasm: sarcastic or non-sarcastic. - Sentiment: positive, negative or neutral. - Dialect: Egyptian, Gulf, Levantine, Maghrebi or Modern Standard Arabic (MSA). #### Who are the annotators? Figure-Eight crowdsourcing platform ### 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 - Ibrahim Abu-Farha - Walid Magdy ### Licensing Information MIT ### Citation Information ``` @inproceedings{abu-farha-magdy-2020-arabic, title = "From {A}rabic Sentiment Analysis to Sarcasm Detection: The {A}r{S}arcasm Dataset", author = "Abu Farha, Ibrahim and Magdy, Walid", booktitle = "Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection", month = may, year = "2020", address = "Marseille, France", publisher = "European Language Resource Association", url = "https://www.aclweb.org/anthology/2020.osact-1.5", pages = "32--39", language = "English", ISBN = "979-10-95546-51-1", } ``` ### Contributions Thanks to [@mapmeld](https://github.com/mapmeld) for adding this dataset.	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danish_political_comments	null	2023-11-24T16:12:39Z	377	0	[ "task_categories:text-classification", "task_ids:multi-class-classification", "annotations_creators:expert-generated", "language_creators:other", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:da", "license:unknown", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - other language: - da license: - unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - multi-class-classification pretty_name: DanishPoliticalComments dataset_info: features: - name: id dtype: string - name: sentence dtype: string - name: target dtype: class_label: names: '0': '2' '1': '1' '2': '0' '3': '-1' '4': '-2' splits: - name: train num_bytes: 829569 num_examples: 9008 download_size: 690873 dataset_size: 829569 --- # Dataset Card for DanishPoliticalComments ## 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://github.com/steffan267/Sentiment-Analysis-on-Danish-Social-Media - Repository: https://github.com/steffan267/Sentiment-Analysis-on-Danish-Social-Media - Paper: https://github.com/lucaspuvis/SAM/blob/master/Thesis.pdf - Point of Contact: [More Information Needed] ### Dataset Summary The dataset consists of 9008 sentences that are labeled with fine-grained polarity in the range from -2 to 2 (negative to positive). The quality of the fine-grained is not cross-validated and is therefore subject to uncertainties; however, the simple polarity has been cross-validated and therefore is considered to be more correct. ### 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 [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### 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 [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.	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DDSC/angry-tweets	DDSC	2023-07-20T00:34:34Z	377	1	[ "task_categories:text-classification", "task_ids:sentiment-classification", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:da", "license:cc-by-4.0", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - found language: - da license: - cc-by-4.0 multilinguality: - monolingual pretty_name: AngryTweets size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification --- # Dataset Card for AngryTweets ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Paper: https://aclanthology.org/2021.nodalida-main.53/ - Direct Download: https://danlp-downloads.alexandra.dk/datasets/game_tweets.zip ### Dataset Summary This dataset consists of anonymised Danish Twitter data that has been annotated for sentiment analysis through crowd-sourcing. All credits go to the authors of the following paper, who created the dataset: [Pauli, Amalie Brogaard, et al. "DaNLP: An open-source toolkit for Danish Natural Language Processing." Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). 2021](https://aclanthology.org/2021.nodalida-main.53/) ### Supported Tasks and Leaderboards This dataset is suitable for sentiment analysis. ### Languages This dataset is in Danish. ## Dataset Structure ### Data Instances Every entry in the dataset has a tweet and an associated label. ### Data Fields An entry in the dataset consists of the following fields: - `text` (`str`): The tweet content. - `label` (`str`): The label of the `text`. Can be "positiv", "neutral" or "negativ" for positive, neutral and negative sentiment, respectively. ### Data Splits A `train` and `test` split is available, with the test split being 30% of the dataset, randomly sampled in a stratified fashion. There are 2,437 tweets in the training split and 1,047 in the test split. ## Additional Information ### Dataset Curators The collection and annotation of the dataset is solely due to the authors of [the original paper](https://aclanthology.org/2021.nodalida-main.53/): Amalie Brogaard Pauli, Maria Barrett, Ophélie Lacroix and Rasmus Hvingelby. The tweets have been anonymised by [@saattrupdan](https://github.com/saattrupdan). ### Licensing Information The dataset is released under the CC BY 4.0 license. ### Citation Information ``` @inproceedings{pauli2021danlp, title={DaNLP: An open-source toolkit for Danish Natural Language Processing}, author={Pauli, Amalie Brogaard and Barrett, Maria and Lacroix, Oph{\'e}lie and Hvingelby, Rasmus}, booktitle={Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)}, pages={460--466}, year={2021} } ``` ### Contributions Thanks to [@saattrupdan](https://github.com/saattrupdan) for adding this dataset to the Hugging Face Hub.	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vincentmin/eli5_rlhf_explainlikeim5	vincentmin	2023-04-10T10:52:49Z	377	7	[ "task_categories:text-generation", "task_categories:question-answering", "size_categories:100K<n<1M", "language:en", "region:us" ]	[ "text-generation", "question-answering" ]	2023-04-07T19:22:14Z	--- task_categories: - text-generation - question-answering language: - en pretty_name: Reddit Explain Like I'm 5 for Reinforcement Learning Human Feedback size_categories: - 100K<n<1M --- # ELI5 paired This is a processed version of the [`eli5`](https://huggingface.co/datasets/eli5) dataset. Compared to ["eli5_rlhf"](https://huggingface.co/datasets/vincentmin/eli5_rlhf), this dataset contains only QA pairs from the train split of the eli5 dataset and only from the subreddit explainlikeimfive. Furthermore, the function ``` def get_question(example): title = example["title"] selftext = example["selftext"] if selftext: if selftext[-1] not in [".", "?", "!"]: seperator = ". " else: seperator = " " question = title + seperator + selftext else: question = title example["question"] = question return example ``` was applied to get the "question" column and the "title" and "selftext" columns were removed. The dataset was created following very closely the steps in the [`stack-exchange-paired`](https://huggingface.co/datasets/lvwerra/stack-exchange-paired) dataset. The following steps were applied: - The "question" field is a concatenation of "title" with "selftext". - Create pairs `(response_j, response_k)` where j was rated better than k - Sample at most 10 pairs per question - Shuffle the dataset globally This dataset is designed to be used for preference learning. The processing notebook is in the repository as well.	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open-llm-leaderboard/details_lgaalves__llama-2-13b-hf-platypus	open-llm-leaderboard	2023-10-28T02:34:08Z	377	0	[ "region:us" ]	null	2023-09-18T14:16:10Z	--- pretty_name: Evaluation run of lgaalves/llama-2-13b-hf-platypus dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lgaalves/llama-2-13b-hf-platypus](https://huggingface.co/lgaalves/llama-2-13b-hf-platypus)\ \ 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_lgaalves__llama-2-13b-hf-platypus\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T02:33:59.939371](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__llama-2-13b-hf-platypus/blob/main/results_2023-10-28T02-33-59.939371.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\": 0.00043200973460388544,\n \"f1\": 0.05985213926174496,\n\ \ \"f1_stderr\": 0.0013641672120704657,\n \"acc\": 0.4325617395685546,\n\ \ \"acc_stderr\": 0.009923090021448928\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0017827181208053692,\n \"em_stderr\": 0.00043200973460388544,\n\ \ \"f1\": 0.05985213926174496,\n \"f1_stderr\": 0.0013641672120704657\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.09401061410159212,\n \ \ \"acc_stderr\": 0.00803881981887246\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.771112865035517,\n \"acc_stderr\": 0.011807360224025398\n\ \ }\n}\n```" repo_url: https://huggingface.co/lgaalves/llama-2-13b-hf-platypus 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_18T14_15_46.670153 path: - '/details_harness\|arc:challenge\|25_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-18T14-15-46.670153.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T00_17_42.072889 path: - '/details_harness\|drop\|3_2023-10-28T00-17-42.072889.parquet' - split: 2023_10_28T02_33_59.939371 path: - '/details_harness\|drop\|3_2023-10-28T02-33-59.939371.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T02-33-59.939371.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T00_17_42.072889 path: - '/details_harness\|gsm8k\|5_2023-10-28T00-17-42.072889.parquet' - split: 2023_10_28T02_33_59.939371 path: - '/details_harness\|gsm8k\|5_2023-10-28T02-33-59.939371.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T02-33-59.939371.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hellaswag\|10_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-15-46.670153.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-15-46.670153.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_18T14_15_46.670153 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-18T14-15-46.670153.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-18T14-15-46.670153.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T00_17_42.072889 path: - '/details_harness\|winogrande\|5_2023-10-28T00-17-42.072889.parquet' - split: 2023_10_28T02_33_59.939371 path: - '/details_harness\|winogrande\|5_2023-10-28T02-33-59.939371.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T02-33-59.939371.parquet' - config_name: results data_files: - split: 2023_09_18T14_15_46.670153 path: - results_2023-09-18T14-15-46.670153.parquet - split: 2023_10_28T00_17_42.072889 path: - results_2023-10-28T00-17-42.072889.parquet - split: 2023_10_28T02_33_59.939371 path: - results_2023-10-28T02-33-59.939371.parquet - split: latest path: - results_2023-10-28T02-33-59.939371.parquet --- # Dataset Card for Evaluation run of lgaalves/llama-2-13b-hf-platypus ## Dataset Description - Homepage: - Repository: https://huggingface.co/lgaalves/llama-2-13b-hf-platypus - 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 [lgaalves/llama-2-13b-hf-platypus](https://huggingface.co/lgaalves/llama-2-13b-hf-platypus) 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_lgaalves__llama-2-13b-hf-platypus", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T02:33:59.939371](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__llama-2-13b-hf-platypus/blob/main/results_2023-10-28T02-33-59.939371.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": 0.00043200973460388544, "f1": 0.05985213926174496, "f1_stderr": 0.0013641672120704657, "acc": 0.4325617395685546, "acc_stderr": 0.009923090021448928 }, "harness\|drop\|3": { "em": 0.0017827181208053692, "em_stderr": 0.00043200973460388544, "f1": 0.05985213926174496, "f1_stderr": 0.0013641672120704657 }, "harness\|gsm8k\|5": { "acc": 0.09401061410159212, "acc_stderr": 0.00803881981887246 }, "harness\|winogrande\|5": { "acc": 0.771112865035517, "acc_stderr": 0.011807360224025398 } } ``` ### 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]	[ -0.38781824707984924, -0.6606348156929016, 0.27870267629623413, 0.32998961210250854, -0.24573832750320435, 0.24473248422145844, -0.3783058524131775, -0.22396716475486755, 0.4718346893787384, 0.5155143141746521, -0.7070090770721436, -0.9140905737876892, -0.6919901371002197, 0.24199382960796356, -0.15704874694347382, 1.1596989631652832, -0.29107216000556946, -0.3140006363391876, 0.02042967639863491, -0.28662124276161194, -0.3509800434112549, -0.4116464853286743, -0.40249237418174744, 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open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-dolphin_5w	open-llm-leaderboard	2023-10-28T08:56:57Z	376	0	[ "region:us" ]	null	2023-08-29T20:18:03Z	--- pretty_name: Evaluation run of CHIH-HUNG/llama-2-13b-dolphin_5w dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CHIH-HUNG/llama-2-13b-dolphin_5w](https://huggingface.co/CHIH-HUNG/llama-2-13b-dolphin_5w)\ \ 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_CHIH-HUNG__llama-2-13b-dolphin_5w\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T08:56:45.584398](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-dolphin_5w/blob/main/results_2023-10-28T08-56-45.584398.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\": 0.004614093959731544,\n\ \ \"em_stderr\": 0.0006940305886353427,\n \"f1\": 0.06955327181208026,\n\ \ \"f1_stderr\": 0.001514906421482751,\n \"acc\": 0.44587604036206907,\n\ \ \"acc_stderr\": 0.010329612453566641\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.004614093959731544,\n \"em_stderr\": 0.0006940305886353427,\n\ \ \"f1\": 0.06955327181208026,\n \"f1_stderr\": 0.001514906421482751\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.11827141774071266,\n \ \ \"acc_stderr\": 0.008895075852434951\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7734806629834254,\n \"acc_stderr\": 0.011764149054698329\n\ \ }\n}\n```" repo_url: https://huggingface.co/CHIH-HUNG/llama-2-13b-dolphin_5w 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_29T20_17_39.109039 path: - '/details_harness\|arc:challenge\|25_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-29T20:17:39.109039.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T08_56_45.584398 path: - '/details_harness\|drop\|3_2023-10-28T08-56-45.584398.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T08-56-45.584398.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T08_56_45.584398 path: - '/details_harness\|gsm8k\|5_2023-10-28T08-56-45.584398.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T08-56-45.584398.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hellaswag\|10_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T20:17:39.109039.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-29T20:17:39.109039.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_29T20_17_39.109039 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-29T20:17:39.109039.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-29T20:17:39.109039.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T08_56_45.584398 path: - '/details_harness\|winogrande\|5_2023-10-28T08-56-45.584398.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T08-56-45.584398.parquet' - config_name: results data_files: - split: 2023_08_29T20_17_39.109039 path: - results_2023-08-29T20:17:39.109039.parquet - split: 2023_10_28T08_56_45.584398 path: - results_2023-10-28T08-56-45.584398.parquet - split: latest path: - results_2023-10-28T08-56-45.584398.parquet --- # Dataset Card for Evaluation run of CHIH-HUNG/llama-2-13b-dolphin_5w ## Dataset Description - Homepage: - Repository: https://huggingface.co/CHIH-HUNG/llama-2-13b-dolphin_5w - 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-dolphin_5w](https://huggingface.co/CHIH-HUNG/llama-2-13b-dolphin_5w) 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_CHIH-HUNG__llama-2-13b-dolphin_5w", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T08:56:45.584398](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-dolphin_5w/blob/main/results_2023-10-28T08-56-45.584398.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": 0.004614093959731544, "em_stderr": 0.0006940305886353427, "f1": 0.06955327181208026, "f1_stderr": 0.001514906421482751, "acc": 0.44587604036206907, "acc_stderr": 0.010329612453566641 }, "harness\|drop\|3": { "em": 0.004614093959731544, "em_stderr": 0.0006940305886353427, "f1": 0.06955327181208026, "f1_stderr": 0.001514906421482751 }, "harness\|gsm8k\|5": { "acc": 0.11827141774071266, "acc_stderr": 0.008895075852434951 }, "harness\|winogrande\|5": { "acc": 0.7734806629834254, "acc_stderr": 0.011764149054698329 } } ``` ### 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]	[ -0.433538019657135, -0.680441677570343, 0.2374527007341385, 0.285052090883255, -0.30169105529785156, 0.17815960943698883, -0.32573673129081726, -0.3330788016319275, 0.45042136311531067, 0.5393332839012146, -0.7094782590866089, -0.8778384923934937, -0.7270389795303345, 0.29755261540412903, -0.1323731392621994, 1.1652463674545288, -0.2205067276954651, -0.22654829919338226, 0.12008240818977356, -0.3223322927951813, -0.3933561146259308, -0.34706979990005493, -0.4501015543937683, 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cail2018	null	2022-11-18T19:24:58Z	375	8	[ "task_categories:other", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:1M<n<10M", "source_datasets:original", "language:zh", "license:unknown", "judgement-prediction", "arxiv:1807.02478", "region:us" ]	[ "other" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - zh license: - unknown multilinguality: - monolingual size_categories: - 1M<n<10M source_datasets: - original task_categories: - other task_ids: [] paperswithcode_id: chinese-ai-and-law-cail-2018 pretty_name: CAIL 2018 tags: - judgement-prediction dataset_info: features: - name: fact dtype: string - name: relevant_articles sequence: int32 - name: accusation sequence: string - name: punish_of_money dtype: float32 - name: criminals sequence: string - name: death_penalty dtype: bool - name: imprisonment dtype: float32 - name: life_imprisonment dtype: bool splits: - name: exercise_contest_train num_bytes: 220112732 num_examples: 154592 - name: exercise_contest_valid num_bytes: 21702157 num_examples: 17131 - name: exercise_contest_test num_bytes: 41057634 num_examples: 32508 - name: first_stage_train num_bytes: 1779657510 num_examples: 1710856 - name: first_stage_test num_bytes: 244335194 num_examples: 217016 - name: final_test num_bytes: 44194707 num_examples: 35922 download_size: 984551626 dataset_size: 2351059934 --- --- # Dataset Card for CAIL 2018 ## 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: [Github](https://github.com/thunlp/CAIL/blob/master/README_en.md) - Repository: [Github](https://github.com/thunlp/CAIL) - Paper: [Arxiv](https://arxiv.org/abs/1807.02478) - 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 [@JetRunner](https://github.com/JetRunner) for adding this dataset.	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code_x_glue_cc_clone_detection_poj104	null	2023-03-13T11:02:07Z	375	3	[ "task_categories:text-retrieval", "task_ids:document-retrieval", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:code", "license:c-uda", "region:us" ]	[ "text-retrieval" ]	2022-03-02T23:29:22Z	--- pretty_name: CodeXGlueCcCloneDetectionPoj104 annotations_creators: - found language_creators: - found language: - code license: - c-uda multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-retrieval task_ids: - document-retrieval dataset_info: features: - name: id dtype: int32 - name: code dtype: string - name: label dtype: string splits: - name: train num_bytes: 20179075 num_examples: 32500 - name: validation num_bytes: 6382433 num_examples: 8500 - name: test num_bytes: 7227506 num_examples: 12000 download_size: 8658581 dataset_size: 33789014 --- # Dataset Card for "code_x_glue_cc_clone_detection_poj_104" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits-sample-size) - [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://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-POJ-104 ### Dataset Summary CodeXGLUE Clone-detection-POJ-104 dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-POJ-104 Given a code and a collection of candidates as the input, the task is to return Top K codes with the same semantic. Models are evaluated by MAP score. We use POJ-104 dataset on this task. ### Supported Tasks and Leaderboards - `document-retrieval`: The dataset can be used to train a model for retrieving top-k codes with the same semantics. ### Languages - C++ programming language ## Dataset Structure ### Data Instances An example of 'train' looks as follows. ``` { "code": "\nint f(int shu,int min)\n{ \n int k=1;\n if(shu < min)\n { \n k= 0; \n return k;\n } \n else\n {\n for(int i = min;i<shu;i++)\n { \n if(shu%i == 0)\n { \n k=k+ f(shu/i,i); \n } \n \n \n } \n return k; \n}\n} \n\nmain()\n{\n int n,i,a;\n scanf(\"%d\",&n);\n \n for(i=0;i<n;i++)\n {\n scanf(\"%d\",&a);\n \n if(i!=n-1) \n printf(\"%d\\n\",f(a,2));\n else\n printf(\"%d\",f(a,2)); \n \n \n \n } \n \n \n }", "id": 0, "label": "home" } ``` ### Data Fields In the following each data field in go is explained for each config. The data fields are the same among all splits. #### default \|field name\| type \| description \| \|----------\|------\|----------------------------------------------\| \|id \|int32 \| Index of the sample \| \|code \|string\| The full text of the function \| \|label \|string\| The id of problem that the source code solves\| ### Data Splits \| name \|train\|validation\|test \| \|-------\|----:\|---------:\|----:\| \|default\|32000\| 8000\|12000\| ## 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 https://github.com/microsoft, https://github.com/madlag ### Licensing Information Computational Use of Data Agreement (C-UDA) License. ### Citation Information ``` @inproceedings{mou2016convolutional, title={Convolutional neural networks over tree structures for programming language processing}, author={Mou, Lili and Li, Ge and Zhang, Lu and Wang, Tao and Jin, Zhi}, booktitle={Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence}, pages={1287--1293}, year={2016} } ``` ### Contributions Thanks to @madlag (and partly also @ncoop57) for adding this dataset.	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open-llm-leaderboard/details_kfkas__Llama-2-ko-7b-Chat	open-llm-leaderboard	2023-09-18T06:21:05Z	375	0	[ "region:us" ]	null	2023-08-18T00:02:13Z	--- pretty_name: Evaluation run of kfkas/Llama-2-ko-7b-Chat dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [kfkas/Llama-2-ko-7b-Chat](https://huggingface.co/kfkas/Llama-2-ko-7b-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 4 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_kfkas__Llama-2-ko-7b-Chat\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-18T06:20:53.119467](https://huggingface.co/datasets/open-llm-leaderboard/details_kfkas__Llama-2-ko-7b-Chat/blob/main/results_2023-09-18T06-20-53.119467.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\": 0.029886744966442953,\n\ \ \"em_stderr\": 0.0017437739254467523,\n \"f1\": 0.11206061241610675,\n\ \ \"f1_stderr\": 0.002589360675643281,\n \"acc\": 0.3406984196130502,\n\ \ \"acc_stderr\": 0.008168649232732146\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.029886744966442953,\n \"em_stderr\": 0.0017437739254467523,\n\ \ \"f1\": 0.11206061241610675,\n \"f1_stderr\": 0.002589360675643281\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.01288855193328279,\n \ \ \"acc_stderr\": 0.003106901266499642\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6685082872928176,\n \"acc_stderr\": 0.01323039719896465\n\ \ }\n}\n```" repo_url: https://huggingface.co/kfkas/Llama-2-ko-7b-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_07_27T10_54_54.901743 path: - '/details_harness\|arc:challenge\|25_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|arc:challenge\|25_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-27T16:15:02.960730.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T05_11_56.274160 path: - '/details_harness\|drop\|3_2023-09-17T05-11-56.274160.parquet' - split: 2023_09_18T06_20_53.119467 path: - '/details_harness\|drop\|3_2023-09-18T06-20-53.119467.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-18T06-20-53.119467.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T05_11_56.274160 path: - '/details_harness\|gsm8k\|5_2023-09-17T05-11-56.274160.parquet' - split: 2023_09_18T06_20_53.119467 path: - '/details_harness\|gsm8k\|5_2023-09-18T06-20-53.119467.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-18T06-20-53.119467.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hellaswag\|10_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hellaswag\|10_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:54:54.901743.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T16:15:02.960730.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-27T16:15:02.960730.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_27T10_54_54.901743 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-27T10:54:54.901743.parquet' - split: 2023_07_27T16_15_02.960730 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-27T16:15:02.960730.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-27T16:15:02.960730.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T05_11_56.274160 path: - '/details_harness\|winogrande\|5_2023-09-17T05-11-56.274160.parquet' - split: 2023_09_18T06_20_53.119467 path: - '/details_harness\|winogrande\|5_2023-09-18T06-20-53.119467.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-18T06-20-53.119467.parquet' - config_name: results data_files: - split: 2023_07_27T10_54_54.901743 path: - results_2023-07-27T10:54:54.901743.parquet - split: 2023_07_27T16_15_02.960730 path: - results_2023-07-27T16:15:02.960730.parquet - split: 2023_09_17T05_11_56.274160 path: - results_2023-09-17T05-11-56.274160.parquet - split: 2023_09_18T06_20_53.119467 path: - results_2023-09-18T06-20-53.119467.parquet - split: latest path: - results_2023-09-18T06-20-53.119467.parquet --- # Dataset Card for Evaluation run of kfkas/Llama-2-ko-7b-Chat ## Dataset Description - Homepage: - Repository: https://huggingface.co/kfkas/Llama-2-ko-7b-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 [kfkas/Llama-2-ko-7b-Chat](https://huggingface.co/kfkas/Llama-2-ko-7b-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 4 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_kfkas__Llama-2-ko-7b-Chat", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-18T06:20:53.119467](https://huggingface.co/datasets/open-llm-leaderboard/details_kfkas__Llama-2-ko-7b-Chat/blob/main/results_2023-09-18T06-20-53.119467.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": 0.029886744966442953, "em_stderr": 0.0017437739254467523, "f1": 0.11206061241610675, "f1_stderr": 0.002589360675643281, "acc": 0.3406984196130502, "acc_stderr": 0.008168649232732146 }, "harness\|drop\|3": { "em": 0.029886744966442953, "em_stderr": 0.0017437739254467523, "f1": 0.11206061241610675, "f1_stderr": 0.002589360675643281 }, "harness\|gsm8k\|5": { "acc": 0.01288855193328279, "acc_stderr": 0.003106901266499642 }, "harness\|winogrande\|5": { "acc": 0.6685082872928176, "acc_stderr": 0.01323039719896465 } } ``` ### 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]	[ -0.37358349561691284, -0.6774166226387024, 0.2608399987220764, 0.32709112763404846, -0.33371877670288086, 0.29131364822387695, -0.2751018702983856, -0.23798373341560364, 0.49929189682006836, 0.5697265863418579, -0.6472985148429871, -0.9409223794937134, -0.7546988129615784, 0.16233380138874054, -0.13854601979255676, 1.197127103805542, -0.1619231253862381, -0.27366989850997925, 0.05253647640347481, -0.1954757422208786, -0.4963986575603485, -0.3876674771308899, -0.44101646542549133, 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open-llm-leaderboard/details_pszemraj__pythia-31m-KI_v1-2048-scratch	open-llm-leaderboard	2023-10-28T08:49:08Z	375	0	[ "region:us" ]	null	2023-09-15T05:01:31Z	--- pretty_name: Evaluation run of pszemraj/pythia-31m-KI_v1-2048-scratch dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [pszemraj/pythia-31m-KI_v1-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-KI_v1-2048-scratch)\ \ 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_pszemraj__pythia-31m-KI_v1-2048-scratch\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T08:48:56.484110](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-KI_v1-2048-scratch/blob/main/results_2023-10-28T08-48-56.484110.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\": 0.009437919463087249,\n\ \ \"em_stderr\": 0.0009901902239103783,\n \"f1\": 0.015236996644295321,\n\ \ \"f1_stderr\": 0.0010823937767906837,\n \"acc\": 0.25887924230465664,\n\ \ \"acc_stderr\": 0.007021809798087482\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.009437919463087249,\n \"em_stderr\": 0.0009901902239103783,\n\ \ \"f1\": 0.015236996644295321,\n \"f1_stderr\": 0.0010823937767906837\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5177584846093133,\n\ \ \"acc_stderr\": 0.014043619596174964\n }\n}\n```" repo_url: https://huggingface.co/pszemraj/pythia-31m-KI_v1-2048-scratch 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_15T05_01_19.324903 path: - '/details_harness\|arc:challenge\|25_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-15T05-01-19.324903.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T08_48_56.484110 path: - '/details_harness\|drop\|3_2023-10-28T08-48-56.484110.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T08-48-56.484110.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T08_48_56.484110 path: - '/details_harness\|gsm8k\|5_2023-10-28T08-48-56.484110.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T08-48-56.484110.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hellaswag\|10_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T05-01-19.324903.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-15T05-01-19.324903.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T05_01_19.324903 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-15T05-01-19.324903.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-15T05-01-19.324903.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T08_48_56.484110 path: - '/details_harness\|winogrande\|5_2023-10-28T08-48-56.484110.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T08-48-56.484110.parquet' - config_name: results data_files: - split: 2023_09_15T05_01_19.324903 path: - results_2023-09-15T05-01-19.324903.parquet - split: 2023_10_28T08_48_56.484110 path: - results_2023-10-28T08-48-56.484110.parquet - split: latest path: - results_2023-10-28T08-48-56.484110.parquet --- # Dataset Card for Evaluation run of pszemraj/pythia-31m-KI_v1-2048-scratch ## Dataset Description - Homepage: - Repository: https://huggingface.co/pszemraj/pythia-31m-KI_v1-2048-scratch - 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 [pszemraj/pythia-31m-KI_v1-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-KI_v1-2048-scratch) 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_pszemraj__pythia-31m-KI_v1-2048-scratch", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T08:48:56.484110](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-KI_v1-2048-scratch/blob/main/results_2023-10-28T08-48-56.484110.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": 0.009437919463087249, "em_stderr": 0.0009901902239103783, "f1": 0.015236996644295321, "f1_stderr": 0.0010823937767906837, "acc": 0.25887924230465664, "acc_stderr": 0.007021809798087482 }, "harness\|drop\|3": { "em": 0.009437919463087249, "em_stderr": 0.0009901902239103783, "f1": 0.015236996644295321, "f1_stderr": 0.0010823937767906837 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5177584846093133, "acc_stderr": 0.014043619596174964 } } ``` ### 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]	[ -0.37764376401901245, -0.662773847579956, 0.26702749729156494, 0.23977521061897278, -0.20997941493988037, 0.18076105415821075, -0.4114934802055359, -0.12287741899490356, 0.43292972445487976, 0.5481856465339661, -0.7611912488937378, -0.9077137112617493, -0.6917691230773926, 0.15598438680171967, -0.12598474323749542, 1.2034879922866821, -0.3039150834083557, -0.15269410610198975, 0.00825317483395338, -0.2009713351726532, -0.2524159848690033, -0.4659397006034851, -0.347593754529953, 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open-llm-leaderboard/details_health360__Healix-410M	open-llm-leaderboard	2023-10-28T06:52:57Z	375	0	[ "region:us" ]	null	2023-09-18T14:26:07Z	--- pretty_name: Evaluation run of health360/Healix-410M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [health360/Healix-410M](https://huggingface.co/health360/Healix-410M) 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_health360__Healix-410M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T06:52:49.299650](https://huggingface.co/datasets/open-llm-leaderboard/details_health360__Healix-410M/blob/main/results_2023-10-28T06-52-49.299650.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\": 0.010591442953020135,\n\ \ \"em_stderr\": 0.0010483469790502306,\n \"f1\": 0.049055159395973116,\n\ \ \"f1_stderr\": 0.0015554088384130706,\n \"acc\": 0.27071823204419887,\n\ \ \"acc_stderr\": 0.007002073426895943\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.010591442953020135,\n \"em_stderr\": 0.0010483469790502306,\n\ \ \"f1\": 0.049055159395973116,\n \"f1_stderr\": 0.0015554088384130706\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5414364640883977,\n\ \ \"acc_stderr\": 0.014004146853791886\n }\n}\n```" repo_url: https://huggingface.co/health360/Healix-410M 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_18T14_25_49.264800 path: - '/details_harness\|arc:challenge\|25_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-18T14-25-49.264800.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T06_49_18.544875 path: - '/details_harness\|drop\|3_2023-10-28T06-49-18.544875.parquet' - split: 2023_10_28T06_52_49.299650 path: - '/details_harness\|drop\|3_2023-10-28T06-52-49.299650.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T06-52-49.299650.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T06_49_18.544875 path: - '/details_harness\|gsm8k\|5_2023-10-28T06-49-18.544875.parquet' - split: 2023_10_28T06_52_49.299650 path: - '/details_harness\|gsm8k\|5_2023-10-28T06-52-49.299650.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T06-52-49.299650.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hellaswag\|10_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-25-49.264800.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-18T14-25-49.264800.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_18T14_25_49.264800 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-18T14-25-49.264800.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-18T14-25-49.264800.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T06_49_18.544875 path: - '/details_harness\|winogrande\|5_2023-10-28T06-49-18.544875.parquet' - split: 2023_10_28T06_52_49.299650 path: - '/details_harness\|winogrande\|5_2023-10-28T06-52-49.299650.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T06-52-49.299650.parquet' - config_name: results data_files: - split: 2023_09_18T14_25_49.264800 path: - results_2023-09-18T14-25-49.264800.parquet - split: 2023_10_28T06_49_18.544875 path: - results_2023-10-28T06-49-18.544875.parquet - split: 2023_10_28T06_52_49.299650 path: - results_2023-10-28T06-52-49.299650.parquet - split: latest path: - results_2023-10-28T06-52-49.299650.parquet --- # Dataset Card for Evaluation run of health360/Healix-410M ## Dataset Description - Homepage: - Repository: https://huggingface.co/health360/Healix-410M - 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 [health360/Healix-410M](https://huggingface.co/health360/Healix-410M) 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_health360__Healix-410M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T06:52:49.299650](https://huggingface.co/datasets/open-llm-leaderboard/details_health360__Healix-410M/blob/main/results_2023-10-28T06-52-49.299650.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": 0.010591442953020135, "em_stderr": 0.0010483469790502306, "f1": 0.049055159395973116, "f1_stderr": 0.0015554088384130706, "acc": 0.27071823204419887, "acc_stderr": 0.007002073426895943 }, "harness\|drop\|3": { "em": 0.010591442953020135, "em_stderr": 0.0010483469790502306, "f1": 0.049055159395973116, "f1_stderr": 0.0015554088384130706 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5414364640883977, "acc_stderr": 0.014004146853791886 } } ``` ### 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]	[ -0.3506942391395569, -0.43703803420066833, 0.3073136806488037, 0.24130329489707947, -0.08359479904174805, 0.08986656367778778, -0.27808329463005066, -0.2043255865573883, 0.40777119994163513, 0.5903244614601135, -0.7519124150276184, -1.0325214862823486, -0.6478865742683411, 0.3392915427684784, -0.01601555570960045, 1.1775543689727783, -0.28412359952926636, -0.14103569090366364, 0.008050772361457348, -0.4787214398384094, -0.2956555187702179, -0.3930228352546692, -0.5085998773574829, 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open-llm-leaderboard/details_llm-agents__tora-7b-v1.0	open-llm-leaderboard	2023-10-27T12:52:43Z	375	0	[ "region:us" ]	null	2023-10-10T14:34:35Z	--- pretty_name: Evaluation run of llm-agents/tora-7b-v1.0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [llm-agents/tora-7b-v1.0](https://huggingface.co/llm-agents/tora-7b-v1.0) 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_llm-agents__tora-7b-v1.0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-27T12:52:31.057587](https://huggingface.co/datasets/open-llm-leaderboard/details_llm-agents__tora-7b-v1.0/blob/main/results_2023-10-27T12-52-31.057587.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\": 0.03166946308724832,\n\ \ \"em_stderr\": 0.001793377907859907,\n \"f1\": 0.0924370805369127,\n\ \ \"f1_stderr\": 0.002203336567209257,\n \"acc\": 0.3803074247848667,\n\ \ \"acc_stderr\": 0.008348384971774042\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.03166946308724832,\n \"em_stderr\": 0.001793377907859907,\n\ \ \"f1\": 0.0924370805369127,\n \"f1_stderr\": 0.002203336567209257\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.025018953752843062,\n \ \ \"acc_stderr\": 0.0043020450465642845\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7355958958168903,\n \"acc_stderr\": 0.012394724896983799\n\ \ }\n}\n```" repo_url: https://huggingface.co/llm-agents/tora-7b-v1.0 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_10T14_34_11.685092 path: - '/details_harness\|arc:challenge\|25_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-10T14-34-11.685092.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_27T12_52_31.057587 path: - '/details_harness\|drop\|3_2023-10-27T12-52-31.057587.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-27T12-52-31.057587.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_27T12_52_31.057587 path: - '/details_harness\|gsm8k\|5_2023-10-27T12-52-31.057587.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-27T12-52-31.057587.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hellaswag\|10_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-34-11.685092.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-34-11.685092.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_10T14_34_11.685092 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T14-34-11.685092.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T14-34-11.685092.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_27T12_52_31.057587 path: - '/details_harness\|winogrande\|5_2023-10-27T12-52-31.057587.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-27T12-52-31.057587.parquet' - config_name: results data_files: - split: 2023_10_10T14_34_11.685092 path: - results_2023-10-10T14-34-11.685092.parquet - split: 2023_10_27T12_52_31.057587 path: - results_2023-10-27T12-52-31.057587.parquet - split: latest path: - results_2023-10-27T12-52-31.057587.parquet --- # Dataset Card for Evaluation run of llm-agents/tora-7b-v1.0 ## Dataset Description - Homepage: - Repository: https://huggingface.co/llm-agents/tora-7b-v1.0 - 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 [llm-agents/tora-7b-v1.0](https://huggingface.co/llm-agents/tora-7b-v1.0) 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_llm-agents__tora-7b-v1.0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-27T12:52:31.057587](https://huggingface.co/datasets/open-llm-leaderboard/details_llm-agents__tora-7b-v1.0/blob/main/results_2023-10-27T12-52-31.057587.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": 0.03166946308724832, "em_stderr": 0.001793377907859907, "f1": 0.0924370805369127, "f1_stderr": 0.002203336567209257, "acc": 0.3803074247848667, "acc_stderr": 0.008348384971774042 }, "harness\|drop\|3": { "em": 0.03166946308724832, "em_stderr": 0.001793377907859907, "f1": 0.0924370805369127, "f1_stderr": 0.002203336567209257 }, "harness\|gsm8k\|5": { "acc": 0.025018953752843062, "acc_stderr": 0.0043020450465642845 }, "harness\|winogrande\|5": { "acc": 0.7355958958168903, "acc_stderr": 0.012394724896983799 } } ``` ### 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]	[ -0.37772655487060547, -0.619478166103363, 0.3156847059726715, 0.2589387595653534, -0.19301703572273254, 0.2904660105705261, -0.23196770250797272, -0.18642978370189667, 0.5115412473678589, 0.5847394466400146, -0.6942533850669861, -0.9581146240234375, -0.6558621525764465, 0.2645276188850403, -0.12477608770132065, 1.005691647529602, -0.14946866035461426, -0.18528378009796143, 0.11232724785804749, -0.3405897617340088, -0.5043994188308716, -0.34249159693717957, -0.5622214674949646, 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BeIR/msmarco-qrels	BeIR	2022-10-23T06:05:55Z	374	1	[ "task_categories:text-retrieval", "task_ids:entity-linking-retrieval", "task_ids:fact-checking-retrieval", "multilinguality:monolingual", "language:en", "license:cc-by-sa-4.0", "region:us" ]	[ "text-retrieval", "zero-shot-retrieval", "information-retrieval", "zero-shot-information-retrieval" ]	2022-06-05T17:26:07Z	--- annotations_creators: [] language_creators: [] language: - en license: - cc-by-sa-4.0 multilinguality: - monolingual paperswithcode_id: beir pretty_name: BEIR Benchmark size_categories: msmarco: - 1M<n<10M trec-covid: - 100k<n<1M nfcorpus: - 1K<n<10K nq: - 1M<n<10M hotpotqa: - 1M<n<10M fiqa: - 10K<n<100K arguana: - 1K<n<10K touche-2020: - 100K<n<1M cqadupstack: - 100K<n<1M quora: - 100K<n<1M dbpedia: - 1M<n<10M scidocs: - 10K<n<100K fever: - 1M<n<10M climate-fever: - 1M<n<10M scifact: - 1K<n<10K source_datasets: [] task_categories: - text-retrieval - zero-shot-retrieval - information-retrieval - zero-shot-information-retrieval task_ids: - passage-retrieval - entity-linking-retrieval - fact-checking-retrieval - tweet-retrieval - citation-prediction-retrieval - duplication-question-retrieval - argument-retrieval - news-retrieval - biomedical-information-retrieval - question-answering-retrieval --- # Dataset Card for BEIR Benchmark ## 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://github.com/UKPLab/beir - Repository: https://github.com/UKPLab/beir - Paper: https://openreview.net/forum?id=wCu6T5xFjeJ - Leaderboard: https://docs.google.com/spreadsheets/d/1L8aACyPaXrL8iEelJLGqlMqXKPX2oSP_R10pZoy77Ns - Point of Contact: [email protected] ### Dataset Summary BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks: - Fact-checking: [FEVER](http://fever.ai), [Climate-FEVER](http://climatefever.ai), [SciFact](https://github.com/allenai/scifact) - Question-Answering: [NQ](https://ai.google.com/research/NaturalQuestions), [HotpotQA](https://hotpotqa.github.io), [FiQA-2018](https://sites.google.com/view/fiqa/) - Bio-Medical IR: [TREC-COVID](https://ir.nist.gov/covidSubmit/index.html), [BioASQ](http://bioasq.org), [NFCorpus](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/) - News Retrieval: [TREC-NEWS](https://trec.nist.gov/data/news2019.html), [Robust04](https://trec.nist.gov/data/robust/04.guidelines.html) - Argument Retrieval: [Touche-2020](https://webis.de/events/touche-20/shared-task-1.html), [ArguAna](tp://argumentation.bplaced.net/arguana/data) - Duplicate Question Retrieval: [Quora](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs), [CqaDupstack](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/) - Citation-Prediction: [SCIDOCS](https://allenai.org/data/scidocs) - Tweet Retrieval: [Signal-1M](https://research.signal-ai.com/datasets/signal1m-tweetir.html) - Entity Retrieval: [DBPedia](https://github.com/iai-group/DBpedia-Entity/) All these datasets have been preprocessed and can be used for your experiments. ```python ``` ### Supported Tasks and Leaderboards The dataset supports a leaderboard that evaluates models against task-specific metrics such as F1 or EM, as well as their ability to retrieve supporting information from Wikipedia. The current best performing models can be found [here](https://eval.ai/web/challenges/challenge-page/689/leaderboard/). ### Languages All tasks are in English (`en`). ## Dataset Structure All BEIR datasets must contain a corpus, queries and qrels (relevance judgments file). They must be in the following format: - `corpus` file: a `.jsonl` file (jsonlines) that contains a list of dictionaries, each with three fields `_id` with unique document identifier, `title` with document title (optional) and `text` with document paragraph or passage. For example: `{"_id": "doc1", "title": "Albert Einstein", "text": "Albert Einstein was a German-born...."}` - `queries` file: a `.jsonl` file (jsonlines) that contains a list of dictionaries, each with two fields `_id` with unique query identifier and `text` with query text. For example: `{"_id": "q1", "text": "Who developed the mass-energy equivalence formula?"}` - `qrels` file: a `.tsv` file (tab-seperated) that contains three columns, i.e. the `query-id`, `corpus-id` and `score` in this order. Keep 1st row as header. For example: `q1 doc1 1` ### Data Instances A high level example of any beir dataset: ```python corpus = { "doc1" : { "title": "Albert Einstein", "text": "Albert Einstein was a German-born theoretical physicist. who developed the theory of relativity, \ one of the two pillars of modern physics (alongside quantum mechanics). His work is also known for \ its influence on the philosophy of science. He is best known to the general public for his massâ€“energy \ equivalence formula E = mc2, which has been dubbed 'the world's most famous equation'. He received the 1921 \ Nobel Prize in Physics 'for his services to theoretical physics, and especially for his discovery of the law \ of the photoelectric effect', a pivotal step in the development of quantum theory." }, "doc2" : { "title": "", # Keep title an empty string if not present "text": "Wheat beer is a top-fermented beer which is brewed with a large proportion of wheat relative to the amount of \ malted barley. The two main varieties are German WeiÃŸbier and Belgian witbier; other types include Lambic (made\ with wild yeast), Berliner Weisse (a cloudy, sour beer), and Gose (a sour, salty beer)." }, } queries = { "q1" : "Who developed the mass-energy equivalence formula?", "q2" : "Which beer is brewed with a large proportion of wheat?" } qrels = { "q1" : {"doc1": 1}, "q2" : {"doc2": 1}, } ``` ### Data Fields Examples from all configurations have the following features: ### Corpus - `corpus`: a `dict` feature representing the document title and passage text, made up of: - `_id`: a `string` feature representing the unique document id - `title`: a `string` feature, denoting the title of the document. - `text`: a `string` feature, denoting the text of the document. ### Queries - `queries`: a `dict` feature representing the query, made up of: - `_id`: a `string` feature representing the unique query id - `text`: a `string` feature, denoting the text of the query. ### Qrels - `qrels`: a `dict` feature representing the query document relevance judgements, made up of: - `_id`: a `string` feature representing the query id - `_id`: a `string` feature, denoting the document id. - `score`: a `int32` feature, denoting the relevance judgement between query and document. ### Data Splits \| Dataset \| Website\| BEIR-Name \| Type \| Queries \| Corpus \| Rel D/Q \| Down-load \| md5 \| \| -------- \| -----\| ---------\| --------- \| ----------- \| ---------\| ---------\| :----------: \| :------:\| \| MSMARCO \| [Homepage](https://microsoft.github.io/msmarco/)\| ``msmarco`` \| ``train``<br>``dev``<br>``test``\| 6,980 \| 8.84M \| 1.1 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/msmarco.zip) \| ``444067daf65d982533ea17ebd59501e4`` \| \| TREC-COVID \| [Homepage](https://ir.nist.gov/covidSubmit/index.html)\| ``trec-covid``\| ``test``\| 50\| 171K\| 493.5 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/trec-covid.zip) \| ``ce62140cb23feb9becf6270d0d1fe6d1`` \| \| NFCorpus \| [Homepage](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/) \| ``nfcorpus`` \| ``train``<br>``dev``<br>``test``\| 323 \| 3.6K \| 38.2 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nfcorpus.zip) \| ``a89dba18a62ef92f7d323ec890a0d38d`` \| \| BioASQ \| [Homepage](http://bioasq.org) \| ``bioasq``\| ``train``<br>``test`` \| 500 \| 14.91M \| 8.05 \| No \| [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#2-bioasq) \| \| NQ \| [Homepage](https://ai.google.com/research/NaturalQuestions) \| ``nq``\| ``train``<br>``test``\| 3,452 \| 2.68M \| 1.2 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/nq.zip) \| ``d4d3d2e48787a744b6f6e691ff534307`` \| \| HotpotQA \| [Homepage](https://hotpotqa.github.io) \| ``hotpotqa``\| ``train``<br>``dev``<br>``test``\| 7,405 \| 5.23M \| 2.0 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/hotpotqa.zip) \| ``f412724f78b0d91183a0e86805e16114`` \| \| FiQA-2018 \| [Homepage](https://sites.google.com/view/fiqa/) \| ``fiqa`` \| ``train``<br>``dev``<br>``test``\| 648 \| 57K \| 2.6 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fiqa.zip) \| ``17918ed23cd04fb15047f73e6c3bd9d9`` \| \| Signal-1M(RT) \| [Homepage](https://research.signal-ai.com/datasets/signal1m-tweetir.html)\| ``signal1m`` \| ``test``\| 97 \| 2.86M \| 19.6 \| No \| [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#4-signal-1m) \| \| TREC-NEWS \| [Homepage](https://trec.nist.gov/data/news2019.html) \| ``trec-news`` \| ``test``\| 57 \| 595K \| 19.6 \| No \| [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#1-trec-news) \| \| ArguAna \| [Homepage](http://argumentation.bplaced.net/arguana/data) \| ``arguana``\| ``test`` \| 1,406 \| 8.67K \| 1.0 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/arguana.zip) \| ``8ad3e3c2a5867cdced806d6503f29b99`` \| \| Touche-2020\| [Homepage](https://webis.de/events/touche-20/shared-task-1.html) \| ``webis-touche2020``\| ``test``\| 49 \| 382K \| 19.0 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/webis-touche2020.zip) \| ``46f650ba5a527fc69e0a6521c5a23563`` \| \| CQADupstack\| [Homepage](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/) \| ``cqadupstack``\| ``test``\| 13,145 \| 457K \| 1.4 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/cqadupstack.zip) \| ``4e41456d7df8ee7760a7f866133bda78`` \| \| Quora\| [Homepage](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) \| ``quora``\| ``dev``<br>``test``\| 10,000 \| 523K \| 1.6 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/quora.zip) \| ``18fb154900ba42a600f84b839c173167`` \| \| DBPedia \| [Homepage](https://github.com/iai-group/DBpedia-Entity/) \| ``dbpedia-entity``\| ``dev``<br>``test``\| 400 \| 4.63M \| 38.2 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/dbpedia-entity.zip) \| ``c2a39eb420a3164af735795df012ac2c`` \| \| SCIDOCS\| [Homepage](https://allenai.org/data/scidocs) \| ``scidocs``\| ``test``\| 1,000 \| 25K \| 4.9 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scidocs.zip) \| ``38121350fc3a4d2f48850f6aff52e4a9`` \| \| FEVER \| [Homepage](http://fever.ai) \| ``fever``\| ``train``<br>``dev``<br>``test``\| 6,666 \| 5.42M \| 1.2\| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/fever.zip) \| ``5a818580227bfb4b35bb6fa46d9b6c03`` \| \| Climate-FEVER\| [Homepage](http://climatefever.ai) \| ``climate-fever``\|``test``\| 1,535 \| 5.42M \| 3.0 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/climate-fever.zip) \| ``8b66f0a9126c521bae2bde127b4dc99d`` \| \| SciFact\| [Homepage](https://github.com/allenai/scifact) \| ``scifact``\| ``train``<br>``test``\| 300 \| 5K \| 1.1 \| [Link](https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/scifact.zip) \| ``5f7d1de60b170fc8027bb7898e2efca1`` \| \| Robust04 \| [Homepage](https://trec.nist.gov/data/robust/04.guidelines.html) \| ``robust04``\| ``test``\| 249 \| 528K \| 69.9 \| No \| [How to Reproduce?](https://github.com/UKPLab/beir/blob/main/examples/dataset#3-robust04) \| ## 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 [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information [Needs More Information] ### Citation Information Cite as: ``` @inproceedings{ thakur2021beir, title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models}, author={Nandan Thakur and Nils Reimers and Andreas R{\"u}ckl{\'e} and Abhishek Srivastava and Iryna Gurevych}, booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)}, year={2021}, url={https://openreview.net/forum?id=wCu6T5xFjeJ} } ``` ### Contributions Thanks to [@Nthakur20](https://github.com/Nthakur20) for adding this dataset.	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open-llm-leaderboard/details_Corianas__Quokka_2.7b	open-llm-leaderboard	2023-09-18T03:06:10Z	374	0	[ "region:us" ]	null	2023-08-17T22:25:42Z	--- pretty_name: Evaluation run of Corianas/Quokka_2.7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Corianas/Quokka_2.7b](https://huggingface.co/Corianas/Quokka_2.7b) 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_Corianas__Quokka_2.7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-18T03:05:58.053951](https://huggingface.co/datasets/open-llm-leaderboard/details_Corianas__Quokka_2.7b/blob/main/results_2023-09-18T03-05-58.053951.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\": 0.027055369127516778,\n\ \ \"em_stderr\": 0.0016615386418947858,\n \"f1\": 0.0843078859060403,\n\ \ \"f1_stderr\": 0.0021162612701253174,\n \"acc\": 0.27932236818091244,\n\ \ \"acc_stderr\": 0.007830181847252834\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.027055369127516778,\n \"em_stderr\": 0.0016615386418947858,\n\ \ \"f1\": 0.0843078859060403,\n \"f1_stderr\": 0.0021162612701253174\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0037907505686125853,\n \ \ \"acc_stderr\": 0.0016927007401501802\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5548539857932123,\n \"acc_stderr\": 0.013967662954355487\n\ \ }\n}\n```" repo_url: https://huggingface.co/Corianas/Quokka_2.7b 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_07_19T15_58_12.174583 path: - '/details_harness\|arc:challenge\|25_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T15:58:12.174583.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_18T03_05_58.053951 path: - '/details_harness\|drop\|3_2023-09-18T03-05-58.053951.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-18T03-05-58.053951.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_18T03_05_58.053951 path: - '/details_harness\|gsm8k\|5_2023-09-18T03-05-58.053951.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-18T03-05-58.053951.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hellaswag\|10_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:58:12.174583.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T15:58:12.174583.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T15_58_12.174583 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T15:58:12.174583.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T15:58:12.174583.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_18T03_05_58.053951 path: - '/details_harness\|winogrande\|5_2023-09-18T03-05-58.053951.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-18T03-05-58.053951.parquet' - config_name: results data_files: - split: 2023_07_19T15_58_12.174583 path: - results_2023-07-19T15:58:12.174583.parquet - split: 2023_09_18T03_05_58.053951 path: - results_2023-09-18T03-05-58.053951.parquet - split: latest path: - results_2023-09-18T03-05-58.053951.parquet --- # Dataset Card for Evaluation run of Corianas/Quokka_2.7b ## Dataset Description - Homepage: - Repository: https://huggingface.co/Corianas/Quokka_2.7b - 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 [Corianas/Quokka_2.7b](https://huggingface.co/Corianas/Quokka_2.7b) 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_Corianas__Quokka_2.7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-18T03:05:58.053951](https://huggingface.co/datasets/open-llm-leaderboard/details_Corianas__Quokka_2.7b/blob/main/results_2023-09-18T03-05-58.053951.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": 0.027055369127516778, "em_stderr": 0.0016615386418947858, "f1": 0.0843078859060403, "f1_stderr": 0.0021162612701253174, "acc": 0.27932236818091244, "acc_stderr": 0.007830181847252834 }, "harness\|drop\|3": { "em": 0.027055369127516778, "em_stderr": 0.0016615386418947858, "f1": 0.0843078859060403, "f1_stderr": 0.0021162612701253174 }, "harness\|gsm8k\|5": { "acc": 0.0037907505686125853, "acc_stderr": 0.0016927007401501802 }, "harness\|winogrande\|5": { "acc": 0.5548539857932123, "acc_stderr": 0.013967662954355487 } } ``` ### 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]	[ -0.3810032606124878, -0.7499247789382935, 0.15036030113697052, 0.27496594190597534, -0.1979185938835144, 0.16877414286136627, -0.2767084240913391, -0.1859806627035141, 0.4929051697254181, 0.43201473355293274, -0.7739217877388, -0.9017496705055237, -0.6105329990386963, 0.12556101381778717, -0.17471855878829956, 1.0927537679672241, -0.22540299594402313, -0.1846495121717453, -0.03715801611542702, -0.3405648469924927, -0.48721417784690857, -0.417158842086792, -0.6419713497161865, 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open-llm-leaderboard/details_HWERI__pythia-1.4b-deduped-sharegpt	open-llm-leaderboard	2023-09-16T20:15:38Z	374	0	[ "region:us" ]	null	2023-08-18T18:41:15Z	--- pretty_name: Evaluation run of HWERI/pythia-1.4b-deduped-sharegpt dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [HWERI/pythia-1.4b-deduped-sharegpt](https://huggingface.co/HWERI/pythia-1.4b-deduped-sharegpt)\ \ 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_HWERI__pythia-1.4b-deduped-sharegpt\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-16T20:15:27.580598](https://huggingface.co/datasets/open-llm-leaderboard/details_HWERI__pythia-1.4b-deduped-sharegpt/blob/main/results_2023-09-16T20-15-27.580598.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\": 0.00033145814652192217,\n \"f1\": 0.04875104865771823,\n\ \ \"f1_stderr\": 0.0012458540332815637,\n \"acc\": 0.2804129195481258,\n\ \ \"acc_stderr\": 0.008239894933698364\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0010486577181208054,\n \"em_stderr\": 0.00033145814652192217,\n\ \ \"f1\": 0.04875104865771823,\n \"f1_stderr\": 0.0012458540332815637\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.008339651250947688,\n \ \ \"acc_stderr\": 0.002504942226860534\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5524861878453039,\n \"acc_stderr\": 0.013974847640536194\n\ \ }\n}\n```" repo_url: https://huggingface.co/HWERI/pythia-1.4b-deduped-sharegpt 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_17T18_24_42.073512 path: - '/details_harness\|arc:challenge\|25_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-17T18:24:42.073512.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_16T20_15_27.580598 path: - '/details_harness\|drop\|3_2023-09-16T20-15-27.580598.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-16T20-15-27.580598.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_16T20_15_27.580598 path: - '/details_harness\|gsm8k\|5_2023-09-16T20-15-27.580598.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-16T20-15-27.580598.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hellaswag\|10_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T18:24:42.073512.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T18:24:42.073512.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_17T18_24_42.073512 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T18:24:42.073512.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T18:24:42.073512.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_16T20_15_27.580598 path: - '/details_harness\|winogrande\|5_2023-09-16T20-15-27.580598.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-16T20-15-27.580598.parquet' - config_name: results data_files: - split: 2023_08_17T18_24_42.073512 path: - results_2023-08-17T18:24:42.073512.parquet - split: 2023_09_16T20_15_27.580598 path: - results_2023-09-16T20-15-27.580598.parquet - split: latest path: - results_2023-09-16T20-15-27.580598.parquet --- # Dataset Card for Evaluation run of HWERI/pythia-1.4b-deduped-sharegpt ## Dataset Description - Homepage: - Repository: https://huggingface.co/HWERI/pythia-1.4b-deduped-sharegpt - 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 [HWERI/pythia-1.4b-deduped-sharegpt](https://huggingface.co/HWERI/pythia-1.4b-deduped-sharegpt) 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_HWERI__pythia-1.4b-deduped-sharegpt", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-16T20:15:27.580598](https://huggingface.co/datasets/open-llm-leaderboard/details_HWERI__pythia-1.4b-deduped-sharegpt/blob/main/results_2023-09-16T20-15-27.580598.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": 0.00033145814652192217, "f1": 0.04875104865771823, "f1_stderr": 0.0012458540332815637, "acc": 0.2804129195481258, "acc_stderr": 0.008239894933698364 }, "harness\|drop\|3": { "em": 0.0010486577181208054, "em_stderr": 0.00033145814652192217, "f1": 0.04875104865771823, "f1_stderr": 0.0012458540332815637 }, "harness\|gsm8k\|5": { "acc": 0.008339651250947688, "acc_stderr": 0.002504942226860534 }, "harness\|winogrande\|5": { "acc": 0.5524861878453039, "acc_stderr": 0.013974847640536194 } } ``` ### 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]	[ -0.40444886684417725, -0.6502466201782227, 0.19511225819587708, 0.22765548527240753, -0.15435874462127686, 0.13445144891738892, -0.38292762637138367, -0.11864228546619415, 0.38744163513183594, 0.38518717885017395, -0.7049422860145569, -0.8611323833465576, -0.6998556852340698, 0.11321967095136642, -0.1221059262752533, 1.1204605102539062, -0.32003217935562134, -0.2983172833919525, 0.15967756509780884, -0.2586376368999481, -0.3167363405227661, -0.5220613479614258, -0.5113584399223328, 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hlgd	null	2023-01-25T14:32:19Z	373	2	[ "task_categories:text-classification", "annotations_creators:crowdsourced", "language_creators:expert-generated", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:apache-2.0", "headline-grouping", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - expert-generated language: - en license: - apache-2.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: [] pretty_name: Headline Grouping (HLGD) tags: - headline-grouping dataset_info: features: - name: timeline_id dtype: class_label: names: '0': 0 '1': 1 '2': 2 '3': 3 '4': 4 '5': 5 '6': 6 '7': 7 '8': 8 '9': 9 - name: headline_a dtype: string - name: headline_b dtype: string - name: date_a dtype: string - name: date_b dtype: string - name: url_a dtype: string - name: url_b dtype: string - name: label dtype: class_label: names: '0': same_event '1': different_event splits: - name: train num_bytes: 6447212 num_examples: 15492 - name: test num_bytes: 941145 num_examples: 2495 - name: validation num_bytes: 798302 num_examples: 2069 download_size: 1858948 dataset_size: 8186659 --- # Dataset Card for Headline Grouping (HLGD) ## 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://github.com/tingofurro/headline_grouping](https://github.com/tingofurro/headline_grouping) - Repository: [https://github.com/tingofurro/headline_grouping](https://github.com/tingofurro/headline_grouping) - Paper: [https://people.eecs.berkeley.edu/~phillab/pdfs/NAACL2021_HLG.pdf](https://people.eecs.berkeley.edu/~phillab/pdfs/NAACL2021_HLG.pdf) - Leaderboard: N/A - Point of Contact: phillab (at) berkeley (dot) edu ### Dataset Summary HLGD is a binary classification dataset consisting of 20,056 labeled news headlines pairs indicating whether the two headlines describe the same underlying world event or not. The dataset comes with an existing split between `train`, `validation` and `test` (60-20-20). ### Supported Tasks and Leaderboards The paper (NAACL2021) introducing HLGD proposes three challenges making use of various amounts of data: - Challenge 1: Headline-only. Models must make predictions using only the text of both headlines. - Challenge 2: Headline + Time. Models must make predictions using the headline and publication date of the two headlines. - Challenge 3: Headline + Time + Other. Models can make predictions using the headline, publication date as well as any other relevant meta-data that can be obtained through the URL attached to the headline (full article content, authors, news source, etc.) ### Languages Dataset is in english. ## Dataset Structure ### Data Instances A typical dataset consists of a timeline_id, two headlines (A/B), each associated with a URL, and a date. Finally, a label indicates whether the two headlines describe the same underlying event (1) or not (0). Below is an example from the training set: ``` {'timeline_id': 4, 'headline_a': 'France fines Google nearly $57 million for first major violation of new European privacy regime', 'headline_b': "France hits Google with record EUR50mn fine over 'forced consent' data collection", 'date_a': '2019-01-21', 'date_b': '2019-01-21', 'url_a': 'https://www.chicagotribune.com/business/ct-biz-france-fines-google-privacy-20190121-story.html', 'url_b': 'https://www.rt.com/news/449369-france-hits-google-with-record-fine/', 'label': 1} ``` ### Data Fields - `timeline_id`: Represents the id of the timeline that the headline pair belongs to (values 0 to 9). The dev set is composed of timelines 0 and 5, and the test set timelines 7 and 8 - `headline_a`, `headline_b`: Raw text for the headline pair being compared - `date_a`, `date_b`: Publication date of the respective headlines, in the `YYYY-MM-DD` format - `url_a`, `url_b`: Original URL of the respective headlines. Can be used to retrieve additional meta-data on the headline. - `label`: 1 if the two headlines are part of the the same headline group and describe the same underlying event, 0 otherwise. ### Data Splits \| \| Train \| Dev \| Test \| \| --------------------------- \| ------- \| ------ \| ----- \| \| Number of examples \| 15,492 \| 2,069 \| 2,495 \| ## Dataset Creation ### Curation Rationale The task of grouping headlines from diverse news sources discussing a same underlying event is important to enable interfaces that can present the diversity of coverage of unfolding news events. Many news aggregators (such as Google or Yahoo news) present several sources for a given event, with an objective to highlight coverage diversity. Automatic grouping of news headlines and articles remains challenging as headlines are short, heavily-stylized texts. The HeadLine Grouping Dataset introduces the first benchmark to evaluate NLU model's ability to group headlines according to the underlying event they describe. ### Source Data #### Initial Data Collection and Normalization The data was obtained by collecting 10 news timelines from the NewsLens project by selecting timelines diversified in topic each contained between 80 and 300 news articles. #### Who are the source language producers? The source language producers are journalists or members of the newsroom of 34 news organizations listed in the paper. ### Annotations #### Annotation process Each timeline was annotated for group IDs by 5 independent annotators. The 5 annotations were merged into a single annotation named the global groups. The global group IDs are then used to generate all pairs of headlines within timelines with binary labels: 1 if two headlines are part of the same global group, and 0 otherwise. A heuristic is used to remove negative examples to obtain a final dataset that has class imbalance of 1 positive example to 5 negative examples. #### Who are the annotators? Annotators were authors of the papers and 8 crowd-workers on the Upwork platform. The crowd-workers were native English speakers with experience either in proof-reading or data-entry. ### Personal and Sensitive Information Annotators identity has been anonymized. Due to the public nature of news headline, it is not expected that the headlines will contain personal sensitive information. ## Considerations for Using the Data ### Social Impact of Dataset The purpose of this dataset is to facilitate applications that present diverse news coverage. By simplifying the process of developing models that can group headlines that describe a common event, we hope the community can build applications that show news readers diverse sources covering similar events. We note however that the annotations were performed in majority by crowd-workers and that even though inter-annotator agreement was high, it was not perfect. Bias of the annotators therefore remains in the dataset. ### Discussion of Biases There are several sources of bias in the dataset: - Annotator bias: 10 annotators participated in the creation of the dataset. Their opinions and perspectives influenced the creation of the dataset. - Subject matter bias: HLGD consists of headlines from 10 news timelines from diverse topics (space, tech, politics, etc.). This choice has an impact on the types of positive and negative examples that appear in the dataset. - Source selection bias: 33 English-language news sources are represented in the dataset. This selection of news sources has an effect on the content in the timeline, and the overall dataset. - Time-range of the timelines: the timelines selected range from 2010 to 2020, which has an influence on the language and style of news headlines. ### Other Known Limitations For the task of Headline Grouping, inter-annotator agreement is high (0.814) but not perfect. Some decisions for headline grouping are subjective and depend on interpretation of the reader. ## Additional Information ### Dataset Curators The dataset was initially created by Philippe Laban, Lucas Bandarkar and Marti Hearst at UC Berkeley. ### Licensing Information The licensing status of the dataset depends on the legal status of news headlines. It is commonly held that News Headlines fall under "fair-use" ([American Bar blog post](https://www.americanbar.org/groups/gpsolo/publications/gp_solo/2011/september/fair_use_news_reviews/)) The dataset only distributes headlines, a URL and a publication date. Users of the dataset can then retrieve additional information (such as the body content, author, etc.) directly by querying the URL. ### Citation Information ``` @inproceedings{Laban2021NewsHG, title={News Headline Grouping as a Challenging NLU Task}, author={Laban, Philippe and Bandarkar, Lucas and Hearst, Marti A}, booktitle={NAACL 2021}, publisher = {Association for Computational Linguistics}, year={2021} } ``` ### Contributions Thanks to [@tingofurro](https://github.com/<tingofurro>) for adding this dataset.	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open-llm-leaderboard/details_Charlie911__vicuna-7b-v1.5-lora-mixed-datasets-time-unit	open-llm-leaderboard	2023-10-28T09:09:12Z	373	0	[ "region:us" ]	null	2023-10-08T16:13:43Z	--- pretty_name: Evaluation run of Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit](https://huggingface.co/Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit)\ \ 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_Charlie911__vicuna-7b-v1.5-lora-mixed-datasets-time-unit\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-28T09:09:00.701109](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__vicuna-7b-v1.5-lora-mixed-datasets-time-unit/blob/main/results_2023-10-28T09-09-00.701109.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\": 0.004928691275167785,\n\ \ \"em_stderr\": 0.0007171872517059817,\n \"f1\": 0.06610213926174507,\n\ \ \"f1_stderr\": 0.001553905671666344,\n \"acc\": 0.4026417372707673,\n\ \ \"acc_stderr\": 0.009752392640502771\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.004928691275167785,\n \"em_stderr\": 0.0007171872517059817,\n\ \ \"f1\": 0.06610213926174507,\n \"f1_stderr\": 0.001553905671666344\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0712661106899166,\n \ \ \"acc_stderr\": 0.007086462127954495\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.734017363851618,\n \"acc_stderr\": 0.012418323153051046\n\ \ }\n}\n```" repo_url: https://huggingface.co/Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit 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_08T16_13_20.175189 path: - '/details_harness\|arc:challenge\|25_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-08T16-13-20.175189.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_28T09_09_00.701109 path: - '/details_harness\|drop\|3_2023-10-28T09-09-00.701109.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-28T09-09-00.701109.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_28T09_09_00.701109 path: - '/details_harness\|gsm8k\|5_2023-10-28T09-09-00.701109.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-28T09-09-00.701109.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hellaswag\|10_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T16-13-20.175189.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T16-13-20.175189.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T16_13_20.175189 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T16-13-20.175189.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T16-13-20.175189.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_28T09_09_00.701109 path: - '/details_harness\|winogrande\|5_2023-10-28T09-09-00.701109.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-28T09-09-00.701109.parquet' - config_name: results data_files: - split: 2023_10_08T16_13_20.175189 path: - results_2023-10-08T16-13-20.175189.parquet - split: 2023_10_28T09_09_00.701109 path: - results_2023-10-28T09-09-00.701109.parquet - split: latest path: - results_2023-10-28T09-09-00.701109.parquet --- # Dataset Card for Evaluation run of Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit ## Dataset Description - Homepage: - Repository: https://huggingface.co/Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit - 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 [Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit](https://huggingface.co/Charlie911/vicuna-7b-v1.5-lora-mixed-datasets-time-unit) 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_Charlie911__vicuna-7b-v1.5-lora-mixed-datasets-time-unit", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-28T09:09:00.701109](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__vicuna-7b-v1.5-lora-mixed-datasets-time-unit/blob/main/results_2023-10-28T09-09-00.701109.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": 0.004928691275167785, "em_stderr": 0.0007171872517059817, "f1": 0.06610213926174507, "f1_stderr": 0.001553905671666344, "acc": 0.4026417372707673, "acc_stderr": 0.009752392640502771 }, "harness\|drop\|3": { "em": 0.004928691275167785, "em_stderr": 0.0007171872517059817, "f1": 0.06610213926174507, "f1_stderr": 0.001553905671666344 }, "harness\|gsm8k\|5": { "acc": 0.0712661106899166, "acc_stderr": 0.007086462127954495 }, "harness\|winogrande\|5": { "acc": 0.734017363851618, "acc_stderr": 0.012418323153051046 } } ``` ### 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]	[ -0.3957480192184448, -0.7562239766120911, 0.20134593546390533, 0.2884088158607483, -0.2504083216190338, 0.0966472327709198, -0.27764174342155457, -0.27330222725868225, 0.5337239503860474, 0.5798359513282776, -0.6476566195487976, -0.9043014645576477, -0.578728973865509, 0.11803161352872849, -0.24831105768680573, 1.0528945922851562, -0.2692107558250427, -0.1927875280380249, 0.2166956216096878, -0.34957969188690186, -0.38766205310821533, -0.4609528183937073, -0.5759902596473694, 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sam-mosaic/iv4-chatml-8k	sam-mosaic	2023-11-28T06:38:55Z	373	0	[ "region:us" ]	null	2023-11-28T06:37:50Z	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: source dtype: string - name: prompt dtype: string - name: response dtype: string splits: - name: train num_bytes: 2207667895.4360986 num_examples: 363958 - name: test num_bytes: 330419382.2206894 num_examples: 54042 download_size: 618017532 dataset_size: 2538087277.656788 --- # Dataset Card for "iv4-chatml-8k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.565336287021637, -0.01406765729188919, 0.10285741835832596, 0.33141806721687317, -0.1364903450012207, 0.06918376684188843, 0.24010097980499268, -0.269311785697937, 0.6610769629478455, 0.6111336946487427, -0.6458147168159485, -0.7539340853691101, -0.6325390338897705, 0.06244725361466408, 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LDJnr/Pure-Dove	LDJnr	2023-11-21T17:55:19Z	372	23	[ "task_categories:conversational", "task_categories:question-answering", "task_categories:text-generation", "size_categories:1K<n<10K", "language:en", "license:apache-2.0", "Physics", "Biology", "Math", "Chemistry", "Culture", "Logic", "Roleplay", "region:us" ]	[ "conversational", "question-answering", "text-generation" ]	2023-09-26T02:06:24Z	--- license: apache-2.0 task_categories: - conversational - question-answering - text-generation language: - en tags: - Physics - Biology - Math - Chemistry - Culture - Logic - Roleplay pretty_name: Pure-Dove size_categories: - 1K<n<10K --- ## This is the Official Pure-Dove dataset. Over 3K multi-turn examples, and many more coming soon! This dataset aims to be the largest highest quality cluster of real human back and forth conversations with GPT-4. Steps have even been done to ensure that only the best GPT-4 conversations in comparisons are kept, there are many instances where two GPT-4 responses are rated as equal to eachother or as both bad. We exclude all such responses from Pure Dove and make sure to only include ChatBot Arena responses that are voted as being better even against another instance of GPT-4. - Comprised of over 3000 highly filtered multi-turn conversations between GPT-4 and real humans. - Average context length per conversation is over 800 tokens. ## Purpose? - This dataset is not particularly intended to be trained on by itself, however, the size and quality of this dataset can work wonderfully as a supplemmentary addition to virtually any multi-turn compatible dataset. I encourage this use, all I ask is proper credits given for such! ## Quality filtering and cleaning. - The conversations were sourced from openly datasets such as ShareGPT and ChatBotArena by Lmsys, however, a large portion of these chats were riddled with hallucinations and abnormal distributions of different languages. - Extensive cleaning was done to filter out instances of overt AI moralizing or related behaviour, such as "As an AI language model" and "September 2021", not just in english, but other languages too! ## Credits During the curation process, there can be some relatively arduos steps when it comes to actually executing on the best experimentation or concepts for how to filter examples out. Luckily there is folks over at NousResearch that helped expedite this process with little to no sacrifices in quality, big credit to J-Supha within NousResearch specifically for making these types of significant contributions. ## Future Plans & How you can help! This is a relatively early build amongst the grand plans for the future of what I plan to work on! In the near future we plan on leveraging the help of domain specific expert volunteers to eliminate any mathematically/verifiably incorrect answers from training curations of different types of datasets. If you have at-least a bachelors in mathematics, physics, biology or chemistry and would like to volunteer even just 30 minutes of your expertise time, please contact LDJ on discord! Citation: ``` @article{daniele2023amplify-instruct, title={Amplify-Instruct: Synthetically Generated Diverse Multi-turn Conversations for Effecient LLM Training.}, author={Daniele, Luigi and Suphavadeeprasit}, journal={arXiv preprint arXiv:(comming soon)}, year={2023} } ```	[ -0.4659765064716339, -0.8260352611541748, 0.4255499541759491, 0.1719999611377716, -0.15100431442260742, 0.0354846827685833, -0.17246384918689728, -0.4451375901699066, 0.16208964586257935, 0.5178658366203308, -0.7029078602790833, -0.41688552498817444, -0.4708016812801361, 0.0717027559876442, -0.44378453493118286, 1.2975550889968872, 0.2924429774284363, 0.21969638764858246, -0.10127489268779755, -0.3267066180706024, -0.3454049229621887, -0.6841748952865601, -0.8443920612335205, -0.22185148298740387, 0.41148701310157776, 0.24388539791107178, 0.3992854356765747, 0.3660290241241455, 0.3728596568107605, 0.2617136240005493, 0.08703787624835968, 0.369594544172287, -0.8685938715934753, -0.020712407305836678, 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lmqg/qag_zhquad	lmqg	2023-11-07T19:15:25Z	372	0	[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10k<n<100K", "source_datasets:lmqg/qag_zhquad", "language:ja", "license:cc-by-sa-4.0", "question-generation", "arxiv:2210.03992", "region:us" ]	[ "text-generation" ]	2023-11-07T11:24:53Z	--- license: cc-by-sa-4.0 pretty_name: Chinese SQuAD for question generation language: ja multilinguality: monolingual size_categories: 10k<n<100K source_datasets: lmqg/qag_zhquad task_categories: - text-generation task_ids: - language-modeling tags: - question-generation --- # Dataset Card for "lmqg/qag_zhquad" ## Dataset Description - Repository: [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation) - Paper: [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992) - Point of Contact: [Asahi Ushio](http://asahiushio.com/) ### Dataset Summary This is the question & answer generation dataset based on the [Chinese SQuAD](https://github.com/junzeng-pluto/ChineseSquad). Please see the original repository ([https://github.com/junzeng-pluto/ChineseSquad](https://github.com/junzeng-pluto/ChineseSquad)) for more details. ### Supported Tasks and Leaderboards * `question-answer-generation`: The dataset is assumed to be used to train a model for question & answer generation. Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore (see our paper for more in detail). ### Languages Japanese (ja) ## Dataset Structure An example of 'train' looks as follows. ``` ``` The data fields are the same among all splits. - `questions`: a `list` of `string` features. - `answers`: a `list` of `string` features. - `paragraph`: a `string` feature. - `questions_answers`: a `string` feature. ## Data Splits \| train \| validation \| test \| \|--------:\|-----------:\|-----:\| \| 19097 \| 2475 \| 6664 \| ## Citation Information ``` @inproceedings{ushio-etal-2022-generative, title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration", author = "Ushio, Asahi and Alva-Manchego, Fernando and Camacho-Collados, Jose", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, U.A.E.", publisher = "Association for Computational Linguistics", } ```	[ -0.46871769428253174, -0.9793251752853394, 0.24544961750507355, -0.01665480062365532, -0.3054236173629761, -0.12361200898885727, -0.2434474229812622, -0.11910656839609146, 0.021806519478559494, 0.38868847489356995, -0.8060130476951599, -0.6634962558746338, -0.10307064652442932, 0.09954416006803513, -0.10964079201221466, 1.1880296468734741, -0.18552158772945404, 0.1357964724302292, -0.4720551073551178, -0.24085310101509094, -0.23248417675495148, -0.5846897959709167, -0.7009602189064026, -0.3542197644710541, 0.3383125364780426, 0.5206778049468994, 0.6088700294494629, 0.49374616146087646, 0.3182832896709442, 0.23668058216571808, -0.1078692227602005, 0.24955153465270996, -0.2720775604248047, 0.1291634887456894, 0.19826897978782654, -0.5650470852851868, -0.5149492621421814, -0.07838645577430725, 0.9025449752807617, 0.58714359998703, -0.20286200940608978, 0.4555791914463043, 0.09935299307107925, 0.44960376620292664, -0.27285319566726685, 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turkish_product_reviews	null	2023-01-25T14:54:42Z	371	3	[ "task_categories:text-classification", "task_ids:sentiment-classification", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:100K<n<1M", "source_datasets:original", "language:tr", "license:unknown", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - tr license: - unknown multilinguality: - monolingual size_categories: - 100K<n<1M source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification pretty_name: Turkish Product Reviews dataset_info: features: - name: sentence dtype: string - name: sentiment dtype: class_label: names: '0': negative '1': positive splits: - name: train num_bytes: 43369710 num_examples: 235165 download_size: 13184332 dataset_size: 43369710 --- # Dataset Card for Turkish Product Reviews ## 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 - Repository: [turkish-text-data](https://github.com/fthbrmnby/turkish-text-data) - Point of Contact: [Fatih Barmanbay](https://github.com/fthbrmnby) ### Dataset Summary This Turkish Product Reviews Dataset contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages The dataset is based on Turkish. ## Dataset Structure ### Data Instances Example 1: sentence: beklentimin altında bir ürün kaliteli değil sentiment: 0 (negative) Example 2: sentence: fiyat ve performans olarak gayet iyi sentiment: 1 (positive) ### Data Fields - sentence(string) : Contatins turkish product review - sentiment(int) : 0 (negative) or 1 (positive) ### Data Splits It is not divided into Train set and Test set. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations The dataset does not contain any additional 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 The dataset was created by [Fatih Barmanbay](https://github.com/fthbrmnby). ### Licensing Information The data is under the [CC-BY-SA-4.0 License](https://github.com/fthbrmnby/turkish-text-data/blob/master/LICENCE) ### Citation Information No citation available for this dataset. ### Contributions Thanks to [@basakbuluz](https://github.com/basakbuluz) for adding this dataset.	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yhavinga/mc4_nl_cleaned	yhavinga	2022-12-16T09:24:34Z	371	7	[ "task_categories:text-generation", "task_ids:language-modeling", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "multilinguality:en-nl", "source_datasets:extended", "language:nl", "language:en", "license:odc-by", "arxiv:1910.10683", "region:us" ]	[ "text-generation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - nl - en license: - odc-by multilinguality: - monolingual - en-nl size_categories: micro: - 120k tiny: - 1M<n<10M small: - 10M<n<100M medium: - 10M<n<100M large: - 10M<n<100M full: - 100M<n<1B source_datasets: - extended task_categories: - text-generation task_ids: - language-modeling paperswithcode_id: mc4 pretty_name: mC4_nl_cleaned --- # Dataset Card for Clean Dutch mC4 ## Table of Contents - [Dataset Card for Clean](#dataset-card-for-mc4) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Preprocessing](#preprocessing) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [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) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Original Homepage: [HF Hub](https://huggingface.co/datasets/allenai/c4) - Paper: [ArXiv](https://arxiv.org/abs/1910.10683) ### Dataset Summary A cleaned version (151GB) of the Dutch part (277GB) of the C4 multilingual dataset (mC4). While this dataset is monolingual, it is possible to download `en-nl` interleaved data, see the Dataset Config section below. Based on the [Common Crawl dataset](https://commoncrawl.org). The original version was prepared by [AllenAI](https://allenai.org/), hosted at the address [https://huggingface.co/datasets/allenai/c4](https://huggingface.co/datasets/allenai/c4). ### Preprocessing The Dutch portion of mC4 was cleaned in a similar fashion as the English cleaned C4 version. See [GitLab](https://gitlab.com/yhavinga/c4nlpreproc) for details. In summary, the preprocessing procedure includes: - Removing documents containing words from a selection of the [Dutch and English List of Dirty Naught Obscene and Otherwise Bad Words](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words). - Removing sentences containing: - Less than 3 words. - A word longer than 250 characters. - An end symbol not matching end-of-sentence punctuation. - Strings associated to javascript code (e.g. `{`), lorem ipsum, policy information in Dutch or English. - Removing documents (after sentence filtering): - Containing less than 5 sentences. - Containing less than 500 or more than 50'000 characters. - Not identified as prevalently Dutch by the `LangDetect` package. Using parallel processing with 96 CPU cores on a TPUv3 via Google Cloud to perform the complete clean of all the original Dutch shards of mC4 (1024 of ~220Mb train, 4 of ~24Mb validation) required roughly 10 hours due to the demanding steps of sentence tokenization and language detection. The total size of compressed `.json.gz` files is roughly halved after the procedure. ## Dataset Structure ### Data Instances An example from the dataset: ``` { 'timestamp': '2019-02-22T15:37:25Z', 'url': 'https://ondernemingen.bnpparibasfortis.be/nl/artikel?n=vijf-gouden-tips-voor-succesvol-zaken-doen-met-japan', 'text': 'Japanse bedrijven zijn niet alleen hondstrouw aan hun leveranciers , ze betalen ook nog eens erg stipt. Alleen is het niet zo makkelijk er een voet tussen de deur te krijgen. Met de volgende tips hebt u alvast een streepje voor.\nIn Japan draait alles om vertrouwen. Neem voldoende tijd om een relatie op te bouwen.Aarzel niet om tijdig een lokale vertrouwenspersoon in te schakelen.\nJapan is een erg competitieve markt.Kwaliteit en prijs zijn erg belangrijk, u zult dus het beste van uzelf moeten geven. Gelukkig is de beloning groot. Japanse zakenlui zijn loyaal en betalen stipt!\nJapanners houden er eigenzinnige eisen op na. Kom dus niet aanzetten met uw standaardproducten voor de Europese markt. Zo moet een producent van diepvriesfrieten bijvoorbeeld perfect identieke frietjes kunnen leveren in mini- verpakkingen. Het goede nieuws is dat Japanners voor kwaliteit graag diep in hun buidel tasten.\nEn u dacht dat Europa lijdt aan reglementitis? Japanners kennen er ook wat van. Tal van voorschriften zeggen wat je wel en niet mag doen. Gelukkig zijn de regels helder geformuleerd.\nHet gebruik van het Engels is niet echt ingeburgerd in Japan. Betrek een tolk bij uw onderhandelingen en zorg voor correcte vertalingen van handleidingen of softwareprogramma’s.' } ``` ### Data Fields The data contains the following fields: - `url`: url of the source as a string - `text`: text content as a string - `timestamp`: timestamp of extraction as a string ### Data Configs To build mC4, the original authors used [CLD3](https://github.com/google/cld3) to identify over 100 languages. For Dutch, the whole corpus of scraped text was divided in `1032` jsonl files, `1024` for training following the naming style `c4-nl-cleaned.tfrecord-0XXXX-of-01024.json.gz` and 4 for validation following the naming style `c4-nl-cleaned.tfrecord-0000X-of-00004.json.gz`. The full set of pre-processed files takes roughly 208GB of disk space to download with Git LFS. For ease of use under different storage capacities, the following incremental configs are available: (note: files on disk are compressed) \| config \| train size (docs, words, download + preproc disk space) \| validation size \| \|:-------\|--------------------------------------------------------:\|----------------:\| \| micro \| 125k docs, 23M words (<1GB) \| 16k docs \| \| tiny \| 6M docs, 2B words (6 GB + 15 GB) \| 16k docs \| \| small \| 15M docs, 6B words (14 GB + 36 GB) \| 16k docs \| \| medium \| 31M docs, 12B words (28 GB + 72 GB) \| 32k docs \| \| large \| 47M docs, 19B words (42 GB + 108 GB) \| 48k docs \| \| full \| 64M docs, 25B words (58 GB + 148 GB) \| 64k docs \| For each config above there also exists a config `<name>_en_nl` that interleaves `nl` and `en` examples from the cleaned `en` variant of C4. You can load any config like this: ```python from datasets import load_dataset datasets = load_dataset('yhavinga/mc4_nl_cleaned', 'tiny', streaming=True) print(datasets) ``` This will print ``` DatasetDict({ train: Dataset({ features: ['text', 'timestamp', 'url'], num_rows: 6303893 }) validation: Dataset({ features: ['text', 'timestamp', 'url'], num_rows: 16189 }) }) ``` Since the configs are quite large, you may want to traverse them using the streaming mode available starting from — Datasets v1.9.0: ```python from datasets import load_dataset mc4_nl_full_stream = load_dataset('yhavinga/mc4_nl_cleaned', "full", split='train', streaming=True) print(next(iter(mc4_nl_full_stream))) # Prints the example presented above ``` ## Dataset Creation Refer to the original paper for more considerations regarding the choice of sources and the scraping process for creating `mC4`. ## Considerations for Using the Data ### Social Impact of Dataset With more than 151GB (58GB compressed) of cleaned Dutch text and more than 23B estimated words, this is by far the largest available cleaned corpus for the Dutch language. The second largest dataset available is [OSCAR](https://oscar-corpus.com/), which is only 39GB in size for its deduplicated variant, and contains vulgarity. Using this corpus for training language models with adequate computational resources will allow researchers to reach parity with the performances observed for the English language. This can in turn have important repercussions for the development of commercial language technology applications for the Dutch language. ### Discussion of Biases Despite the cleaning procedure aimed at removing vulgarity and profanity, it must be considered that model trained on this scraped corpus will inevitably reflect biases present in blog articles and comments on the Internet. This makes the corpus especially interesting in the context of studying data biases and how to limit their impacts. ## Additional Information ### Licensing Information AllenAI are releasing this dataset under the terms of ODC-BY. By using this, you are also bound by the Common Crawl terms of use in respect of the content contained in the dataset. ### Citation Information ``` @article{2019t5, author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu}, title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer}, journal = {arXiv e-prints}, year = {2019}, archivePrefix = {arXiv}, eprint = {1910.10683}, } ``` ### Contributions Thanks to [[email protected]](mailto:[email protected]), [@dirkgr](https://github.com/dirkgr) and [@lhoestq](https://github.com/lhoestq) for providing the `cleaned_it_mc4` example that shows how upload a dataset to the Huggingface hub.	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llm-lens/descriptors-text-davinci-003	llm-lens	2023-06-29T02:39:27Z	371	0	[ "region:us" ]	null	2023-06-29T02:38:48Z	--- dataset_info: features: - name: vocab dtype: string - name: descriptions sequence: string - name: prompt_descriptions sequence: string splits: - name: birdsnap num_bytes: 322488 num_examples: 500 - name: caltech101 num_bytes: 56880 num_examples: 102 - name: cifar100 num_bytes: 54081 num_examples: 100 - name: coco num_bytes: 45186 num_examples: 80 - name: dtd num_bytes: 25204 num_examples: 47 - name: fgvc num_bytes: 74126 num_examples: 100 - name: food101 num_bytes: 58525 num_examples: 101 - name: full num_bytes: 3000578 num_examples: 4951 - name: imagenet21k num_bytes: 604897 num_examples: 998 - name: lvis num_bytes: 679195 num_examples: 1198 - name: oxfordflowers num_bytes: 58560 num_examples: 102 - name: oxfordpets num_bytes: 22322 num_examples: 37 - name: stanfordcars num_bytes: 157786 num_examples: 196 - name: sun397 num_bytes: 243017 num_examples: 362 - name: visualgenome num_bytes: 1092697 num_examples: 1913 download_size: 3257945 dataset_size: 6495542 --- # Dataset Card for "descriptors-text-davinci-003" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.5535128712654114, -0.2813825309276581, 0.44205570220947266, -0.005008627660572529, -0.28340432047843933, -0.12219417840242386, 0.2945317327976227, -0.16788412630558014, 0.7579323649406433, 0.36232033371925354, -0.7846376895904541, -0.7042503356933594, -0.8678887486457825, 0.031163271516561508, -0.5544702410697937, 1.2282705307006836, -0.005120988469570875, 0.0044446075335145, -0.13158372044563293, -0.09013272076845169, -0.14615246653556824, -0.5208819508552551, -0.6105707287788391, -0.14722885191440582, 1.061777114868164, 0.656152606010437, 0.4009048342704773, 0.8255969285964966, 1.0616610050201416, 0.14990709722042084, -0.1571393460035324, -0.20917123556137085, -0.19681166112422943, 0.09473872929811478, 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EleutherAI/asdiv	EleutherAI	2023-11-02T14:45:42Z	371	1	[ "license:cc-by-nc-4.0", "region:us" ]	null	2023-07-07T14:58:55Z	--- license: cc-by-nc-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, 0.7903715372085571, 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C-MTEB/BQ	C-MTEB	2023-07-28T13:52:50Z	371	0	[ "region:us" ]	null	2023-07-28T13:52:31Z	--- 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: sentence1 dtype: string - name: sentence2 dtype: string - name: score dtype: int32 splits: - name: train num_bytes: 8156338 num_examples: 100000 - name: validation num_bytes: 812244 num_examples: 10000 - name: test num_bytes: 815362 num_examples: 10000 download_size: 5588828 dataset_size: 9783944 --- # Dataset Card for "BQ" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.406152606010437, -0.16973614692687988, 0.16174684464931488, 0.20584601163864136, -0.23641818761825562, 0.14065194129943848, 0.42179691791534424, -0.08533798158168793, 0.6949484348297119, 0.5473307967185974, -0.8261774778366089, -0.7515595555305481, 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open-llm-leaderboard/details_chargoddard__duplicitous-slurpbeast-13b	open-llm-leaderboard	2023-10-26T12:10:51Z	371	0	[ "region:us" ]	null	2023-10-08T19:36:13Z	--- pretty_name: Evaluation run of chargoddard/duplicitous-slurpbeast-13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [chargoddard/duplicitous-slurpbeast-13b](https://huggingface.co/chargoddard/duplicitous-slurpbeast-13b)\ \ 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_chargoddard__duplicitous-slurpbeast-13b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-26T12:10:38.195509](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__duplicitous-slurpbeast-13b/blob/main/results_2023-10-26T12-10-38.195509.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\": 0.022651006711409395,\n\ \ \"em_stderr\": 0.0015237307803438113,\n \"f1\": 0.10978607382550301,\n\ \ \"f1_stderr\": 0.0022271926416287282,\n \"acc\": 0.41926868133939454,\n\ \ \"acc_stderr\": 0.009980675697209198\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.022651006711409395,\n \"em_stderr\": 0.0015237307803438113,\n\ \ \"f1\": 0.10978607382550301,\n \"f1_stderr\": 0.0022271926416287282\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08794541319181198,\n \ \ \"acc_stderr\": 0.007801162197487707\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7505919494869772,\n \"acc_stderr\": 0.012160189196930689\n\ \ }\n}\n```" repo_url: https://huggingface.co/chargoddard/duplicitous-slurpbeast-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_10_08T19_35_50.428127 path: - '/details_harness\|arc:challenge\|25_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-08T19-35-50.428127.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_26T12_10_38.195509 path: - '/details_harness\|drop\|3_2023-10-26T12-10-38.195509.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-26T12-10-38.195509.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_26T12_10_38.195509 path: - '/details_harness\|gsm8k\|5_2023-10-26T12-10-38.195509.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-26T12-10-38.195509.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hellaswag\|10_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T19-35-50.428127.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-08T19-35-50.428127.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T19_35_50.428127 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T19-35-50.428127.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-08T19-35-50.428127.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_26T12_10_38.195509 path: - '/details_harness\|winogrande\|5_2023-10-26T12-10-38.195509.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-26T12-10-38.195509.parquet' - config_name: results data_files: - split: 2023_10_08T19_35_50.428127 path: - results_2023-10-08T19-35-50.428127.parquet - split: 2023_10_26T12_10_38.195509 path: - results_2023-10-26T12-10-38.195509.parquet - split: latest path: - results_2023-10-26T12-10-38.195509.parquet --- # Dataset Card for Evaluation run of chargoddard/duplicitous-slurpbeast-13b ## Dataset Description - Homepage: - Repository: https://huggingface.co/chargoddard/duplicitous-slurpbeast-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 [chargoddard/duplicitous-slurpbeast-13b](https://huggingface.co/chargoddard/duplicitous-slurpbeast-13b) 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_chargoddard__duplicitous-slurpbeast-13b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-26T12:10:38.195509](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__duplicitous-slurpbeast-13b/blob/main/results_2023-10-26T12-10-38.195509.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": 0.022651006711409395, "em_stderr": 0.0015237307803438113, "f1": 0.10978607382550301, "f1_stderr": 0.0022271926416287282, "acc": 0.41926868133939454, "acc_stderr": 0.009980675697209198 }, "harness\|drop\|3": { "em": 0.022651006711409395, "em_stderr": 0.0015237307803438113, "f1": 0.10978607382550301, "f1_stderr": 0.0022271926416287282 }, "harness\|gsm8k\|5": { "acc": 0.08794541319181198, "acc_stderr": 0.007801162197487707 }, "harness\|winogrande\|5": { "acc": 0.7505919494869772, "acc_stderr": 0.012160189196930689 } } ``` ### 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]	[ -0.37806373834609985, -0.6652194261550903, 0.19548483192920685, 0.2088957577943802, -0.16138093173503876, 0.1811557114124298, -0.30451998114585876, -0.17023047804832458, 0.47732454538345337, 0.6406633853912354, -0.6847859621047974, -0.9319913983345032, -0.7131909728050232, 0.11622346192598343, -0.2097594290971756, 1.224655270576477, -0.22362414002418518, -0.1677425503730774, 0.060170724987983704, -0.2798030376434326, -0.39509937167167664, -0.42362189292907715, -0.5290876030921936, 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mteb/medrxiv-clustering-p2p	mteb	2022-09-27T19:10:43Z	370	0	[ "language:en", "region:us" ]	null	2022-05-11T06:56:44Z	--- language: - en ---	[ -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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AIML-TUDA/i2p	AIML-TUDA	2023-05-25T08:04:07Z	370	5	[ "license:mit", "arxiv:2211.05105", "region:us" ]	null	2022-10-19T12:41:55Z	--- license: mit --- # Inaproppriate Image Prompts (I2P) The I2P benchmark contains real user prompts for generative text2image prompts that are unproportionately likely to produce <i>inappropriate</i> images. I2P was introduced in the 2023 CVPR paper [Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models](https://arxiv.org/abs/2211.05105). This benchmark is not specific to any approach or model, but was designed to evaluate mitigating measures against <i>inappropriate</i> degeneration in Stable Diffusion. The corresponding repository to evaluate text-to-image diffusion models on I2P can be found at https://github.com/ml-research/i2p. ## Definition of <i>inappropriate</i> content What is considered inappropriate imagery may differ based on context, setting, cultural and social predisposition as well as individual factors and is overall highly subjective. In this work we base our definition of inappropriate content on the work of Gebru <i> et al.</i>: > [data that] if viewed directly, might be offensive, insulting, threatening, or might otherwise cause anxiety. > > --<cite>Gebru, Timnit, et al. "Datasheets for datasets," (2021)</cite> which is for example also reflected by the OpenAI content policy [OpenAI content policy](https://labs.openai.com/policies/content-policy) that also applies to the use of DALL-E. Specifically, we consider images from the following categories: hate, harassment, violence, self-harm, sexual content, shocking images, illegal activity. Note that inappropriateness is not limited to these concepts, varies between cultures, and constantly evolves. Here we restricted ourselves on images displaying tangible acts of <I>inappropriate</i> behavior. Consequently, our test bed may contain prompts describing e.g.~geopolitical events or hateful symbols. ## Data Collection For the 7 concepts mentioned above we used 26 keywords and phrases describing them in more detail and collected up to 250 real world text prompts for each. For a given keyword we collected the prompts of the top 250 images returned by [lexica.art](https://www.lexica.art). Lexica is a collection of real-world, user generated images base on the official stable diffusion discord and collects the prompt, seed, guidance scale and image dimensions used in generation. Image retrieval in lexica is based on the similarity of an image and search query in CLIP embedding space. Therefore, the collected prompts have generated images that are close to an <i>inappropriate</i> concept in CLIP space. Please note that we identify duplicate prompts based on their unique identifier on lexica. Accordingly, the I2P benchmark may contain entries with the same text prompt but different seeds and generation parameters. ## Estimation of generated, <i>inappropriate</i> content We provide an estimation of the percentage of <i>inappropriate</i> content based on images generated using [Stable Diffusion v1.4](https://huggingface.co/CompVis/stable-diffusion-v1-4). For each prompt we generated 10 images using the seed and guidance scale specified in lexica while keeping the maximum image size to 512x512. Our estimate is based on the portion out of these 10 images that are classified as <i>inappropriate</i> by either the [Q16 classifier](https://github.com/ml-research/Q16) or [NudeNet Detector](https://github.com/notAI-tech/NudeNet). ## Dataset Format The benchmark consists of the following fields: \| Field \| Explanation \| \| ----------- \| ----------- \| \| prompt \| The text prompt used as input to the model (Please not that this may contain Unicode characters) \| \| categories \| One or multiple of the 7 categories mentioned above that yield this prompt. \| \| hard \| Indicates if this is a hard prompt to remove <i>inappropriate</i> content from. Prompts are labled as hard if at least half of their generated images are <i>inappropriate</i> \| \| inappropriate_percentage \| Percentage of <i>inappropriate</i> images as classified by Q16 and NudeNet out of 10 generated images using Stable Diffusion \| \| nudity_percentage \| Percentage of images as depicting explicit nudity as per the NudeNet out of 10 generated images using Stable Diffusion \| \| q16_percentage \| Percentage of <i>inappropriate</i> images as classified by Q16 out of 10 generated images using Stable Diffusion \| \| sd_safety_percentage \| Percentage of <i>inappropriate</i> images as classified by the SD NSWF safety checker out of 10 generated images using Stable Diffusion \| \| prompt_toxicity \| The toxicity score of the text prompt according to the [PerspectiveAPI](https://github.com/conversationai/perspectiveapi) \| \| lexica_url \| URL to the original prompt and the respective images in lexica for reference \| \| sd_seed \| Stable diffusion seed used in our image generation \| \| sd_guidance_scale \| Stable diffusion guidance scale used in our image generation \| \| sd_image_width \| Stable diffusion image width used in our image generation \| \| sd_image_height \| Stable diffusion image height used in our image generation \|	[ -0.5130426287651062, -0.7691758871078491, 0.3858644664287567, 0.42441317439079285, -0.37469321489334106, -0.5061724781990051, 0.27711403369903564, -0.4067153334617615, -0.15375633537769318, 0.20748792588710785, -0.5814074277877808, -0.5217206478118896, -0.6079685688018799, 0.3110073506832123, -0.3705069422721863, 0.8927870392799377, 0.10470087826251984, -0.04913980886340141, -0.2942350208759308, -0.22845859825611115, -0.7251838445663452, -0.05906759947538376, -0.9309791922569275, 0.13145717978477478, 0.576715886592865, 0.3486440181732178, 0.4476427733898163, 0.4768001139163971, 0.2615799903869629, 0.2596593201160431, -0.1777060478925705, 0.03718045353889465, -0.47285372018814087, 0.23551324009895325, 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open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE5_4w-r4-gate_up_down	open-llm-leaderboard	2023-10-26T15:53:22Z	370	0	[ "region:us" ]	null	2023-10-10T11:38:47Z	--- pretty_name: Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down)\ \ 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_CHIH-HUNG__llama-2-13b-FINETUNE5_4w-r4-gate_up_down\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-26T15:53:08.381645](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE5_4w-r4-gate_up_down/blob/main/results_2023-10-26T15-53-08.381645.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\": 0.2154991610738255,\n\ \ \"em_stderr\": 0.004210747014430766,\n \"f1\": 0.25919148489932897,\n\ \ \"f1_stderr\": 0.004195696877017449,\n \"acc\": 0.4490387889225113,\n\ \ \"acc_stderr\": 0.01073317504472215\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.2154991610738255,\n \"em_stderr\": 0.004210747014430766,\n\ \ \"f1\": 0.25919148489932897,\n \"f1_stderr\": 0.004195696877017449\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.1372251705837756,\n \ \ \"acc_stderr\": 0.009477808244600398\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.760852407261247,\n \"acc_stderr\": 0.011988541844843905\n\ \ }\n}\n```" repo_url: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down 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_10T11_38_23.134636 path: - '/details_harness\|arc:challenge\|25_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-10T11-38-23.134636.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_26T15_53_08.381645 path: - '/details_harness\|drop\|3_2023-10-26T15-53-08.381645.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-26T15-53-08.381645.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_26T15_53_08.381645 path: - '/details_harness\|gsm8k\|5_2023-10-26T15-53-08.381645.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-26T15-53-08.381645.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hellaswag\|10_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T11-38-23.134636.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T11-38-23.134636.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_10T11_38_23.134636 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T11-38-23.134636.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T11-38-23.134636.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_26T15_53_08.381645 path: - '/details_harness\|winogrande\|5_2023-10-26T15-53-08.381645.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-26T15-53-08.381645.parquet' - config_name: results data_files: - split: 2023_10_10T11_38_23.134636 path: - results_2023-10-10T11-38-23.134636.parquet - split: 2023_10_26T15_53_08.381645 path: - results_2023-10-26T15-53-08.381645.parquet - split: latest path: - results_2023-10-26T15-53-08.381645.parquet --- # Dataset Card for Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down ## Dataset Description - Homepage: - Repository: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down - 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-FINETUNE5_4w-r4-gate_up_down](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE5_4w-r4-gate_up_down) 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_CHIH-HUNG__llama-2-13b-FINETUNE5_4w-r4-gate_up_down", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-26T15:53:08.381645](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE5_4w-r4-gate_up_down/blob/main/results_2023-10-26T15-53-08.381645.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": 0.2154991610738255, "em_stderr": 0.004210747014430766, "f1": 0.25919148489932897, "f1_stderr": 0.004195696877017449, "acc": 0.4490387889225113, "acc_stderr": 0.01073317504472215 }, "harness\|drop\|3": { "em": 0.2154991610738255, "em_stderr": 0.004210747014430766, "f1": 0.25919148489932897, "f1_stderr": 0.004195696877017449 }, "harness\|gsm8k\|5": { "acc": 0.1372251705837756, "acc_stderr": 0.009477808244600398 }, "harness\|winogrande\|5": { "acc": 0.760852407261247, "acc_stderr": 0.011988541844843905 } } ``` ### 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]	[ -0.38648301362991333, -0.7324141263961792, 0.24876581132411957, 0.2616077959537506, -0.18907473981380463, 0.16376176476478577, -0.34530502557754517, -0.2759898006916046, 0.4473915696144104, 0.5353860259056091, -0.728070080280304, -0.9262571930885315, -0.7374188303947449, 0.25340062379837036, -0.2156805694103241, 1.188907265663147, -0.28047889471054077, -0.22257903218269348, 0.11069343984127045, -0.2330712378025055, -0.44391828775405884, -0.3737178444862366, -0.4380019009113312, 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mia-project/child_handpicked_sentences	mia-project	2023-11-14T05:17:36Z	370	0	[ "license:unknown", "region:us" ]	null	2023-11-14T00:20:46Z	--- license: unknown dataset_info: features: - name: audio_quality dtype: string - name: age dtype: int64 - name: sentence_transcription dtype: string - name: audio dtype: audio - name: sentence_number dtype: string - name: language_collection dtype: string - name: kid_name dtype: string - name: url_origin dtype: string splits: - name: train num_bytes: 2583290.0 num_examples: 189 download_size: 2447605 dataset_size: 2583290.0 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, 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ar_res_reviews	null	2023-01-25T14:26:30Z	369	5	[ "task_categories:text-classification", "task_ids:sentiment-classification", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:ar", "license:unknown", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - ar license: - unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification pretty_name: ArRestReviews dataset_info: features: - name: polarity dtype: class_label: names: '0': negative '1': positive - name: text dtype: string - name: restaurant_id dtype: string - name: user_id dtype: string splits: - name: train num_bytes: 3617097 num_examples: 8364 download_size: 3503230 dataset_size: 3617097 --- # Dataset Card for ArRestReviews ## 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: [Large Arabic Sentiment Analysis Resources](https://github.com/hadyelsahar/large-arabic-sentiment-analysis-resouces) - Repository: [Large Arabic Sentiment Analysis Resources](https://github.com/hadyelsahar/large-arabic-sentiment-analysis-resouces) - Paper: [ Building Large Arabic Multi-domain Resources for Sentiment Analysis](https://github.com/hadyelsahar/large-arabic-sentiment-analysis-resouces/blob/master/Paper%20-%20Building%20Large%20Arabic%20Multi-domain%20Resources%20for%20Sentiment%20Analysis.pdf) - Point of Contact: [hady elsahar]([email protected]) ### Dataset Summary Dataset of 8364 restaurant reviews from qaym.com in Arabic for sentiment analysis ### Supported Tasks and Leaderboards [More Information Needed] ### Languages The dataset is based on Arabic. ## Dataset Structure ### Data Instances A typical data point comprises of the following: - "polarity": which is a string value of either 0 or 1 indicating the sentiment around the review - "text": is the review plain text of a restaurant in Arabic - "restaurant_id": the restaurant ID on the website - "user_id": the user ID on the website example: ``` { 'polarity': 0, # negative 'restaurant_id': '1412', 'text': 'عادي جدا مامن زود', 'user_id': '21294' } ``` ### Data Fields - "polarity": is a string value of either 0 or 1 indicating the sentiment around the review - "text": is the review plain text of a restaurant in Arabic - "restaurant_id": the restaurant ID on the website (string) - "user_id": the user ID on the website (string) ### Data Splits The dataset is not split. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization Contains 8364 restaurant reviews from qaym.com #### Who are the source language producers? From tweeter. ### Annotations The polarity field provides a label of 1 or -1 pertaining to the sentiment of the review #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Discussion of Social Impact and Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information @InProceedings{10.1007/978-3-319-18117-2_2, author="ElSahar, Hady and El-Beltagy, Samhaa R.", editor="Gelbukh, Alexander", title="Building Large Arabic Multi-domain Resources for Sentiment Analysis", booktitle="Computational Linguistics and Intelligent Text Processing", year="2015", publisher="Springer International Publishing", address="Cham", pages="23--34", isbn="978-3-319-18117-2" } ### Contributions Thanks to [@abdulelahsm](https://github.com/abdulelahsm) for adding this dataset.	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lmqg/qg_jaquad	lmqg	2022-12-02T18:51:27Z	369	4	[ "task_categories:text-generation", "task_ids:language-modeling", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:SkelterLabsInc/JaQuAD", "language:ja", "license:cc-by-sa-3.0", "question-generation", "arxiv:2210.03992", "region:us" ]	[ "text-generation" ]	2022-03-02T23:29:22Z	--- license: cc-by-sa-3.0 pretty_name: JaQuAD for question generation language: ja multilinguality: monolingual size_categories: 10K<n<100K source_datasets: SkelterLabsInc/JaQuAD task_categories: - text-generation task_ids: - language-modeling tags: - question-generation --- # Dataset Card for "lmqg/qg_jaquad" ## Dataset Description - Repository: [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation) - Paper: [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992) - Point of Contact: [Asahi Ushio](http://asahiushio.com/) ### Dataset Summary This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](https://arxiv.org/abs/2210.03992). This is [JaQuAD](https://github.com/SkelterLabsInc/JaQuAD) dataset compiled for question generation (QG) task. The test set of the original data is not publicly released, so we randomly sampled test questions from the training set. There are no overlap in terms of the paragraph across train, test, and validation split. ### Supported Tasks and Leaderboards * `question-generation`: The dataset is assumed to be used to train a model for question generation. Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore (see our paper for more in detail). ### Languages Japanese (ja) ## Dataset Structure An example of 'train' looks as follows. ``` { "question": "新型車両として6000系が構想されたのは、製造費用のほか、どんな費用を抑えるためだったの?", "paragraph": "三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現都営地下鉄新宿線、以下新宿線と表記する)乗入構想により、京王線の利用客増加が見込まれ、相当数の車両を準備する必要に迫られるなか、製造費用、保守費用を抑えた新型車両として6000系が構想された。新宿線建設に際してはすでに1号線(後の浅草線)を1,435mm軌間で開業させていた東京都は京成電鉄と1号線との乗り入れにあたり京成電鉄の路線を1,372mmから1,435mmに改軌させた事例や、1,372mm軌間の特殊性から運輸省(当時、2001年から国土交通省)と共に京王にも改軌を求めたが、改軌工事中の輸送力確保が困難なことを理由に改軌しないことで決着している。", "answer": "保守費用", "sentence": "三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現都営地下鉄新宿線、以下新宿線と表記する)乗入構想により、京王線の利用客増加が見込まれ、相当数の車両を準備する必要に迫られるなか、製造費用、保守費用を抑えた新型車両として6000系が構想された。", "paragraph_sentence": "<hl>三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現都営地下鉄新宿線、以下新宿線と表記する)乗入構想により、京王線の利用客増加が見込まれ、相当数の車両を準備する必要に迫られるなか、製造費用、保守費用を抑えた新型車両として6000系が構想された。<hl>新宿線建設に際してはすでに1号線(後の浅草線)を1,435mm軌間で開業させていた東京都は京成電鉄と1号線との乗り入れにあたり京成電鉄の路線を1,372mmから1,435mmに改軌させた事例や、1,372mm軌間の特殊性から運輸省(当時、2001年から国土交通省)と共に京王にも改軌を求めたが、改軌工事中の輸送力確保が困難なことを理由に改軌しないことで決着している。", "paragraph_answer": "三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現都営地下鉄新宿線、以下新宿線と表記する)乗入構想により、京王線の利用客増加が見込まれ、相当数の車両を準備する必要に迫られるなか、製造費用、<hl>保守費用<hl>を抑えた新型車両として6000系が構想された。新宿線建設に際してはすでに1号線(後の浅草線)を1,435mm軌間で開業させていた東京都は京成電鉄と1号線との乗り入れにあたり京成電鉄の路線を1,372mmから1,435mmに改軌させた事例や、1,372mm軌間の特殊性から運輸省(当時、2001年から国土交通省)と共に京王にも改軌を求めたが、改軌工事中の輸送力確保が困難なことを理由に改軌しないことで決着している。", "sentence_answer": "三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現都営地下鉄新宿線、以下新宿線と表記する)乗入構想により、京王線の利用客増加が見込まれ、相当数の車両を準備する必要に迫られるなか、製造費用、<hl>保守費用<hl>を抑えた新型車両として6000系が構想された。" } ``` The data fields are the same among all splits. - `question`: a `string` feature. - `paragraph`: a `string` feature. - `answer`: a `string` feature. - `sentence`: a `string` feature. - `paragraph_answer`: a `string` feature, which is same as the paragraph but the answer is highlighted by a special token `<hl>`. - `paragraph_sentence`: a `string` feature, which is same as the paragraph but a sentence containing the answer is highlighted by a special token `<hl>`. - `sentence_answer`: a `string` feature, which is same as the sentence but the answer is highlighted by a special token `<hl>`. Each of `paragraph_answer`, `paragraph_sentence`, and `sentence_answer` feature is assumed to be used to train a question generation model, but with different information. The `paragraph_answer` and `sentence_answer` features are for answer-aware question generation and `paragraph_sentence` feature is for sentence-aware question generation. ## Data Splits \|train\|validation\|test \| \|----:\|---------:\|----:\| \|27809\| 3939\| 3939\| ## Citation Information ``` @inproceedings{ushio-etal-2022-generative, title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration", author = "Ushio, Asahi and Alva-Manchego, Fernando and Camacho-Collados, Jose", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, U.A.E.", publisher = "Association for Computational Linguistics", } ```	[ -0.8911774158477783, -0.8899005651473999, 0.6107444763183594, 0.34420332312583923, -0.44214946031570435, -0.34140998125076294, -0.06650769710540771, -0.1790781021118164, 0.13064979016780853, 0.5682042837142944, -0.7130501866340637, -0.6366428136825562, 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thu-coai/esconv	thu-coai	2023-07-15T08:26:36Z	369	0	[ "language:en", "license:cc-by-nc-4.0", "arxiv:2106.01144", "region:us" ]	null	2023-05-08T09:18:06Z	--- license: cc-by-nc-4.0 language: - en --- The ESConv dataset. [GitHub repo](https://github.com/thu-coai/Emotional-Support-Conversation). [Original paper](https://arxiv.org/abs/2106.01144). ```bib @inproceedings{liu-etal-2021-towards, title={Towards Emotional Support Dialog Systems}, author={Liu, Siyang and Zheng, Chujie and Demasi, Orianna and Sabour, Sahand and Li, Yu and Yu, Zhou and Jiang, Yong and Huang, Minlie}, booktitle={ACL}, year={2021} } ```	[ -0.30468887090682983, -0.5407780408859253, 0.32051581144332886, 0.19853603839874268, 0.08693496137857437, -0.217624694108963, -0.1896647959947586, -0.5244183540344238, 0.6007713675498962, 0.4270268380641937, -1.0089635848999023, -0.5131627321243286, -0.3175285756587982, 0.25550413131713867, -0.10029967129230499, 1.2700470685958862, 0.31240397691726685, 0.26870235800743103, -0.34945207834243774, -0.34493792057037354, -0.11988212913274765, -0.2923755645751953, -0.6066709756851196, -0.16001760959625244, 0.39815884828567505, 0.7688542604446411, 0.09482445567846298, 0.24758195877075195, 0.2734859585762024, 0.18588878214359283, -0.21809181571006775, 0.03469238802790642, 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jphme/ger_micro_benchmark	jphme	2023-09-18T21:15:10Z	369	1	[ "region:us" ]	null	2023-09-18T20:55:08Z	--- configs: - config_name: default data_files: - split: eval path: data/eval-* dataset_info: features: - name: input dtype: string - name: output dtype: string - name: subject dtype: string splits: - name: eval num_bytes: 69430 num_examples: 200 download_size: 39957 dataset_size: 69430 --- # Dataset Card for "ger_micro_benchmark" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.9021761417388916, -0.3807407021522522, 0.24111269414424896, -0.07469798624515533, -0.1237550675868988, -0.12048477679491043, 0.2542354464530945, -0.09194784611463547, 0.6537338495254517, 0.14711421728134155, -0.7215719223022461, -0.7299205660820007, -0.43071991205215454, -0.4174720346927643, -0.19469469785690308, 1.2542181015014648, 0.09283825010061264, 0.15162688493728638, -0.5637366771697998, -0.3804864287376404, 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0x7194633/gamio-ai-authorLM-dataset	0x7194633	2023-11-24T11:48:55Z	369	0	[ "region:us" ]	null	2023-11-24T11:48:49Z	--- dataset_info: features: - name: texts dtype: string splits: - name: train num_bytes: 6551786 num_examples: 288 download_size: 2843488 dataset_size: 6551786 --- # Dataset Card for "gamio-ai-authorLM-dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.43788033723831177, -0.30284518003463745, 0.2913345396518707, 0.16642454266548157, -0.1500573456287384, 0.04419109970331192, 0.31027042865753174, -0.23978294432163239, 0.7972939610481262, 0.5276944041252136, -0.7331423759460449, -0.6203585267066956, -0.6246473789215088, -0.17390619218349457, -0.18716824054718018, 1.4458833932876587, 0.19364099204540253, 0.08149811625480652, -0.7528338432312012, -0.2511856257915497, -0.41727975010871887, -0.6608497500419617, -0.747330904006958, -0.6112837791442871, 0.8196036219596863, 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CAiRE/ASCEND	CAiRE	2022-10-24T12:43:58Z	368	10	[ "task_categories:automatic-speech-recognition", "annotations_creators:expert-generated", "language_creators:crowdsourced", "multilinguality:multilingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "language:zh", "license:cc-by-sa-4.0", "speech-recognition", "code-switching", "arxiv:2112.06223", "region:us" ]	[ "automatic-speech-recognition" ]	2022-03-02T23:29:22Z	--- annotations_creators: - expert-generated language_creators: - crowdsourced language: - en - zh license: - cc-by-sa-4.0 multilinguality: - multilingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - automatic-speech-recognition task_ids: [] pretty_name: 'ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation' tags: - speech-recognition - code-switching --- # Dataset Card for ASCEND ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Usage](#usage) - [Dataset Structure](#dataset-structure) - [Data Splits](#data-instances) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - Homepage: [Needs More Information] - Repository: [Needs More Information] - Paper: https://arxiv.org/abs/2112.06223 - Leaderboard: [Needs More Information] - Point of Contact: [Needs More Information] ### Dataset Summary ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set. ### Supported Tasks and Leaderboards Code-switching ### Languages Chinese and English ## Usage To obtain the full dataset (complete with train, validation, and test set), simply run this: ``` import datasets dataset = datasets.load_dataset("CAiRE/ASCEND") ``` ## Dataset Structure A typical data point comprises the path to the audio file, the loaded audio array, and its transcription. Additional fields include datapoint id, duration, language, speaker id, session id, and topic. ``` { 'id': '00644', 'path': '.cache/huggingface/datasets/downloads/extracted/f0b33b5266cd9452ee310eef3577cf7adb7f29aa54dbff74b9a8ee406a55d614/waves/ses2_spk3_L13101_189.900_5.490.wav', 'audio': { 'path': '.cache/huggingface/datasets/downloads/extracted/f0b33b5266cd9452ee310eef3577cf7adb7f29aa54dbff74b9a8ee406a55d614/waves/ses2_spk3_L13101_189.900_5.490.wav', 'array': array([-6.1035156e-05, -1.8310547e-04, 3.0517578e-05, ..., 0.0000000e+00, -3.0517578e-05, 0.0000000e+00 ], dtype = float32), 'sampling_rate': 16000 }, 'transcription': '因为你不可能邀你的female friends去说走我们去play basketball', 'duration': 5.489999771118164, 'language': 'mixed', 'original_speaker_id': 3, 'session_id': 2, 'topic': 'sports' } ``` ### Data Splits Number of utterances: 9,869 train, 1,130 validation, and 1,315 test. ## Additional Information For comprehensive explanations, please check [our paper](https://arxiv.org/pdf/2112.06223.pdf). ### Licensing Information Creative Common Attribution Share-Alike 4.0 International (CC-BY-SA 4.0) ### Citation Information If you use our dataset, please cite us: ``` @inproceedings{lovenia2022ascend, title={ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation}, author={Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others}, booktitle={Proceedings of the 13th Language Resources and Evaluation Conference (LREC)}, year={2022} ```	[ -0.11227650940418243, -0.5307848453521729, -0.12936651706695557, 0.7168128490447998, -0.19355523586273193, 0.11788985878229141, -0.5058417916297913, -0.41847026348114014, 0.3977300226688385, 0.27295535802841187, -0.8055211901664734, -0.7272219061851501, -0.4613759219646454, -0.05917442589998245, -0.40938782691955566, 0.8988656997680664, 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chenz16/curriculum_benchmark	chenz16	2022-07-11T01:51:34Z	368	0	[ "license:mit", "region:us" ]	null	2022-07-11T01:50:55Z	--- 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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izumi-lab/wikipedia-ja-20230720	izumi-lab	2023-07-29T03:05:36Z	368	2	[ "language:ja", "license:cc-by-sa-3.0", "region:us" ]	null	2023-07-28T02:11:33Z	--- dataset_info: features: - name: curid dtype: string - name: title dtype: string - name: text dtype: string splits: - name: train num_bytes: 3653518687 num_examples: 1362415 download_size: 2130533065 dataset_size: 3653518687 license: cc-by-sa-3.0 language: - ja --- # Dataset Card for "wikipedia-ja-20230720" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.9370321035385132, -0.24046087265014648, 0.24610716104507446, 0.15865419805049896, -0.204843670129776, -0.27423861622810364, 0.14281326532363892, -0.23087452352046967, 0.9997025728225708, 0.44935160875320435, -0.925218939781189, -0.6331663727760315, -0.47435441613197327, -0.05469713360071182, -0.3638753890991211, 1.4187666177749634, 0.09340814501047134, 0.13940900564193726, -0.5022730231285095, 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hindi_discourse	null	2023-01-25T14:32:13Z	367	1	[ "task_categories:text-classification", "task_ids:multi-label-classification", "annotations_creators:other", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:hi", "license:other", "discourse-analysis", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - other language_creators: - found language: - hi license: - other multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - multi-label-classification pretty_name: Discourse Analysis dataset tags: - discourse-analysis dataset_info: features: - name: Story_no dtype: int32 - name: Sentence dtype: string - name: Discourse Mode dtype: class_label: names: '0': Argumentative '1': Descriptive '2': Dialogue '3': Informative '4': Narrative '5': Other splits: - name: train num_bytes: 1998930 num_examples: 9968 download_size: 4176677 dataset_size: 1998930 --- # Dataset Card for Discourse Analysis dataset ## 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: https://github.com/midas-research/hindi-discourse - Paper: [An Annotated Dataset of Discourse Modes in Hindi Stories](https://aclanthology.org/2020.lrec-1.149/) - Point of Contact: https://github.com/midas-research/MeTooMA ### Dataset Summary - The Hindi Discourse Analysis dataset is a corpus for analyzing discourse modes present in its sentences. - It contains sentences from stories written by 11 famous authors from the 20th Century. - 4-5 stories by each author have been selected which were available in the public domain resulting in a collection of 53 stories. - Most of these short stories were originally written in Hindi but some of them were written in other Indian languages and later translated to Hindi. The corpus contains a total of 10472 sentences belonging to the following categories: - Argumentative - Descriptive - Dialogic - Informative - Narrative ### Supported Tasks and Leaderboards - Discourse Analysis of Hindi. ### Languages Hindi ## Dataset Structure - The dataset is structured into JSON format. ### Data Instances {'Story_no': 15, 'Sentence': ' गाँठ से साढ़े तीन रुपये लग गये, जो अब पेट में जाकर खनकते भी नहीं! जो तेरी करनी मालिक! ” “इसमें मालिक की क्या करनी है? ”', 'Discourse Mode': 'Dialogue'} ### Data Fields Sentence number, story number, sentence and discourse mode ### Data Splits - Train: 9983 ## Dataset Creation ### Curation Rationale - Present a new publicly available corpus consisting of sentences from short stories written in a low-resource language of Hindi having high quality annotation for five different discourse modes - argumentative, narrative, descriptive, dialogic and informative. - Perform a detailed analysis of the proposed annotated corpus and characterize the performance of different classification algorithms. ### Source Data - Source of all the data points in this dataset is Hindi stories written by famous authors of Hindi literature. #### Initial Data Collection and Normalization - All the data was collected from various Hindi websites. - We chose against crowd-sourcing the annotation pro- cess because we wanted to directly work with the an- notators for qualitative feedback and to also ensure high quality annotations. - We employed three native Hindi speakers with college level education for the an- notation task. - We first selected two random stories from our corpus and had the three annotators work on them independently and classify each sentence based on the discourse mode. - Please refer to this paper for detailed information: https://www.aclweb.org/anthology/2020.lrec-1.149/ #### Who are the source language producers? Please refer to this paper for detailed information: https://www.aclweb.org/anthology/2020.lrec-1.149/ ### Annotations #### Annotation process - The authors chose against crowd sourcing for labeling this dataset due to its highly sensitive nature. - The annotators are domain experts having degress in advanced clinical psychology and gender studies. - They were provided a guidelines document with instructions about each task and its definitions, labels and examples. - They studied the document, worked a few examples to get used to this annotation task. - They also provided feedback for improving the class definitions. - The annotation process is not mutually exclusive, implying that presence of one label does not mean the absence of the other one. #### Who are the annotators? - The annotators were three native Hindi speakers with college level education. - Please refer to the accompnaying paper for a detailed annotation process. ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset - As a future work we would also like to use the presented corpus to see how it could be further used in certain downstream tasks such as emotion analysis, machine translation, textual entailment, and speech sythesis for improving storytelling experience in Hindi language. ### Discussion of Biases [More Information Needed] ### Other Known Limitations - We could not get the best performance using the deep learning model trained on the data, due to insufficient data for DL models. ## Additional Information Please refer to this link: https://github.com/midas-research/hindi-discourse ### Dataset Curators - If you use the corpus in a product or application, then please credit the authors and [Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi] (http://midas.iiitd.edu.in) appropriately. Also, if you send us an email, we will be thrilled to know about how you have used the corpus. - If interested in commercial use of the corpus, send email to [email protected]. - Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi, India disclaims any responsibility for the use of the corpus and does not provide technical support. However, the contact listed above will be happy to respond to queries and clarifications - Please feel free to send us an email: - with feedback regarding the corpus. - with information on how you have used the corpus. - if interested in having us analyze your social media data. - if interested in a collaborative research project. ### Licensing Information - If you use the corpus in a product or application, then please credit the authors and [Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi] (http://midas.iiitd.edu.in) appropriately. ### Citation Information Please cite the following publication if you make use of the dataset: https://aclanthology.org/2020.lrec-1.149/ ``` @inproceedings{dhanwal-etal-2020-annotated, title = "An Annotated Dataset of Discourse Modes in {H}indi Stories", author = "Dhanwal, Swapnil and Dutta, Hritwik and Nankani, Hitesh and Shrivastava, Nilay and Kumar, Yaman and Li, Junyi Jessy and Mahata, Debanjan and Gosangi, Rakesh and Zhang, Haimin and Shah, Rajiv Ratn and Stent, Amanda", booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference", month = may, year = "2020", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://www.aclweb.org/anthology/2020.lrec-1.149", pages = "1191--1196", abstract = "In this paper, we present a new corpus consisting of sentences from Hindi short stories annotated for five different discourse modes argumentative, narrative, descriptive, dialogic and informative. We present a detailed account of the entire data collection and annotation processes. The annotations have a very high inter-annotator agreement (0.87 k-alpha). We analyze the data in terms of label distributions, part of speech tags, and sentence lengths. We characterize the performance of various classification algorithms on this dataset and perform ablation studies to understand the nature of the linguistic models suitable for capturing the nuances of the embedded discourse structures in the presented corpus.", language = "English", ISBN = "979-10-95546-34-4", } ``` ### Contributions Thanks to [@duttahritwik](https://github.com/duttahritwik) for adding this dataset.	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newspop	null	2022-11-03T16:31:06Z	367	2	[ "task_categories:text-classification", "task_ids:text-scoring", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:original", "language:en", "license:cc-by-4.0", "social-media-shares-prediction", "arxiv:1801.07055", "region:us" ]	[ "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - found language: - en license: - cc-by-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: - text-scoring paperswithcode_id: null pretty_name: News Popularity in Multiple Social Media Platforms tags: - social-media-shares-prediction dataset_info: features: - name: id dtype: int32 - name: title dtype: string - name: headline dtype: string - name: source dtype: string - name: topic dtype: string - name: publish_date dtype: string - name: facebook dtype: int32 - name: google_plus dtype: int32 - name: linked_in dtype: int32 splits: - name: train num_bytes: 27927641 num_examples: 93239 download_size: 30338277 dataset_size: 27927641 --- # Dataset Card for News Popularity in Multiple Social Media Platforms ## 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: [UCI](https://archive.ics.uci.edu/ml/datasets/News+Popularity+in+Multiple+Social+Media+Platforms) - Repository: - Paper: [Arxiv](https://arxiv.org/abs/1801.07055) - Leaderboard: [Kaggle](https://www.kaggle.com/nikhiljohnk/news-popularity-in-multiple-social-media-platforms/code) - Point of Contact: ### Dataset Summary Social sharing data across Facebook, Google+ and LinkedIn for 100k news items on the topics of: economy, microsoft, obama and palestine. ### Supported Tasks and Leaderboards Popularity prediction/shares prediction ### Languages English ## Dataset Structure ### Data Instances ``` { "id": 35873, "title": "Microsoft's 'teen girl' AI turns into a Hitler-loving sex robot within 24 ...", "headline": "Developers at Microsoft created 'Tay', an AI modelled to speak 'like a teen girl', in order to improve the customer service on their voice", "source": "Telegraph.co.uk", "topic": "microsoft", "publish_date": "2016-03-24 09:53:54", "facebook": 22346, "google_plus": 973, "linked_in": 1009 } ``` ### Data Fields - id: the sentence id in the source dataset - title: the title of the link as shared on social media - headline: the headline, or sometimes the lede of the story - source: the source news site - topic: the topic: one of "economy", "microsoft", "obama" and "palestine" - publish_date: the date the original article was published - facebook: the number of Facebook shares, or -1 if this data wasn't collected - google_plus: the number of Google+ likes, or -1 if this data wasn't collected - linked_in: the number of LinkedIn shares, or -1 if if this data wasn't collected ### Data Splits None ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? The source headlines were by journalists, while the titles were written by the people sharing it on social media. ### Annotations #### Annotation process The 'annotations' are simply the number of shares, or likes in the case of Google+ as collected from various API endpoints. #### Who are the annotators? Social media users. ### 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 License: Creative Commons Attribution 4.0 International License (CC-BY) ### Citation Information ``` @article{Moniz2018MultiSourceSF, title={Multi-Source Social Feedback of Online News Feeds}, author={N. Moniz and L. Torgo}, journal={ArXiv}, year={2018}, volume={abs/1801.07055} } ``` ### Contributions Thanks to [@frankier](https://github.com/frankier) for adding this dataset.	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tmu_gfm_dataset	null	2022-11-03T16:30:48Z	367	2	[ "task_categories:text2text-generation", "annotations_creators:crowdsourced", "language_creators:machine-generated", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "license:unknown", "grammatical-error-correction", "region:us" ]	[ "text2text-generation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - machine-generated language: - en license: - unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text2text-generation task_ids: [] paperswithcode_id: null pretty_name: TMU-GFM-Dataset tags: - grammatical-error-correction dataset_info: features: - name: source dtype: string - name: output dtype: string - name: grammer sequence: int32 - name: fluency sequence: int32 - name: meaning sequence: int32 - name: system dtype: string - name: ave_g dtype: float32 - name: ave_f dtype: float32 - name: ave_m dtype: float32 splits: - name: train num_bytes: 1446144 num_examples: 4221 download_size: 1270197 dataset_size: 1446144 --- # Dataset Card for TMU-GFM-Dataset ## 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: [N/A] - Repository: https://github.com/tmu-nlp/TMU-GFM-Dataset - Paper: [SOME: Reference-less Sub-Metrics Optimized for Manual Evaluations of Grammatical Error Correction](https://www.aclweb.org/anthology/2020.coling-main.573.pdf) - Leaderboard: [N/A] - Point of Contact: Check the paper. ### Dataset Summary Authors collected manual evaluations for the grammaticality, fluency, and meaning preservation of the system outputs of 1,381 sentences from CoNLL 2013. To collect the manual evaluations for various system outputs, each source sentence was corrected by the following five typical systems: statistical machine translation (SMT) (Grundkiewicz and Junczys-Dowmunt, 2018), recurrent neural network (RNN) (Luong et al., 2015), convolutional neural network (CNN) (Chollampatt and Ng, 2018), self-attention network (SAN) (Vaswani et al., 2017), and SAN with copy mechanism (SAN+Copy) (Zhao et al., 2019). Manual evaluation for the grammaticality, fluency, and meaning preservation were assigned to a total of 4,223 sentences. ### Supported Tasks and Leaderboards Grammatical Error Correction ### Languages English ## Dataset Structure ### Data Instances An example from the TMU-GFM-Dataset looks as follows: ``` {'ave_f': 3.4000000953674316, 'ave_g': 3.4000000953674316, 'ave_m': 3.5999999046325684, 'fluency': [3, 4, 3, 4, 3], 'grammer': [3, 4, 3, 4, 3], 'meaning': [3, 4, 4, 4, 3], 'output': 'After all, there will be an endless battle between the technology and human mentality.', 'source': 'Afterall there will be an endless battle between the technology and human mentality.', 'system': 'lstm,cnn'} ``` ### Data Fields The are 9 columns in the tmu-gfm-dataset. - source: source sentence. - output: system output sentence. - grammer: Grammaticaliry annotations by 5 annotators. - fluency: Fluency annotations by 5 annotators. - meaning: Meaning Preservation annotations by 5 annotators. - system: Which system the output sentence is from. - ave_g: Average grammer score. - ave_f: Average fluency score. - ave_m: Average meaning score. ### Data Splits Authors divided the dataset into train/dev/test with 3,376/422/423 sentences and used for fine-tuning BERT in thier paper. ## Dataset Creation ### Curation Rationale The authors proposed a reference-less metric trained on manual evaluations of system outputs for grammatical error correction (GEC). They said that previous studies have shown that reference-less metrics are promising; however, existing metrics are not optimized for manual evaluation of the system output because there is no dataset of system output with manual evaluation. To achieve a better correlation with manual evaluation, they created a dataset to optimize each sub-metric to the manual evaluation of GEC systems. Their annotators evaluated the output of five typical GEC systems. ### Source Data #### Initial Data Collection and Normalization Authors collected manual evaluations for the grammaticality, fluency, and meaning preservation of the system outputs of 1,381 sentences from CoNLL 2013. To collect the manual evaluations for various system outputs, each source sentence was corrected by the following five typical systems: statistical machine translation (SMT) (Grundkiewicz and Junczys-Dowmunt, 2018), recurrent neural network (RNN) (Luong et al., 2015), convolutional neural network (CNN) (Chollampatt and Ng, 2018), self-attention network (SAN) (Vaswani et al., 2017), and SAN with copy mechanism (SAN+Copy) (Zhao et al., 2019). #### Who are the source language producers? machine-generated ### Annotations #### Annotation process By excluding duplicate corrected sentences, manual evaluation for the grammaticality, fluency, and meaning preservation were assigned to a total of 4,223 sentences, as follows: - Grammaticality: Annotators evaluated the grammatical correctness of the system output. The authors followed the five-point scale evaluation criteria (4: Perfect, 3: Comprehensible, 2: Somewhat comprehensible, 1: Incomprehensible, and 0: Other) proposed by Heilman et al. (2014). - Fluency: Annotators evaluated how natural the sentence sounds for native speakers. The authors followed the criteria (4: Extremely natural, 3: Somewhat natural, 2: Somewhat unnatural, and 1: Extremely unnatural) proposed by Lau et al. (2015). - Meaning preservation: Annotators evaluated the extent to which the meaning of source sentences is preserved in system output. The authors followed the criteria (4: Identical, 3: Minor differences, 2: Moderate differences, 1: Sub- stantially different, and 0: Other) proposed by Xu et al. (2016). Finally, the authors created a dataset with manual evaluations for a total of 4,221 sentences, excluding sentences in which three or more annotators answered “0: Other.” #### Who are the annotators? Five native English annotators reqruited by using Amazon Mechaincal turk ### 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 @inproceedings{yoshimura-etal-2020-reference, title = "{SOME}: Reference-less Sub-Metrics Optimized for Manual Evaluations of Grammatical Error Correction", author = "Yoshimura, Ryoma and Kaneko, Masahiro and Kajiwara, Tomoyuki and Komachi, Mamoru", booktitle = "Proceedings of the 28th International Conference on Computational Linguistics", month = dec, year = "2020", address = "Barcelona, Spain (Online)", publisher = "International Committee on Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.coling-main.573", pages = "6516--6522", abstract = "We propose a reference-less metric trained on manual evaluations of system outputs for grammatical error correction (GEC). Previous studies have shown that reference-less metrics are promising; however, existing metrics are not optimized for manual evaluations of the system outputs because no dataset of the system output exists with manual evaluation. This study manually evaluates outputs of GEC systems to optimize the metrics. Experimental results show that the proposed metric improves correlation with the manual evaluation in both system- and sentence-level meta-evaluation. Our dataset and metric will be made publicly available.", } ### Contributions Thanks to [@forest1988](https://github.com/forest1988) for adding this dataset.	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mystic-leung/medical_cord19	mystic-leung	2023-09-14T03:00:13Z	367	2	[ "task_categories:summarization", "language:aa", "license:openrail", "medical", "region:us" ]	[ "summarization" ]	2023-08-22T13:35:59Z	--- license: openrail task_categories: - summarization language: - aa tags: - medical --- ## Description This dataset contains large amounts of biomedical abstracts and corresponding summaries.	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OpenAssistant/OASST-DE	OpenAssistant	2023-11-13T10:24:29Z	367	9	[ "size_categories:1K<n<10K", "language:de", "license:apache-2.0", "arxiv:2304.07327", "region:us" ]	null	2023-08-29T12:04:11Z	--- dataset_info: features: - name: conversation list: - name: role dtype: string - name: text dtype: string splits: - name: train num_bytes: 8022604.792326268 num_examples: 3721 download_size: 4325950 dataset_size: 8022604.792326268 license: apache-2.0 language: - de size_categories: - 1K<n<10K --- # German OpenAssistant Conversations Dataset (OASST-DE) With the goal of advancing open-source, german-language LLM research, we present OASST-DE: a high quality subset of a recent (25.08.23) dump from the [OpenAssistant website](https://www.open-assistant.io/) translated to German using the GPT-3.5 API. More details on how the dataset was filtered and translated under [dataset creation.](#dataset-creation-process) For more details on the OpenAssistant Project, look at the [first OASST dataset (OASST1)](https://huggingface.co/datasets/OpenAssistant/oasst1), [the Open-Assistant GitHub repo](https://github.com/LAION-AI/Open-Assistant) or [our paper](https://arxiv.org/abs/2304.07327). This dataset was created as part of LAION's LeoLM (Linguistically Enhanced Open Language Model) project led by Björn Plüster. Check out LeoLM-Chat trained with OASST-DE ([7b](https://huggingface.co/LeoLM/leo-hessianai-7b-chat), [13b](https://huggingface.co/LeoLM/leo-hessianai-13b-chat)) finetuned on OASST-DE and read [their blog post](https://laion.ai/blog/leo-lm/)) for more info on LeoLM. ## Dataset Creation Process This dataset was created from a recent OASST dump by following these steps: - Filter for Top1 response trees with assistant response leaves - Filter first prompt quality >= 0.5 - Filter total conversation length < 1900 tokens to fit in GPT3.5 context length - Filter for `'lang' == 'de'` -> add to dataset - Filter for `'lang' == 'en'` (other languages often result in failed translations) - Translate using GPT-3.5-turbo API (total cost ~15$). This results in around 3.7k samples of high-quality assistant conversations. ## Dataset Structure This dataset has only one `'conversation'` field. Each example is a list of an alternating conversation between `'prompter'` and `'assistant'`, where each entry is a dict with `'text'` and `'role'` fields: ```json "conversation": [ {"role": "prompter", "text": "Moin, wie geht's dir?"}, {"role": "assistant", "text": "Moin Moin! Mir geht es gut, und dir?"}, ... ] ``` ## Usage with 🤗Datasets: ```python from datasets import load_dataset ds = load_dataset("OpenAssistant/OASST-DE", split="train") print(ds[0]["conversation"]) ```	[ -0.4078393280506134, -0.8423583507537842, 0.3895381987094879, 0.03126863017678261, -0.20792368054389954, -0.20354127883911133, -0.14347901940345764, -0.5136016011238098, 0.14079920947551727, 0.47786155343055725, -0.5429739952087402, -0.7011434435844421, -0.4442865550518036, -0.02904774621129036, -0.16474781930446625, 1.1331685781478882, -0.20104475319385529, 0.23671117424964905, 0.08514594286680222, -0.28906041383743286, -0.33279040455818176, -0.48925909399986267, -0.8133406043052673, -0.23073579370975494, 0.26594358682632446, 0.37273702025413513, 0.7064017653465271, 0.5088110566139221, 0.42619433999061584, 0.2845027446746826, -0.17984150350093842, 0.12878568470478058, -0.7510002851486206, 0.13840782642364502, -0.042044203728437424, -0.06826615333557129, -0.6424990892410278, 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ostapeno/qa-openai_batched_icl0_clen512_maxD-1_maxC2500_0_cleaned_9000_train	ostapeno	2023-11-03T18:45:53Z	367	0	[ "region:us" ]	null	2023-11-03T18:45:43Z	--- configs: - config_name: default data_files: - split: abstract_algebra path: data/abstract_algebra-* - split: college_biology path: data/college_biology-* - split: formal_logic path: data/formal_logic-* - split: global_facts path: data/global_facts-* - split: high_school_government_and_politics path: data/high_school_government_and_politics-* - split: high_school_physics path: data/high_school_physics-* - split: machine_learning path: data/machine_learning-* - split: prehistory path: data/prehistory-* - split: security_studies path: data/security_studies-* - split: sociology path: data/sociology-* dataset_info: features: - name: id dtype: string - name: context dtype: string - name: docno dtype: string - name: subject dtype: string - name: icl_examples dtype: 'null' - name: author_instr dtype: string - name: instruction dtype: string - name: response dtype: string splits: - name: abstract_algebra num_bytes: 25746312 num_examples: 9000 - name: college_biology num_bytes: 26406462 num_examples: 9000 - name: formal_logic num_bytes: 26700506 num_examples: 9000 - name: global_facts num_bytes: 26114274 num_examples: 9000 - name: high_school_government_and_politics num_bytes: 27122691 num_examples: 9000 - name: high_school_physics num_bytes: 27471037 num_examples: 9000 - name: machine_learning num_bytes: 27810367 num_examples: 9000 - name: prehistory num_bytes: 27171444 num_examples: 9000 - name: security_studies num_bytes: 26736316 num_examples: 9000 - name: sociology num_bytes: 25312963 num_examples: 9000 download_size: 38613929 dataset_size: 266592372 --- # Dataset Card for "qa-openai_batched_icl0_clen512_maxD-1_maxC2500_0_cleaned_9000_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)	[ -0.5265905261039734, 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farsi_news	null	2022-11-03T16:15:15Z	366	2	[ "task_categories:text-generation", "task_categories:fill-mask", "task_ids:language-modeling", "task_ids:masked-language-modeling", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:fa", "license:unknown", "region:us" ]	[ "text-generation", "fill-mask" ]	2022-03-02T23:29:22Z	--- annotations_creators: - found language_creators: - found language: - fa license: - unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: null pretty_name: FarsiNews dataset_info: features: - name: title dtype: string - name: summary dtype: string - name: link dtype: string - name: tags sequence: string splits: - name: hamshahri num_bytes: 1267659 num_examples: 2203 - name: radiofarda num_bytes: 265272 num_examples: 284 download_size: 1648337 dataset_size: 1532931 --- # Dataset Card for FarsiNews ## 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: [link](https://github.com/sci2lab/Farsi-datasets) - Paper: []() - Leaderboard: []() - Point of Contact: []() ### Dataset Summary https://github.com/sci2lab/Farsi-datasets Contains Farsi (Persian) datasets for Machine Learning tasks, particularly NLP. These datasets have been extracted from the RSS feed of two Farsi news agency websites: - Hamshahri - RadioFarda ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure [More Information Needed] ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### 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 https://github.com/sci2lab/Farsi-datasets ### Contributions Thanks to [@Narsil](https://github.com/Narsil) for adding this dataset.	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open-llm-leaderboard/details_Writer__palmyra-med-20b	open-llm-leaderboard	2023-10-27T07:44:04Z	366	0	[ "region:us" ]	null	2023-09-11T17:21:33Z	--- pretty_name: Evaluation run of Writer/palmyra-med-20b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Writer/palmyra-med-20b](https://huggingface.co/Writer/palmyra-med-20b) 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_Writer__palmyra-med-20b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-27T07:43:51.319096](https://huggingface.co/datasets/open-llm-leaderboard/details_Writer__palmyra-med-20b/blob/main/results_2023-10-27T07-43-51.319096.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\": 0.05851510067114094,\n\ \ \"em_stderr\": 0.0024037002515447264,\n \"f1\": 0.11879089765100655,\n\ \ \"f1_stderr\": 0.002692444748823806,\n \"acc\": 0.34002374380150946,\n\ \ \"acc_stderr\": 0.008900409699475408\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.05851510067114094,\n \"em_stderr\": 0.0024037002515447264,\n\ \ \"f1\": 0.11879089765100655,\n \"f1_stderr\": 0.002692444748823806\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.026535253980288095,\n \ \ \"acc_stderr\": 0.004427045987265168\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6535122336227308,\n \"acc_stderr\": 0.013373773411685648\n\ \ }\n}\n```" repo_url: https://huggingface.co/Writer/palmyra-med-20b 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_11T17_21_21.677448 path: - '/details_harness\|arc:challenge\|25_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|arc:challenge\|25_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-12T21-53-25.718910.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_27T07_43_51.319096 path: - '/details_harness\|drop\|3_2023-10-27T07-43-51.319096.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-27T07-43-51.319096.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_27T07_43_51.319096 path: - '/details_harness\|gsm8k\|5_2023-10-27T07-43-51.319096.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-27T07-43-51.319096.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hellaswag\|10_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hellaswag\|10_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T17-21-21.677448.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T21-53-25.718910.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T21-53-25.718910.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_11T17_21_21.677448 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-11T17-21-21.677448.parquet' - split: 2023_09_12T21_53_25.718910 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T21-53-25.718910.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T21-53-25.718910.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_27T07_43_51.319096 path: - '/details_harness\|winogrande\|5_2023-10-27T07-43-51.319096.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-27T07-43-51.319096.parquet' - config_name: results data_files: - split: 2023_09_11T17_21_21.677448 path: - results_2023-09-11T17-21-21.677448.parquet - split: 2023_09_12T21_53_25.718910 path: - results_2023-09-12T21-53-25.718910.parquet - split: 2023_10_27T07_43_51.319096 path: - results_2023-10-27T07-43-51.319096.parquet - split: latest path: - results_2023-10-27T07-43-51.319096.parquet --- # Dataset Card for Evaluation run of Writer/palmyra-med-20b ## Dataset Description - Homepage: - Repository: https://huggingface.co/Writer/palmyra-med-20b - 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 [Writer/palmyra-med-20b](https://huggingface.co/Writer/palmyra-med-20b) 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_Writer__palmyra-med-20b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-27T07:43:51.319096](https://huggingface.co/datasets/open-llm-leaderboard/details_Writer__palmyra-med-20b/blob/main/results_2023-10-27T07-43-51.319096.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": 0.05851510067114094, "em_stderr": 0.0024037002515447264, "f1": 0.11879089765100655, "f1_stderr": 0.002692444748823806, "acc": 0.34002374380150946, "acc_stderr": 0.008900409699475408 }, "harness\|drop\|3": { "em": 0.05851510067114094, "em_stderr": 0.0024037002515447264, "f1": 0.11879089765100655, "f1_stderr": 0.002692444748823806 }, "harness\|gsm8k\|5": { "acc": 0.026535253980288095, "acc_stderr": 0.004427045987265168 }, "harness\|winogrande\|5": { "acc": 0.6535122336227308, "acc_stderr": 0.013373773411685648 } } ``` ### 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]	[ -0.37976062297821045, -0.6909648180007935, 0.26644566655158997, 0.26817408204078674, -0.0707208514213562, 0.09969840943813324, -0.44477981328964233, -0.25395703315734863, 0.39581337571144104, 0.6698043942451477, -0.652725875377655, -1.0232081413269043, -0.694863498210907, 0.24697895348072052, -0.20020988583564758, 1.304119348526001, -0.36231914162635803, -0.26485955715179443, 0.0802396908402443, -0.29999345541000366, -0.21536357700824738, -0.41667640209198, -0.5132437348365784, 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open-llm-leaderboard/details_BELLE-2__BELLE-Llama2-13B-chat-0.4M	open-llm-leaderboard	2023-10-26T14:38:06Z	366	0	[ "region:us" ]	null	2023-10-01T13:36:59Z	--- pretty_name: Evaluation run of BELLE-2/BELLE-Llama2-13B-chat-0.4M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BELLE-2/BELLE-Llama2-13B-chat-0.4M](https://huggingface.co/BELLE-2/BELLE-Llama2-13B-chat-0.4M)\ \ 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_BELLE-2__BELLE-Llama2-13B-chat-0.4M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-26T14:37:54.228887](https://huggingface.co/datasets/open-llm-leaderboard/details_BELLE-2__BELLE-Llama2-13B-chat-0.4M/blob/main/results_2023-10-26T14-37-54.228887.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\": 0.28492030201342283,\n\ \ \"em_stderr\": 0.004622517599527834,\n \"f1\": 0.36695364932886015,\n\ \ \"f1_stderr\": 0.004514579216323901,\n \"acc\": 0.4496880334950361,\n\ \ \"acc_stderr\": 0.010877118313612513\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.28492030201342283,\n \"em_stderr\": 0.004622517599527834,\n\ \ \"f1\": 0.36695364932886015,\n \"f1_stderr\": 0.004514579216323901\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.14404852160727824,\n \ \ \"acc_stderr\": 0.009672110973065286\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.755327545382794,\n \"acc_stderr\": 0.012082125654159738\n\ \ }\n}\n```" repo_url: https://huggingface.co/BELLE-2/BELLE-Llama2-13B-chat-0.4M 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_01T13_36_40.123057 path: - '/details_harness\|arc:challenge\|25_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-01T13-36-40.123057.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_26T14_37_54.228887 path: - '/details_harness\|drop\|3_2023-10-26T14-37-54.228887.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-26T14-37-54.228887.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_26T14_37_54.228887 path: - '/details_harness\|gsm8k\|5_2023-10-26T14-37-54.228887.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-26T14-37-54.228887.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hellaswag\|10_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T13-36-40.123057.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T13-36-40.123057.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_01T13_36_40.123057 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T13-36-40.123057.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T13-36-40.123057.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_26T14_37_54.228887 path: - '/details_harness\|winogrande\|5_2023-10-26T14-37-54.228887.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-26T14-37-54.228887.parquet' - config_name: results data_files: - split: 2023_10_01T13_36_40.123057 path: - results_2023-10-01T13-36-40.123057.parquet - split: 2023_10_26T14_37_54.228887 path: - results_2023-10-26T14-37-54.228887.parquet - split: latest path: - results_2023-10-26T14-37-54.228887.parquet --- # Dataset Card for Evaluation run of BELLE-2/BELLE-Llama2-13B-chat-0.4M ## Dataset Description - Homepage: - Repository: https://huggingface.co/BELLE-2/BELLE-Llama2-13B-chat-0.4M - 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 [BELLE-2/BELLE-Llama2-13B-chat-0.4M](https://huggingface.co/BELLE-2/BELLE-Llama2-13B-chat-0.4M) 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_BELLE-2__BELLE-Llama2-13B-chat-0.4M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-26T14:37:54.228887](https://huggingface.co/datasets/open-llm-leaderboard/details_BELLE-2__BELLE-Llama2-13B-chat-0.4M/blob/main/results_2023-10-26T14-37-54.228887.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": 0.28492030201342283, "em_stderr": 0.004622517599527834, "f1": 0.36695364932886015, "f1_stderr": 0.004514579216323901, "acc": 0.4496880334950361, "acc_stderr": 0.010877118313612513 }, "harness\|drop\|3": { "em": 0.28492030201342283, "em_stderr": 0.004622517599527834, "f1": 0.36695364932886015, "f1_stderr": 0.004514579216323901 }, "harness\|gsm8k\|5": { "acc": 0.14404852160727824, "acc_stderr": 0.009672110973065286 }, "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]	[ -0.3833319842815399, -0.6625766754150391, 0.1763797551393509, 0.32168570160865784, -0.048838093876838684, 0.14191673696041107, -0.2683233320713043, -0.33438530564308167, 0.46251770853996277, 0.6057047247886658, -0.7577412724494934, -0.8671621084213257, -0.7130577564239502, 0.16200342774391174, -0.26264339685440063, 1.1730453968048096, -0.1425294429063797, -0.22970591485500336, 0.06621962040662766, -0.1902717649936676, -0.3470037281513214, -0.4496631920337677, -0.5963785648345947, 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erwanlc/cocktails_recipe_no_brand	erwanlc	2022-10-25T09:17:08Z	365	3	[ "annotations_creators:machine-generated", "language_creators:machine-generated", "multilinguality:monolingual", "size_categories:2M<n<3M", "language:en", "license:other", "region:us" ]	[]	2022-03-02T23:29:22Z	--- annotations_creators: - machine-generated language_creators: - machine-generated language: - en license: - other multilinguality: - monolingual size_categories: - 2M<n<3M source_datasets: [] task_categories: [] task_ids: [] pretty_name: cocktails_recipe_no_brand language_bcp47: - en - en-US --- # Dataset Card for cocktails_recipe ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Source Data](#source-data) - [Personal and Sensitive Information](#personal-and-sensitive-information) ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This dataset contains a list of cocktails and how to do them. ### Languages The language is english. ## Dataset Structure ### Data Fields - Title: name of the cocktail - Glass: type of glass to use - Garnish: garnish to use for the glass - Recipe: how to do the cocktail - Ingredients: ingredients required - Raw Ingredients: ingredients mapped to their raw ingredients to remove the brand ### Data Splits Currently, there is no splits. ## Dataset Creation ### Source Data #### Initial Data Collection and Normalization The dataset was created by scraping the Diffords cocktail website. ### Personal and Sensitive Information It should not contain any personal or sensitive information. ### Contributions Thanks to [@github-erwanlc](https://github.com/erwanlc) for adding this dataset.	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MBZUAI/LaMini-instruction	MBZUAI	2023-04-30T11:01:41Z	365	110	[ "task_categories:text2text-generation", "size_categories:1M<n<10M", "language:en", "license:cc-by-nc-4.0", "arxiv:2304.14402", "region:us" ]	[ "text2text-generation" ]	2023-04-08T07:48:12Z	--- license: cc-by-nc-4.0 task_categories: - text2text-generation language: - en size_categories: - 1M<n<10M dataset_info: features: - name: instruction dtype: string - name: response dtype: string - name: instruction_source dtype: string splits: - name: train num_bytes: 1162632572 num_examples: 2585615 download_size: 704293718 dataset_size: 1162632572 --- # Dataset Card for "LaMini-Instruction" <p align="center" width="100%"> <a><img src="https://raw.githubusercontent.com/mbzuai-nlp/lamini-lm/main/images/lamini.png" alt="Title" style="width: 100%; min-width: 300px; display: block; margin: auto;"></a> </p> <p align="center"> <a href="https://twitter.com/WuMinghao_nlp" target="_blank">Minghao Wu</a>, <a href="https://twitter.com/MacAbdul9" target="_blank">Abdul Waheed</a>, <a href="https://chiyuzhang94.github.io/" target="_blank">Chiyu Zhang</a>, <a href="https://mageed.arts.ubc.ca/" target="_blank">Muhammad Abdul-Mageed</a>, <a href="https://afaji.github.io/" target="_blank">Alham Fikri Aji</a>,</p> ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Instances](#data-instances) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Additional Information](#additional-information) ## Dataset Description We distill the knowledge from large language models by performing sentence/offline distillation (Kim and Rush, 2016). We generate a total of 2.58M pairs of instructions and responses using [`gpt-3.5-turbo`](https://openai.com/api/) based on several existing resources of prompts, including [self-instruct](https://github.com/yizhongw/self-instruct) (Wang et al., 2022), [P3](https://huggingface.co/datasets/bigscience/P3) (Sanh et al., 2022), [FLAN](https://github.com/google-research/FLAN) (Longpre et al., 2023) and [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) (Taori et al., 2023). More information about the process for generating our instruction dataset, please refer to [our paper](https://arxiv.org/abs/2304.14402). We use LaMini-Instruction to fine-tune various small-sized language models, resulting in [LaMini-LM model series](https://github.com/mbzuai-nlp/laMini-LM#models). Each sample contain the following two fields: * `instruction`: `string`, describes the task that the model is expected to perform. * `response`: `string`, the response to the instruction as generated by `gpt-3.5-turbo`. * `instruction_source`: `string`, the source of a instruction. The possible values are `{'alpaca', 'generated_flan', 'generated_p3', 'original_flan', 'original_p3', 'self_instruct_with_topic', 'self_instruct_without_topic'}`. Two examples in our LaMini-instruction data: ```json { "instruction": "What is the capital of Australia?\n\nIs Canberra the only city chosen to serve as a capital due to a compromise between Sydney and Melbourne?", "response": "The capital of Australia is Canberra. Yes, Canberra was chosen as the capital of Australia in 1908 due to a compromise between Sydney and Melbourne, as neither city wanted the other to become the capital.", "instruction_source": "generated_flan" } ``` ```json { "instruction": "Create a poem that has the word \"ocean\" in every other line.", "response": "The ocean's depth is a mystery,\nIts waves crashing with energy.\nSalt air fills the coastal scene,\nThe ocean's blue hues pure and clean.\n\nSeagulls cry out a melancholy song,\nThe ocean's rhythm steady and strong.\nSunsets paint the water gold,\nThe ocean's secrets forever untold.", "instruction_source": "self_instruct_without_topic" } ``` ## Considerations for Using the Data As the output is distilled from ChatGPT, this data contains errors and biases produced by ChatGPT. Models trained with this dataset will inherit the errors and biases. We encourage users to use this data with caution and propose new methods to filter or improve the imperfections. ### Licensing Information The dataset is available under the [Creative Commons NonCommercial (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/legalcode). ### Citation Information Please cite us if you use our data or models. ```bibtex @article{lamini-lm, author = {Minghao Wu and Abdul Waheed and Chiyu Zhang and Muhammad Abdul-Mageed and Alham Fikri Aji }, title = {LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions}, journal = {CoRR}, volume = {abs/2304.14402}, year = {2023}, url = {https://arxiv.org/abs/2304.14402}, eprinttype = {arXiv}, eprint = {2304.14402} } ```	[ -0.4712550938129425, -0.8536713123321533, 0.27738791704177856, 0.08997409790754318, -0.27629345655441284, -0.4465496242046356, -0.27667224407196045, -0.28058603405952454, 0.0038051775190979242, 0.6824484467506409, -0.8180960416793823, -0.6123979091644287, 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open-llm-leaderboard/details_MayaPH__GodziLLa-30B	open-llm-leaderboard	2023-09-17T01:20:49Z	365	0	[ "region:us" ]	null	2023-08-17T23:56:09Z	--- pretty_name: Evaluation run of MayaPH/GodziLLa-30B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [MayaPH/GodziLLa-30B](https://huggingface.co/MayaPH/GodziLLa-30B) 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__GodziLLa-30B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T01:20:37.554639](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__GodziLLa-30B/blob/main/results_2023-09-17T01-20-37.554639.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\": 0.22808305369127516,\n\ \ \"em_stderr\": 0.004297060303049989,\n \"f1\": 0.34862416107382826,\n\ \ \"f1_stderr\": 0.004249472334452047,\n \"acc\": 0.3827162119062479,\n\ \ \"acc_stderr\": 0.006833824703926247\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.22808305369127516,\n \"em_stderr\": 0.004297060303049989,\n\ \ \"f1\": 0.34862416107382826,\n \"f1_stderr\": 0.004249472334452047\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0037907505686125853,\n \ \ \"acc_stderr\": 0.0016927007401501802\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7616416732438832,\n \"acc_stderr\": 0.011974948667702313\n\ \ }\n}\n```" repo_url: https://huggingface.co/MayaPH/GodziLLa-30B 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_19T22_21_46.977528 path: - '/details_harness\|arc:challenge\|25_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T22:21:46.977528.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T01_20_37.554639 path: - '/details_harness\|drop\|3_2023-09-17T01-20-37.554639.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T01-20-37.554639.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T01_20_37.554639 path: - '/details_harness\|gsm8k\|5_2023-09-17T01-20-37.554639.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T01-20-37.554639.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hellaswag\|10_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T22:21:46.977528.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T22:21:46.977528.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T22_21_46.977528 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T22:21:46.977528.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T22:21:46.977528.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T01_20_37.554639 path: - '/details_harness\|winogrande\|5_2023-09-17T01-20-37.554639.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T01-20-37.554639.parquet' - config_name: results data_files: - split: 2023_07_19T22_21_46.977528 path: - results_2023-07-19T22:21:46.977528.parquet - split: 2023_09_17T01_20_37.554639 path: - results_2023-09-17T01-20-37.554639.parquet - split: latest path: - results_2023-09-17T01-20-37.554639.parquet --- # Dataset Card for Evaluation run of MayaPH/GodziLLa-30B ## Dataset Description - Homepage: - Repository: https://huggingface.co/MayaPH/GodziLLa-30B - 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/GodziLLa-30B](https://huggingface.co/MayaPH/GodziLLa-30B) 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__GodziLLa-30B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T01:20:37.554639](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__GodziLLa-30B/blob/main/results_2023-09-17T01-20-37.554639.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": 0.22808305369127516, "em_stderr": 0.004297060303049989, "f1": 0.34862416107382826, "f1_stderr": 0.004249472334452047, "acc": 0.3827162119062479, "acc_stderr": 0.006833824703926247 }, "harness\|drop\|3": { "em": 0.22808305369127516, "em_stderr": 0.004297060303049989, "f1": 0.34862416107382826, "f1_stderr": 0.004249472334452047 }, "harness\|gsm8k\|5": { "acc": 0.0037907505686125853, "acc_stderr": 0.0016927007401501802 }, "harness\|winogrande\|5": { "acc": 0.7616416732438832, "acc_stderr": 0.011974948667702313 } } ``` ### 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]	[ -0.5172390341758728, -0.6370846629142761, 0.20063075423240662, 0.3005668818950653, -0.21376824378967285, 0.1642398089170456, -0.33532479405403137, -0.18875330686569214, 0.37852126359939575, 0.5018324851989746, -0.653843104839325, -0.9542935490608215, -0.6946123242378235, 0.23166529834270477, -0.06964471191167831, 1.171669602394104, -0.24996627867221832, -0.22960032522678375, 0.056894298642873764, -0.31128743290901184, -0.3155210018157959, -0.31283998489379883, -0.5973270535469055, 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open-llm-leaderboard/details_DanielSc4__RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1	open-llm-leaderboard	2023-09-17T02:48:47Z	365	0	[ "region:us" ]	null	2023-08-18T18:57:04Z	--- pretty_name: Evaluation run of DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1](https://huggingface.co/DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1)\ \ 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_DanielSc4__RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T02:48:34.876063](https://huggingface.co/datasets/open-llm-leaderboard/details_DanielSc4__RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1/blob/main/results_2023-09-17T02-48-34.876063.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\": 0.018141778523489933,\n\ \ \"em_stderr\": 0.0013667968592600823,\n \"f1\": 0.0824182046979865,\n\ \ \"f1_stderr\": 0.0019512337351707363,\n \"acc\": 0.30108941444123377,\n\ \ \"acc_stderr\": 0.0072592536452981875\n },\n \"harness\|drop\|3\":\ \ {\n \"em\": 0.018141778523489933,\n \"em_stderr\": 0.0013667968592600823,\n\ \ \"f1\": 0.0824182046979865,\n \"f1_stderr\": 0.0019512337351707363\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.000758150113722517,\n \ \ \"acc_stderr\": 0.000758150113722541\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.601420678768745,\n \"acc_stderr\": 0.013760357176873834\n\ \ }\n}\n```" repo_url: https://huggingface.co/DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1 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_17T19_06_24.257655 path: - '/details_harness\|arc:challenge\|25_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-17T19:06:24.257655.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T02_48_34.876063 path: - '/details_harness\|drop\|3_2023-09-17T02-48-34.876063.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T02-48-34.876063.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T02_48_34.876063 path: - '/details_harness\|gsm8k\|5_2023-09-17T02-48-34.876063.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T02-48-34.876063.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hellaswag\|10_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T19:06:24.257655.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-17T19:06:24.257655.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_17T19_06_24.257655 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T19:06:24.257655.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-17T19:06:24.257655.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T02_48_34.876063 path: - '/details_harness\|winogrande\|5_2023-09-17T02-48-34.876063.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T02-48-34.876063.parquet' - config_name: results data_files: - split: 2023_08_17T19_06_24.257655 path: - results_2023-08-17T19:06:24.257655.parquet - split: 2023_09_17T02_48_34.876063 path: - results_2023-09-17T02-48-34.876063.parquet - split: latest path: - results_2023-09-17T02-48-34.876063.parquet --- # Dataset Card for Evaluation run of DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1 ## Dataset Description - Homepage: - Repository: https://huggingface.co/DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1 - 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 [DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1](https://huggingface.co/DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1) 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_DanielSc4__RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T02:48:34.876063](https://huggingface.co/datasets/open-llm-leaderboard/details_DanielSc4__RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1/blob/main/results_2023-09-17T02-48-34.876063.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": 0.018141778523489933, "em_stderr": 0.0013667968592600823, "f1": 0.0824182046979865, "f1_stderr": 0.0019512337351707363, "acc": 0.30108941444123377, "acc_stderr": 0.0072592536452981875 }, "harness\|drop\|3": { "em": 0.018141778523489933, "em_stderr": 0.0013667968592600823, "f1": 0.0824182046979865, "f1_stderr": 0.0019512337351707363 }, "harness\|gsm8k\|5": { "acc": 0.000758150113722517, "acc_stderr": 0.000758150113722541 }, "harness\|winogrande\|5": { "acc": 0.601420678768745, "acc_stderr": 0.013760357176873834 } } ``` ### 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]	[ -0.45868486166000366, -0.8012303709983826, 0.18304722011089325, 0.2523333430290222, -0.15043209493160248, 0.05296909436583519, -0.3661184012889862, -0.2623933255672455, 0.5586703419685364, 0.5897898077964783, -0.6962619423866272, -0.9641145467758179, -0.6949290633201599, 0.15299376845359802, -0.28960931301116943, 1.1341067552566528, -0.27997106313705444, -0.2537309229373932, 0.036850202828645706, -0.35491490364074707, -0.45340195298194885, -0.42585867643356323, -0.5467405319213867, 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Goader/ukrainian-treebank-lm	Goader	2023-09-11T02:17:39Z	365	0	[ "task_categories:fill-mask", "task_categories:text-generation", "language:uk", "license:cc-by-nc-sa-4.0", "region:us" ]	[ "fill-mask", "text-generation" ]	2023-09-10T20:18:33Z	--- license: cc-by-nc-sa-4.0 task_categories: - fill-mask - text-generation language: - uk pretty_name: Ukrainian Treebank (Language Modeling) ---	[ -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, 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mponty/code_tutorials	mponty	2023-11-01T02:22:58Z	365	4	[ "task_categories:text-generation", "size_categories:100K<n<1M", "language:en", "language:ru", "language:zh", "language:es", "code", "region:us" ]	[ "text-generation" ]	2023-10-31T14:32:09Z	--- dataset_info: features: - name: text dtype: string - name: url dtype: string - name: dump dtype: string - name: lang dtype: string - name: source dtype: string splits: - name: train num_bytes: 3124929718.313386 num_examples: 518410 download_size: 2971113091 dataset_size: 3124929718.313386 configs: - config_name: default data_files: - split: train path: data/train-* task_categories: - text-generation language: - en - ru - zh - es tags: - code pretty_name: k size_categories: - 100K<n<1M --- # Coding Tutorials This comprehensive dataset consists of 500,000 documents, summing up to around 1.5 billion tokens. Predominantly composed of coding tutorials, it has been meticulously compiled from various web crawl datasets like RefinedWeb, OSCAR, and Escorpius. The selection process involved a stringent filtering of files using regular expressions to ensure the inclusion of content that contains programming code (most of them). These tutorials offer more than mere code snippets. They provide an extensive context, including the rationale behind the code, the problem being addressed, and detailed step-by-step instructions. This layered context is helpful for training a code-LM model, enabling it to discern the user intent behind a piece of code and thus facilitating more contextually relevant assistance. ### Programming Language Distribution ``` cpp ▏ 39% █████████████████████████ python ▏ 25% ████████████████ java ▏ 16% ██████████ csharp ▏ 3% ██ javascript ▏ 1% ▋ kotlin ▏ 1% ▋ other ▏ 14% █████████ ``` ### Natural language distribution ``` en ▏ 80% █████████████████████████ ru ▏ 16% █████ zh ▏ 2% ▋ es ▏ 2% ▋ ```	[ -0.37918925285339355, -0.5453417897224426, 0.26849350333213806, 0.2355893850326538, -0.11710123717784882, 0.24783717095851898, -0.1778336465358734, -0.08868741244077682, 0.04896740987896919, 0.4703766703605652, -0.5965960621833801, -0.942409336566925, -0.2887328267097473, 0.13989943265914917, -0.7169004082679749, 1.258028507232666, 0.18747888505458832, 0.1443203091621399, -0.2084316909313202, 0.17898234724998474, -0.35739994049072266, -0.38754889369010925, -0.348324716091156, 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huggingartists/imagine-dragons	huggingartists	2022-10-25T09:31:53Z	364	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/imagine-dragons" ## 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: 0.380929 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/ec1df125fd46ec3ef56f228df021a8cd.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/imagine-dragons"> <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">Imagine Dragons</div> <a href="https://genius.com/artists/imagine-dragons"> <div style="text-align: center; font-size: 14px;">@imagine-dragons</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/imagine-dragons). ### 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/imagine-dragons") ``` ## 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\| \|------:\|---------:\|---:\| \|272\| -\| -\| '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/imagine-dragons") 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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Short-Answer-Feedback/saf_communication_networks_english	Short-Answer-Feedback	2023-03-31T11:46:04Z	364	6	[ "task_categories:text2text-generation", "annotations_creators:expert-generated", "language_creators:other", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "license:cc-by-4.0", "short answer feedback", "communication networks", "region:us" ]	[ "text2text-generation" ]	2022-11-10T21:22:13Z	--- pretty_name: SAF - Communication Networks - English annotations_creators: - expert-generated language: - en language_creators: - other multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original tags: - short answer feedback - communication networks task_categories: - text2text-generation dataset_info: features: - name: id dtype: string - name: question dtype: string - name: reference_answer dtype: string - name: provided_answer dtype: string - name: answer_feedback dtype: string - name: verification_feedback dtype: string - name: score dtype: float64 splits: - name: train num_bytes: 2363828 num_examples: 1700 - name: validation num_bytes: 592869 num_examples: 427 - name: test_unseen_answers num_bytes: 515669 num_examples: 375 - name: test_unseen_questions num_bytes: 777945 num_examples: 479 download_size: 941169 dataset_size: 4250311 license: cc-by-4.0 --- # Dataset Card for "saf_communication_networks_english" ## 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) - [Annotation process](#annotation-process) - [Additional Information](#additional-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Paper: [Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset](https://aclanthology.org/2022.acl-long.587) (Filighera et al., ACL 2022) ### Dataset Summary Short Answer Feedback (SAF) dataset is a short answer dataset introduced in [Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset](https://aclanthology.org/2022.acl-long.587) (Filighera et al., ACL 2022) as a way to remedy the lack of content-focused feedback datasets. This version of the dataset contains 31 English questions covering a range of college-level communication networks topics - while the original dataset presented in the paper is comprised of an assortment of both English and German short answer questions (with reference answers). Please refer to the [saf_micro_job_german](https://huggingface.co/datasets/Short-Answer-Feedback/saf_micro_job_german) dataset to examine the German subset of the original dataset. Furthermore, a similarly constructed SAF dataset (covering the German legal domain) can be found at [saf_legal_domain_german](https://huggingface.co/datasets/Short-Answer-Feedback/saf_legal_domain_german). ### Supported Tasks and Leaderboards - `short_answer_feedback`: The dataset can be used to train a Text2Text Generation model from HuggingFace transformers in order to generate automatic short answer feedback. ### Languages The questions, reference answers, provided answers and the answer feedback in the dataset are written in English. ## Dataset Structure ### Data Instances An example of an entry of the training split looks as follows. ``` { "id": "1", "question": "Is this a question?", "reference_answer": "Yes, that is a question.", "provided_answer": "I'm certain this is a question.", "answer_feedback": "The response is correct.", "verification_feedback": "Correct", "score": 1 } ``` ### Data Fields The data fields are the same among all splits. - `id`: a `string` feature (UUID4 in HEX format). - `question`: a `string` feature representing a question. - `reference_answer`: a `string` feature representing a reference answer to the question. - `provided_answer`: a `string` feature representing an answer that was provided for a particular question. - `answer_feedback`: a `string` feature representing the feedback given to the provided answers. - `verification_feedback`: a `string` feature representing an automatic labeling of the score. It can be `Correct` (`score` = maximum points achievable), `Incorrect` (`score` = 0) or `Partially correct` (all intermediate scores). - `score`: a `float64` feature representing the score given to the provided answer. For most questions it ranges from 0 to 1. ### Data Splits The dataset is comprised of four data splits. - `train`: used for training, contains a set of questions and the provided answers to them. - `validation`: used for validation, contains a set of questions and the provided answers to them (derived from the original training set defined in the paper). - `test_unseen_answers`: used for testing, contains unseen answers to the questions present in the `train` split. - `test_unseen_questions`: used for testing, contains unseen questions that do not appear in the `train` split. \| Split \|train\|validation\|test_unseen_answers\|test_unseen_questions\| \|-------------------\|----:\|---------:\|------------------:\|--------------------:\| \|Number of instances\| 1700\| 427\| 375\| 479\| ## Dataset Creation ### Annotation Process Two graduate students who had completed the communication networks course were selected to evaluate the answers, and both of them underwent a general annotation guideline training (supervised by a Psychology doctoral student with prior work in the field of feedback). After the training, the annotators individually provided feedback to the answers following an agreed upon scoring rubric and the general annotation guideline. The individually annotated answer files were then combined into a cohesive gold standard after discussing and solving possible disagreements. ## Additional Information ### Citation Information ``` @inproceedings{filighera-etal-2022-answer, title = "Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset", author = "Filighera, Anna and Parihar, Siddharth and Steuer, Tim and Meuser, Tobias and Ochs, Sebastian", booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", month = may, year = "2022", address = "Dublin, Ireland", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.acl-long.587", doi = "10.18653/v1/2022.acl-long.587", pages = "8577--8591", } ``` ### Contributions Thanks to [@JohnnyBoy2103](https://github.com/JohnnyBoy2103) for adding this dataset.	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amttl	null	2023-01-25T14:26:23Z	363	1	[ "task_categories:token-classification", "task_ids:parsing", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:zh", "license:mit", "region:us" ]	[ "token-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - found language: - zh license: - mit multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - token-classification task_ids: - parsing pretty_name: AMTTL dataset_info: features: - name: id dtype: string - name: tokens sequence: string - name: tags sequence: class_label: names: '0': B '1': I '2': E '3': S config_name: amttl splits: - name: train num_bytes: 1132212 num_examples: 3063 - name: validation num_bytes: 324374 num_examples: 822 - name: test num_bytes: 328525 num_examples: 908 download_size: 685534 dataset_size: 1785111 --- # Dataset Card for AMTTL ## 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: [Github](https://github.com/adapt-sjtu/AMTTL/tree/master/medical_data) - Repository: [Github](https://github.com/adapt-sjtu/AMTTL/tree/master/medical_data) - Paper: [Aclweb](http://aclweb.org/anthology/C18-1307) - 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 ```bibtex @inproceedings{xing2018adaptive, title={Adaptive multi-task transfer learning for Chinese word segmentation in medical text}, author={Xing, Junjie and Zhu, Kenny and Zhang, Shaodian}, booktitle={Proceedings of the 27th International Conference on Computational Linguistics}, pages={3619--3630}, year={2018} } ``` ### Contributions Thanks to [@JetRunner](https://github.com/JetRunner) for adding this dataset.	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limit	null	2022-11-18T20:18:52Z	363	3	[ "task_categories:token-classification", "task_categories:text-classification", "task_ids:multi-class-classification", "task_ids:named-entity-recognition", "annotations_creators:crowdsourced", "language_creators:found", "multilinguality:monolingual", "size_categories:10K<n<100K", "source_datasets:extended\|net-activities-captions", "source_datasets:original", "language:en", "license:cc-by-sa-4.0", "region:us" ]	[ "token-classification", "text-classification" ]	2022-03-02T23:29:22Z	--- annotations_creators: - crowdsourced language_creators: - found language: - en license: - cc-by-sa-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - extended\|net-activities-captions - original task_categories: - token-classification - text-classification task_ids: - multi-class-classification - named-entity-recognition paperswithcode_id: limit pretty_name: LiMiT dataset_info: features: - name: id dtype: int32 - name: sentence dtype: string - name: motion dtype: string - name: motion_entities list: - name: entity dtype: string - name: start_index dtype: int32 splits: - name: train num_bytes: 3064208 num_examples: 23559 - name: test num_bytes: 139742 num_examples: 1000 download_size: 4214925 dataset_size: 3203950 --- # Dataset Card for LiMiT ## 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: [github](https://github.com/ilmgut/limit_dataset) - Paper: [LiMiT: The Literal Motion in Text Dataset](https://www.aclweb.org/anthology/2020.findings-emnlp.88/) - Leaderboard: N/A - Point of Contact: [More Information Needed] ### Dataset Summary Motion recognition is one of the basic cognitive capabilities of many life forms, yet identifying motion of physical entities in natural language have not been explored extensively and empirically. Literal-Motion-in-Text (LiMiT) dataset, is a large human-annotated collection of English text sentences describing physical occurrence of motion, with annotated physical entities in motion. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages The text in the dataset is in English (`en`). ## Dataset Structure ### Data Instances Example of one instance in the dataset ``` { "id": 0, "motion": "yes", "motion_entities": [ { "entity": "little boy", "start_index": 2 }, { "entity": "ball", "start_index": 30 } ], "sentence": " A little boy holding a yellow ball walks by." } ``` ### Data Fields - `id`: intger index of the example - `motion`: indicates whether the sentence is literal motion i.e. describes the movement of a physical entity or not - `motion_entities`: A `list` of `dicts` with following keys - `entity`: the extracted entity in motion - `start_index`: index in the sentence for the first char of the entity text ### Data Splits The dataset is split into a `train`, and `test` split with the following sizes: \| \| train \| validation \| \| ----- \|------:\|-----------:\| \| Number of examples \| 23559 \| 1000 \| ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### 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 ``` @inproceedings{manotas-etal-2020-limit, title = "{L}i{M}i{T}: The Literal Motion in Text Dataset", author = "Manotas, Irene and Vo, Ngoc Phuoc An and Sheinin, Vadim", booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.findings-emnlp.88", doi = "10.18653/v1/2020.findings-emnlp.88", pages = "991--1000", abstract = "Motion recognition is one of the basic cognitive capabilities of many life forms, yet identifying motion of physical entities in natural language have not been explored extensively and empirically. We present the Literal-Motion-in-Text (LiMiT) dataset, a large human-annotated collection of English text sentences describing physical occurrence of motion, with annotated physical entities in motion. We describe the annotation process for the dataset, analyze its scale and diversity, and report results of several baseline models. We also present future research directions and applications of the LiMiT dataset and share it publicly as a new resource for the research community.", } ``` ### Contributions Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.	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DDSC/reddit-da	DDSC	2022-10-27T11:00:42Z	363	2	[ "task_categories:text-generation", "task_ids:language-modeling", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:1M<n<10M", "source_datasets:original", "language:da", "license:mit", "region:us" ]	[ "text-generation" ]	2022-03-02T23:29:22Z	--- annotations_creators: - no-annotation language_creators: - found language: - da license: - mit multilinguality: - monolingual size_categories: - 1M<n<10M source_datasets: - original task_categories: - text-generation task_ids: - language-modeling pretty_name: Reddit-da --- # Dataset Card for SQuAD-da ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Contributions](#contributions) ### Dataset Summary This dataset consists of 1,908,887 Danish posts from Reddit. These are from [this Reddit dump](https://files.pushshift.io/reddit/) and have been filtered using [this script](https://github.com/NBAiLab/notram/blob/master/corpus_generation_scripts/lang_detect_reddit.py), which uses FastText to detect the Danish posts. ### Supported Tasks and Leaderboards This dataset is suitable for language modelling. ### Languages This dataset is in Danish. ## Dataset Structure ### Data Instances Every entry in the dataset contains short Reddit comments in Danish, along with a unique ID. ### Data Fields An entry in the dataset consists of the following fields: - `id` (`str`): A unique identifier. - `text` (`str`): A short Reddit comment. ## Additional Information ### Licensing Information The dataset is released under the MIT license. ### Contributions Thanks to [@saattrupdan](https://github.com/saattrupdan) for adding this dataset to the Hugging Face Hub.	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huggingartists/slava-marlow	huggingartists	2022-10-25T09:45:03Z	363	0	[ "language:en", "huggingartists", "lyrics", "region:us" ]	null	2022-03-02T23:29:22Z	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/slava-marlow" ## 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: 0.471147 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/e308b1bc9eeb159ecfa9d807d715f095.1000x1000x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/slava-marlow"> <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">SLAVA MARLOW</div> <a href="https://genius.com/artists/slava-marlow"> <div style="text-align: center; font-size: 14px;">@slava-marlow</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/slava-marlow). ### 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/slava-marlow") ``` ## 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\| \|------:\|---------:\|---:\| \|249\| -\| -\| '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/slava-marlow") 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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polinaeterna/amazon_us_reviews	polinaeterna	2023-06-09T17:56:17Z	362	1	[ "task_categories:summarization", "task_categories:text-generation", "task_categories:fill-mask", "task_categories:text-classification", "task_ids:text-scoring", "task_ids:language-modeling", "task_ids:masked-language-modeling", "task_ids:sentiment-classification", "task_ids:sentiment-scoring", "task_ids:topic-classification", "annotations_creators:no-annotation", "language_creators:found", "multilinguality:monolingual", "size_categories:100M<n<1B", "source_datasets:original", "language:en", "license:other", "region:us" ]	[ "summarization", "text-generation", "fill-mask", "text-classification" ]	2023-06-09T17:56:16Z	--- annotations_creators: - no-annotation language_creators: - found language: - en license: - other multilinguality: - monolingual size_categories: - 100M<n<1B source_datasets: - original task_categories: - summarization - text-generation - fill-mask - text-classification task_ids: - text-scoring - language-modeling - masked-language-modeling - sentiment-classification - sentiment-scoring - topic-classification pretty_name: Amazon US Reviews dataset_info: - config_name: Books_v1_01 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 6997552259 num_examples: 6106719 download_size: 2692708591 dataset_size: 6997552259 - config_name: Watches_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 458976082 num_examples: 960872 download_size: 162973819 dataset_size: 458976082 - config_name: Personal_Care_Appliances_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 49036547 num_examples: 85981 download_size: 17634794 dataset_size: 49036547 - config_name: Mobile_Electronics_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 63293377 num_examples: 104975 download_size: 22870508 dataset_size: 63293377 - config_name: Digital_Video_Games_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 80176851 num_examples: 145431 download_size: 27442648 dataset_size: 80176851 - config_name: Digital_Software_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 58782931 num_examples: 102084 download_size: 18997559 dataset_size: 58782931 - config_name: Major_Appliances_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 67642424 num_examples: 96901 download_size: 24359816 dataset_size: 67642424 - config_name: Gift_Card_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 47188062 num_examples: 149086 download_size: 12134676 dataset_size: 47188062 - config_name: Video_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 356264426 num_examples: 380604 download_size: 138929896 dataset_size: 356264426 - config_name: Luggage_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 167354173 num_examples: 348657 download_size: 60320191 dataset_size: 167354173 - config_name: Software_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 266020595 num_examples: 341931 download_size: 94010685 dataset_size: 266020595 - config_name: Video_Games_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1291054668 num_examples: 1785997 download_size: 475199894 dataset_size: 1291054668 - config_name: Furniture_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 405212374 num_examples: 792113 download_size: 148982796 dataset_size: 405212374 - config_name: Musical_Instruments_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 518908568 num_examples: 904765 download_size: 193389086 dataset_size: 518908568 - config_name: Digital_Music_Purchase_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 710546079 num_examples: 1688884 download_size: 253570168 dataset_size: 710546079 - config_name: Books_v1_02 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 3387034903 num_examples: 3105520 download_size: 1329539135 dataset_size: 3387034903 - config_name: Home_Entertainment_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 534333848 num_examples: 705889 download_size: 193168458 dataset_size: 534333848 - config_name: Grocery_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1072289473 num_examples: 2402458 download_size: 401337166 dataset_size: 1072289473 - config_name: Outdoors_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1172986088 num_examples: 2302401 download_size: 448963100 dataset_size: 1172986088 - config_name: Pet_Products_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1355659812 num_examples: 2643619 download_size: 515815253 dataset_size: 1355659812 - config_name: Video_DVD_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 3953234561 num_examples: 5069140 download_size: 1512355451 dataset_size: 3953234561 - config_name: Apparel_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2256558450 num_examples: 5906333 download_size: 648641286 dataset_size: 2256558450 - config_name: PC_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 3982684438 num_examples: 6908554 download_size: 1512903923 dataset_size: 3982684438 - config_name: Tools_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 872273119 num_examples: 1741100 download_size: 333782939 dataset_size: 872273119 - config_name: Jewelry_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 703275869 num_examples: 1767753 download_size: 247022254 dataset_size: 703275869 - config_name: Baby_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 956952590 num_examples: 1752932 download_size: 357392893 dataset_size: 956952590 - config_name: Home_Improvement_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1329688315 num_examples: 2634781 download_size: 503339178 dataset_size: 1329688315 - config_name: Camera_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1187101912 num_examples: 1801974 download_size: 442653086 dataset_size: 1187101912 - config_name: Lawn_and_Garden_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1272255987 num_examples: 2557288 download_size: 486772662 dataset_size: 1272255987 - config_name: Office_Products_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1370685534 num_examples: 2642434 download_size: 512323500 dataset_size: 1370685534 - config_name: Electronics_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1875406721 num_examples: 3093869 download_size: 698828243 dataset_size: 1875406721 - config_name: Automotive_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1520191087 num_examples: 3514942 download_size: 582145299 dataset_size: 1520191087 - config_name: Digital_Video_Download_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1484214187 num_examples: 4057147 download_size: 506979922 dataset_size: 1484214187 - config_name: Mobile_Apps_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1627857158 num_examples: 5033376 download_size: 557959415 dataset_size: 1627857158 - config_name: Shoes_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 1781283508 num_examples: 4366916 download_size: 642255314 dataset_size: 1781283508 - config_name: Toys_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2197820069 num_examples: 4864249 download_size: 838451398 dataset_size: 2197820069 - config_name: Sports_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2241349145 num_examples: 4850360 download_size: 872478735 dataset_size: 2241349145 - config_name: Kitchen_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2453735305 num_examples: 4880466 download_size: 930744854 dataset_size: 2453735305 - config_name: Beauty_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2399292506 num_examples: 5115666 download_size: 914070021 dataset_size: 2399292506 - config_name: Music_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 3900138839 num_examples: 4751577 download_size: 1521994296 dataset_size: 3900138839 - config_name: Health_Personal_Care_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2679427491 num_examples: 5331449 download_size: 1011180212 dataset_size: 2679427491 - config_name: Digital_Ebook_Purchase_v1_01 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 3470453859 num_examples: 5101693 download_size: 1294879074 dataset_size: 3470453859 - config_name: Home_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 2796680249 num_examples: 6221559 download_size: 1081002012 dataset_size: 2796680249 - config_name: Wireless_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 4633213433 num_examples: 9002021 download_size: 1704713674 dataset_size: 4633213433 - config_name: Books_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 7197687124 num_examples: 10319090 download_size: 2740337188 dataset_size: 7197687124 - config_name: Digital_Ebook_Purchase_v1_00 features: - name: marketplace dtype: string - name: customer_id dtype: string - name: review_id dtype: string - name: product_id dtype: string - name: product_parent dtype: string - name: product_title dtype: string - name: product_category dtype: string - name: star_rating dtype: int32 - name: helpful_votes dtype: int32 - name: total_votes dtype: int32 - name: vine dtype: class_label: names: '0': 'N' '1': 'Y' - name: verified_purchase dtype: class_label: names: '0': 'N' '1': 'Y' - name: review_headline dtype: string - name: review_body dtype: string - name: review_date dtype: string splits: - name: train num_bytes: 7302303804 num_examples: 12520722 download_size: 2689739299 dataset_size: 7302303804 duplicated_from: amazon_us_reviews --- # Dataset Card for "amazon_us_reviews" ## 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://s3.amazonaws.com/amazon-reviews-pds/readme.html](https://s3.amazonaws.com/amazon-reviews-pds/readme.html) - Repository: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - 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 downloaded dataset files: 32377.29 MB - Size of the generated dataset: 82820.19 MB - Total amount of disk used: 115197.49 MB ### Dataset Summary Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews. Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters). Each Dataset contains the following columns : marketplace - 2 letter country code of the marketplace where the review was written. customer_id - Random identifier that can be used to aggregate reviews written by a single author. review_id - The unique ID of the review. product_id - The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id. product_parent - Random identifier that can be used to aggregate reviews for the same product. product_title - Title of the product. product_category - Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). star_rating - The 1-5 star rating of the review. helpful_votes - Number of helpful votes. total_votes - Number of total votes the review received. vine - Review was written as part of the Vine program. verified_purchase - The review is on a verified purchase. review_headline - The title of the review. review_body - The review text. review_date - The date the review was written. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### Apparel_v1_00 - Size of downloaded dataset files: 648.64 MB - Size of the generated dataset: 2254.36 MB - Total amount of disk used: 2903.00 MB An example of 'train' looks as follows. ``` { "customer_id": "45223824", "helpful_votes": 0, "marketplace": "US", "product_category": "Apparel", "product_id": "B016PUU3VO", "product_parent": "893588059", "product_title": "Fruit of the Loom Boys' A-Shirt (Pack of 4)", "review_body": "I ordered the same size as I ordered last time, and these shirts were much larger than the previous order. They were also about 6 inches longer. It was like they sent men's shirts instead of boys' shirts. I'll be returning these...", "review_date": "2015-01-01", "review_headline": "Sizes not correct, too big overall and WAY too long", "review_id": "R1N3Z13931J3O9", "star_rating": 2, "total_votes": 0, "verified_purchase": 1, "vine": 0 } ``` #### Automotive_v1_00 - Size of downloaded dataset files: 582.15 MB - Size of the generated dataset: 1518.88 MB - Total amount of disk used: 2101.03 MB An example of 'train' looks as follows. ``` { "customer_id": "16825098", "helpful_votes": 0, "marketplace": "US", "product_category": "Automotive", "product_id": "B000E4PCGE", "product_parent": "694793259", "product_title": "00-03 NISSAN SENTRA MIRROR RH (PASSENGER SIDE), Power, Non-Heated (2000 00 2001 01 2002 02 2003 03) NS35ER 963015M000", "review_body": "Product was as described, new and a great look. Only bad thing is that one of the screws was stripped so I couldn't tighten all three.", "review_date": "2015-08-31", "review_headline": "new and a great look. Only bad thing is that one of ...", "review_id": "R2RUIDUMDKG7P", "star_rating": 3, "total_votes": 0, "verified_purchase": 1, "vine": 0 } ``` #### Baby_v1_00 - Size of downloaded dataset files: 357.40 MB - Size of the generated dataset: 956.30 MB - Total amount of disk used: 1313.70 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "customer_id": "23299101", "helpful_votes": 2, "marketplace": "US", "product_category": "Baby", "product_id": "B00SN6F9NG", "product_parent": "3470998", "product_title": "Rhoost Nail Clipper for Baby - Ergonomically Designed and Easy to Use Baby Nail Clipper, Natural Wooden Bamboo - Baby Health and Personal Care Kits", "review_body": "\"This is an absolute MUST item to have! I was scared to death to clip my baby's nails. I tried other baby nail clippers and th...", "review_date": "2015-08-31", "review_headline": "If fits so comfortably in my hand and I feel like I have ...", "review_id": "R2DRL5NRODVQ3Z", "star_rating": 5, "total_votes": 2, "verified_purchase": 1, "vine": 0 } ``` #### Beauty_v1_00 - Size of downloaded dataset files: 914.08 MB - Size of the generated dataset: 2397.39 MB - Total amount of disk used: 3311.47 MB An example of 'train' looks as follows. ``` { "customer_id": "24655453", "helpful_votes": 1, "marketplace": "US", "product_category": "Beauty", "product_id": "B00SAQ9DZY", "product_parent": "292127037", "product_title": "12 New, High Quality, Amber 2 ml (5/8 Dram) Glass Bottles, with Orifice Reducer and Black Cap.", "review_body": "These are great for small mixtures for EO's, especially for traveling. I only gave this 4 stars because of the orifice reducer. The hole is so small it is hard to get the oil out. Just needs to be slightly bigger.", "review_date": "2015-08-31", "review_headline": "Good Product", "review_id": "R2A30ALEGLMCGN", "star_rating": 4, "total_votes": 1, "verified_purchase": 1, "vine": 0 } ``` #### Books_v1_00 - Size of downloaded dataset files: 2740.34 MB - Size of the generated dataset: 7193.86 MB - Total amount of disk used: 9934.20 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "customer_id": "49735028", "helpful_votes": 0, "marketplace": "US", "product_category": "Books", "product_id": "0664254969", "product_parent": "248307276", "product_title": "Presbyterian Creeds: A Guide to the Book of Confessions", "review_body": "\"The Presbyterian Book of Confessions contains multiple Creeds for use by the denomination. This guidebook helps he lay person t...", "review_date": "2015-08-31", "review_headline": "The Presbyterian Book of Confessions contains multiple Creeds for use ...", "review_id": "R2G519UREHRO8M", "star_rating": 3, "total_votes": 1, "verified_purchase": 1, "vine": 0 } ``` ### Data Fields The data fields are the same among all splits. #### Apparel_v1_00 - `marketplace`: a `string` feature. - `customer_id`: a `string` feature. - `review_id`: a `string` feature. - `product_id`: a `string` feature. - `product_parent`: a `string` feature. - `product_title`: a `string` feature. - `product_category`: a `string` feature. - `star_rating`: a `int32` feature. - `helpful_votes`: a `int32` feature. - `total_votes`: a `int32` feature. - `vine`: a classification label, with possible values including `Y` (0), `N` (1). - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1). - `review_headline`: a `string` feature. - `review_body`: a `string` feature. - `review_date`: a `string` feature. #### Automotive_v1_00 - `marketplace`: a `string` feature. - `customer_id`: a `string` feature. - `review_id`: a `string` feature. - `product_id`: a `string` feature. - `product_parent`: a `string` feature. - `product_title`: a `string` feature. - `product_category`: a `string` feature. - `star_rating`: a `int32` feature. - `helpful_votes`: a `int32` feature. - `total_votes`: a `int32` feature. - `vine`: a classification label, with possible values including `Y` (0), `N` (1). - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1). - `review_headline`: a `string` feature. - `review_body`: a `string` feature. - `review_date`: a `string` feature. #### Baby_v1_00 - `marketplace`: a `string` feature. - `customer_id`: a `string` feature. - `review_id`: a `string` feature. - `product_id`: a `string` feature. - `product_parent`: a `string` feature. - `product_title`: a `string` feature. - `product_category`: a `string` feature. - `star_rating`: a `int32` feature. - `helpful_votes`: a `int32` feature. - `total_votes`: a `int32` feature. - `vine`: a classification label, with possible values including `Y` (0), `N` (1). - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1). - `review_headline`: a `string` feature. - `review_body`: a `string` feature. - `review_date`: a `string` feature. #### Beauty_v1_00 - `marketplace`: a `string` feature. - `customer_id`: a `string` feature. - `review_id`: a `string` feature. - `product_id`: a `string` feature. - `product_parent`: a `string` feature. - `product_title`: a `string` feature. - `product_category`: a `string` feature. - `star_rating`: a `int32` feature. - `helpful_votes`: a `int32` feature. - `total_votes`: a `int32` feature. - `vine`: a classification label, with possible values including `Y` (0), `N` (1). - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1). - `review_headline`: a `string` feature. - `review_body`: a `string` feature. - `review_date`: a `string` feature. #### Books_v1_00 - `marketplace`: a `string` feature. - `customer_id`: a `string` feature. - `review_id`: a `string` feature. - `product_id`: a `string` feature. - `product_parent`: a `string` feature. - `product_title`: a `string` feature. - `product_category`: a `string` feature. - `star_rating`: a `int32` feature. - `helpful_votes`: a `int32` feature. - `total_votes`: a `int32` feature. - `vine`: a classification label, with possible values including `Y` (0), `N` (1). - `verified_purchase`: a classification label, with possible values including `Y` (0), `N` (1). - `review_headline`: a `string` feature. - `review_body`: a `string` feature. - `review_date`: a `string` feature. ### Data Splits \| name \| train \| \|----------------\|-------:\| \|Apparel_v1_00 \| 5906333\| \|Automotive_v1_00 \| 3514942\| \|Baby_v1_00 \| 1752932\| \|Beauty_v1_00 \| 5115666\| \|Books_v1_00 \| 10319090\| \|Books_v1_01 \| 6106719\| \|Books_v1_02 \| 3105520\| \|Camera_v1_00 \| 1801974\| \|Digital_Ebook_Purchase_v1_00 \| 12520722\| \|Digital_Ebook_Purchase_v1_01 \| 5101693\| \|Digital_Music_Purchase_v1_00 \| 1688884\| \|Digital_Software_v1_00 \| 102084\| \|Digital_Video_Download_v1_00 \| 4057147\| \|Digital_Video_Games_v1_00 \| 145431\| \|Electronics_v1_00 \| 3093869\| \|Furniture_v1_00 \| 792113\| \|Gift_Card_v1_00 \| 149086\| \|Grocery_v1_00 \| 2402458\| \|Health_Personal_Care_v1_00 \| 5331449\| \|Home_Entertainment_v1_00 \| 705889\| \|Home_Improvement_v1_00 \| 2634781\| \|Home_v1_00 \| 6221559\| \|Jewelry_v1_00 \| 1767753\| \|Kitchen_v1_00 \| 4880466\| \|Lawn_and_Garden_v1_00 \| 2557288\| \|Luggage_v1_00 \| 348657\| \|Major_Appliances_v1_00 \| 96901\| \|Mobile_Apps_v1_00 \| 5033376\| \|Mobile_Electronics_v1_00 \| 104975\| \|Music_v1_00 \| 4751577\| \|Musical_Instruments_v1_00 \| 904765\| \|Office_Products_v1_00 \| 2642434\| \|Outdoors_v1_00 \| 2302401\| \|PC_v1_00 \| 6908554\| \|Personal_Care_Appliances_v1_00 \| 85981\| \|Pet_Products_v1_00 \| 2643619\| \|Shoes_v1_00 \| 4366916\| \|Software_v1_00 \| 341931\| \|Sports_v1_00 \| 4850360\| \|Tools_v1_00 \| 1741100\| \|Toys_v1_00 \| 4864249\| \|Video_DVD_v1_00 \| 5069140\| \|Video_Games_v1_00 \| 1785997\| \|Video_v1_00 \| 380604\| \|Watches_v1_00 \| 960872\| \|Wireless_v1_00 \| 9002021\| ## 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 https://s3.amazonaws.com/amazon-reviews-pds/LICENSE.txt By accessing the Amazon Customer Reviews Library ("Reviews Library"), you agree that the Reviews Library is an Amazon Service subject to the [Amazon.com Conditions of Use](https://www.amazon.com/gp/help/customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088) and you agree to be bound by them, with the following additional conditions: In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Library for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Library or its contents, including use of the Reviews Library for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Library with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Library. If you violate any of the foregoing conditions, your license to access and use the Reviews Library will automatically terminate without prejudice to any of the other rights or remedies Amazon may have. ### Citation Information No citation information. ### Contributions Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset.	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severo/flores_101	severo	2022-10-27T08:37:36Z	362	1	[ "task_categories:text-generation", "task_categories:translation", "annotations_creators:found", "language_creators:expert-generated", "multilinguality:multilingual", "multilinguality:translation", "size_categories:unknown", "source_datasets:extended\|flores", "language:af", "language:am", "language:ar", "language:hy", "language:as", "language:ast", "language:az", "language:be", "language:bn", "language:bs", "language:bg", "language:my", "language:ca", "language:ceb", "language:zho", "language:hr", "language:cs", "language:da", "language:nl", "language:en", "language:et", "language:tl", "language:fi", "language:fr", "language:ff", "language:gl", "language:lg", "language:ka", "language:de", "language:el", "language:gu", "language:ha", "language:he", "language:hi", "language:hu", "language:is", "language:ig", "language:id", "language:ga", "language:it", "language:ja", "language:jv", "language:kea", "language:kam", "language:kn", "language:kk", "language:km", "language:ko", "language:ky", "language:lo", "language:lv", "language:ln", "language:lt", "language:luo", "language:lb", "language:mk", "language:ms", "language:ml", "language:mt", "language:mi", "language:mr", "language:mn", "language:ne", "language:ns", "language:no", "language:ny", "language:oc", "language:or", "language:om", "language:ps", "language:fa", "language:pl", "language:pt", "language:pa", "language:ro", "language:ru", "language:sr", "language:sn", "language:sd", "language:sk", "language:sl", "language:so", "language:ku", "language:es", "language:sw", "language:sv", "language:tg", "language:ta", "language:te", "language:th", "language:tr", "language:uk", "language:umb", "language:ur", "language:uz", "language:vi", "language:cy", "language:wo", "language:xh", "language:yo", "language:zu", "license:cc-by-sa-4.0", "conditional-text-generation", "arxiv:2106.03193", "region:us" ]	[ "text-generation", "translation" ]	2023-06-20T21:40:23Z	--- annotations_creators: - found language_creators: - expert-generated language: - af - am - ar - hy - as - ast - az - be - bn - bs - bg - my - ca - ceb - zho - hr - cs - da - nl - en - et - tl - fi - fr - ff - gl - lg - ka - de - el - gu - ha - he - hi - hu - is - ig - id - ga - it - ja - jv - kea - kam - kn - kk - km - ko - ky - lo - lv - ln - lt - luo - lb - mk - ms - ml - mt - mi - mr - mn - ne - ns - 'no' - ny - oc - or - om - ps - fa - pl - pt - pa - ro - ru - sr - sn - sd - sk - sl - so - ku - es - sw - sv - tg - ta - te - th - tr - uk - umb - ur - uz - vi - cy - wo - xh - yo - zu license: - cc-by-sa-4.0 multilinguality: - multilingual - translation size_categories: - unknown source_datasets: - extended\|flores task_categories: - text-generation - translation task_ids: [] paperswithcode_id: flores pretty_name: flores101 tags: - conditional-text-generation --- # Dataset Card for Flores 101 ## Table of Contents - [Dataset Card for Flores 101](#dataset-card-for-flores-101) - [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) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - Home: [WMT](http://www.statmt.org/wmt21/large-scale-multilingual-translation-task.html) - Repository: [Github](https://github.com/facebookresearch/flores) - Blogpost: [FAIR](https://ai.facebook.com/blog/the-flores-101-data-set-helping-build-better-translation-systems-around-the-world) - Paper: [Arxiv](https://arxiv.org/abs/2106.03193) - Point of Contact: [[email protected]](mailto:[email protected]) - Leaderboard [Dynabench](https://dynabench.org/flores/Flores%20MT%20Evaluation%20(FULL)) ### Dataset Summary FLORES is a benchmark dataset for machine translation between English and low-resource languages. Abstract from the original paper: > One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks. Current evaluation benchmarks either lack good coverage of low-resource languages, consider only restricted domains, or are low quality because they are constructed using semi-automatic procedures. In this work, we introduce the FLORES evaluation benchmark, consisting of 3001 sentences extracted from English Wikipedia and covering a variety of different topics and domains. These sentences have been translated in 101 languages by professional translators through a carefully controlled process. The resulting dataset enables better assessment of model quality on the long tail of low-resource languages, including the evaluation of many-to-many multilingual translation systems, as all translations are multilingually aligned. By publicly releasing such a high-quality and high-coverage dataset, we hope to foster progress in the machine translation community and beyond. Disclaimer: The Flores-101 dataset is hosted by the Facebook and licensed under the [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/). ### Supported Tasks and Leaderboards #### Multilingual Machine Translation Refer to the [Dynabench leaderboard](https://dynabench.org/flores/Flores%20MT%20Evaluation%20(FULL)) for additional details on model evaluation on FLORES-101 in the context of the WMT2021 shared task on [Large-Scale Multilingual Machine Translation](http://www.statmt.org/wmt21/large-scale-multilingual-translation-task.html). ### Languages The dataset contains parallel sentences for 101 languages, as mentioned in the original [Github](https://github.com/facebookresearch/flores/blob/master/README.md) page for the project. Languages are identified with the ISO 639-3 code (e.g. `eng`, `fra`, `rus`) as in the original dataset. New:* Use the configuration `all` to access the full set of parallel sentences for all the available languages in a single command. ## Dataset Structure ### Data Instances A sample from the `dev` split for the Russian language (`rus` config) is provided below. All configurations have the same structure, and all sentences are aligned across configurations and splits. ```python { 'id': 1, 'sentence': 'В понедельник ученые из Медицинской школы Стэнфордского университета объявили об изобретении нового диагностического инструмента, который может сортировать клетки по их типу; это маленький чип, который можно напечатать, используя стандартный струйный принтер примерно за 1 цент США.', 'URL': 'https://en.wikinews.org/wiki/Scientists_say_new_medical_diagnostic_chip_can_sort_cells_anywhere_with_an_inkjet', 'domain': 'wikinews', 'topic': 'health', 'has_image': 0, 'has_hyperlink': 0 } ``` The text is provided as-in the original dataset, without further preprocessing or tokenization. ### Data Fields - `id`: Row number for the data entry, starting at 1. - `sentence`: The full sentence in the specific language. - `URL`: The URL for the English article from which the sentence was extracted. - `domain`: The domain of the sentence. - `topic`: The topic of the sentence. - `has_image`: Whether the original article contains an image. - `has_hyperlink`: Whether the sentence contains a hyperlink. ### Data Splits \| config\| `dev`\| `devtest`\| \|-----------------:\|-----:\|---------:\| \|all configurations\| 997\| 1012:\| ### Dataset Creation Please refer to the original article [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) for additional information on dataset creation. ## Additional Information ### Dataset Curators The original authors of FLORES-101 are the curators of the original dataset. For problems or updates on this 🤗 Datasets version, please contact [[email protected]](mailto:[email protected]). ### Licensing Information Licensed with Creative Commons Attribution Share Alike 4.0. License available [here](https://creativecommons.org/licenses/by-sa/4.0/). ### Citation Information Please cite the authors if you use these corpora in your work: ```bibtex @inproceedings{flores101, title={The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation}, author={Goyal, Naman and Gao, Cynthia and Chaudhary, Vishrav and Chen, Peng-Jen and Wenzek, Guillaume and Ju, Da and Krishnan, Sanjana and Ranzato, Marc'Aurelio and Guzm\'{a}n, Francisco and Fan, Angela}, journal={arXiv preprint arXiv:2106.03193}, year={2021} } ```	[ -0.2978246510028839, -0.5223730206489563, 0.34789714217185974, 0.5215265154838562, -0.0169824231415987, -0.185068279504776, -0.6274722814559937, -0.24975430965423584, 0.365675151348114, 0.06680816411972046, -0.6470465660095215, -0.7625761032104492, -0.5026506185531616, 0.710382342338562, -0.33098262548446655, 1.0779703855514526, -0.2678394615650177, 0.07080140709877014, -0.28841903805732727, -0.42918652296066284, 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strombergnlp/pypi-20230724	strombergnlp	2023-07-25T03:12:55Z	362	0	[ "license:apache-2.0", "region:us" ]	null	2023-07-25T03:12:35Z	--- license: apache-2.0 ---	[ -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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open-llm-leaderboard/details__fsx_shared-falcon-180B_2100	open-llm-leaderboard	2023-09-11T14:39:05Z	362	0	[ "region:us" ]	null	2023-09-11T11:31:21Z	--- pretty_name: Evaluation run of _fsx_shared-falcon-180B_2100 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [_fsx_shared-falcon-180B_2100](https://huggingface.co/_fsx_shared-falcon-180B_2100)\ \ 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__fsx_shared-falcon-180B_2100\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-11T14:38:41.751680](https://huggingface.co/datasets/open-llm-leaderboard/details__fsx_shared-falcon-180B_2100/blob/main/results_2023-09-11T14-38-41.751680.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\": 0.7013964110418803,\n\ \ \"acc_stderr\": 0.030702382053756392,\n \"acc_norm\": 0.7050725401087311,\n\ \ \"acc_norm_stderr\": 0.030672281323978368,\n \"mc1\": 0.3157894736842105,\n\ \ \"mc1_stderr\": 0.016272287957916916,\n \"mc2\": 0.4692416686068408,\n\ \ \"mc2_stderr\": 0.014108890624515822\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6544368600682594,\n \"acc_stderr\": 0.013896938461145677,\n\ \ \"acc_norm\": 0.6860068259385665,\n \"acc_norm_stderr\": 0.013562691224726288\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7061342362079267,\n\ \ \"acc_stderr\": 0.004546002255456772,\n \"acc_norm\": 0.8914558852818164,\n\ \ \"acc_norm_stderr\": 0.003104306434972476\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7763157894736842,\n \"acc_stderr\": 0.033911609343436046,\n\ \ \"acc_norm\": 0.7763157894736842,\n \"acc_norm_stderr\": 0.033911609343436046\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.74,\n\ \ \"acc_stderr\": 0.04408440022768081,\n \"acc_norm\": 0.74,\n \ \ \"acc_norm_stderr\": 0.04408440022768081\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7471698113207547,\n \"acc_stderr\": 0.026749899771241214,\n\ \ \"acc_norm\": 0.7471698113207547,\n \"acc_norm_stderr\": 0.026749899771241214\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.031164899666948607,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.031164899666948607\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.59,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\ : 0.59,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness\|hendrycksTest-college_mathematics\|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_medicine\|5\": {\n \"acc\": 0.7283236994219653,\n\ \ \"acc_stderr\": 0.03391750322321659,\n \"acc_norm\": 0.7283236994219653,\n\ \ \"acc_norm_stderr\": 0.03391750322321659\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082635,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082635\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.83,\n \"acc_stderr\": 0.03775251680686371,\n \"acc_norm\": 0.83,\n\ \ \"acc_norm_stderr\": 0.03775251680686371\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6595744680851063,\n \"acc_stderr\": 0.030976692998534446,\n\ \ \"acc_norm\": 0.6595744680851063,\n \"acc_norm_stderr\": 0.030976692998534446\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.04692008381368909,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.04692008381368909\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.04013124195424386,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.04013124195424386\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4947089947089947,\n \"acc_stderr\": 0.02574986828855657,\n \"\ acc_norm\": 0.4947089947089947,\n \"acc_norm_stderr\": 0.02574986828855657\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness\|hendrycksTest-global_facts\|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-high_school_biology\|5\": {\n \"acc\": 0.8451612903225807,\n\ \ \"acc_stderr\": 0.020579287326583227,\n \"acc_norm\": 0.8451612903225807,\n\ \ \"acc_norm_stderr\": 0.020579287326583227\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5615763546798029,\n \"acc_stderr\": 0.03491207857486519,\n\ \ \"acc_norm\": 0.5615763546798029,\n \"acc_norm_stderr\": 0.03491207857486519\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\ : 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8242424242424242,\n \"acc_stderr\": 0.02972094300622445,\n\ \ \"acc_norm\": 0.8242424242424242,\n \"acc_norm_stderr\": 0.02972094300622445\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8787878787878788,\n \"acc_stderr\": 0.023253157951942084,\n \"\ acc_norm\": 0.8787878787878788,\n \"acc_norm_stderr\": 0.023253157951942084\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9430051813471503,\n \"acc_stderr\": 0.016731085293607548,\n\ \ \"acc_norm\": 0.9430051813471503,\n \"acc_norm_stderr\": 0.016731085293607548\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.7333333333333333,\n \"acc_stderr\": 0.022421273612923714,\n\ \ \"acc_norm\": 0.7333333333333333,\n \"acc_norm_stderr\": 0.022421273612923714\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.35185185185185186,\n \"acc_stderr\": 0.029116617606083025,\n \ \ \"acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.029116617606083025\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.7815126050420168,\n \"acc_stderr\": 0.026841514322958938,\n\ \ \"acc_norm\": 0.7815126050420168,\n \"acc_norm_stderr\": 0.026841514322958938\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.4304635761589404,\n \"acc_stderr\": 0.04042809961395634,\n \"\ acc_norm\": 0.4304635761589404,\n \"acc_norm_stderr\": 0.04042809961395634\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8935779816513761,\n \"acc_stderr\": 0.013221554674594372,\n \"\ acc_norm\": 0.8935779816513761,\n \"acc_norm_stderr\": 0.013221554674594372\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.6064814814814815,\n \"acc_stderr\": 0.03331747876370312,\n \"\ acc_norm\": 0.6064814814814815,\n \"acc_norm_stderr\": 0.03331747876370312\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9166666666666666,\n \"acc_stderr\": 0.019398452135813902,\n \"\ acc_norm\": 0.9166666666666666,\n \"acc_norm_stderr\": 0.019398452135813902\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8987341772151899,\n \"acc_stderr\": 0.019637720526065494,\n \ \ \"acc_norm\": 0.8987341772151899,\n \"acc_norm_stderr\": 0.019637720526065494\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7847533632286996,\n\ \ \"acc_stderr\": 0.027584066602208274,\n \"acc_norm\": 0.7847533632286996,\n\ \ \"acc_norm_stderr\": 0.027584066602208274\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8320610687022901,\n \"acc_stderr\": 0.032785485373431386,\n\ \ \"acc_norm\": 0.8320610687022901,\n \"acc_norm_stderr\": 0.032785485373431386\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8099173553719008,\n \"acc_stderr\": 0.03581796951709282,\n \"\ acc_norm\": 0.8099173553719008,\n \"acc_norm_stderr\": 0.03581796951709282\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8240740740740741,\n\ \ \"acc_stderr\": 0.03680918141673881,\n \"acc_norm\": 0.8240740740740741,\n\ \ \"acc_norm_stderr\": 0.03680918141673881\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.803680981595092,\n \"acc_stderr\": 0.031207970394709218,\n\ \ \"acc_norm\": 0.803680981595092,\n \"acc_norm_stderr\": 0.031207970394709218\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5982142857142857,\n\ \ \"acc_stderr\": 0.04653333146973646,\n \"acc_norm\": 0.5982142857142857,\n\ \ \"acc_norm_stderr\": 0.04653333146973646\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\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\": 0.8,\n \"acc_stderr\": 0.04020151261036846,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n\ \ \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.879948914431673,\n\ \ \"acc_stderr\": 0.011622736692041256,\n \"acc_norm\": 0.879948914431673,\n\ \ \"acc_norm_stderr\": 0.011622736692041256\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7890173410404624,\n \"acc_stderr\": 0.021966309947043114,\n\ \ \"acc_norm\": 0.7890173410404624,\n \"acc_norm_stderr\": 0.021966309947043114\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.5072625698324023,\n\ \ \"acc_stderr\": 0.0167207374051795,\n \"acc_norm\": 0.5072625698324023,\n\ \ \"acc_norm_stderr\": 0.0167207374051795\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7810457516339869,\n \"acc_stderr\": 0.02367908986180772,\n\ \ \"acc_norm\": 0.7810457516339869,\n \"acc_norm_stderr\": 0.02367908986180772\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.797427652733119,\n\ \ \"acc_stderr\": 0.022827317491059682,\n \"acc_norm\": 0.797427652733119,\n\ \ \"acc_norm_stderr\": 0.022827317491059682\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8179012345679012,\n \"acc_stderr\": 0.021473491834808355,\n\ \ \"acc_norm\": 0.8179012345679012,\n \"acc_norm_stderr\": 0.021473491834808355\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5567375886524822,\n \"acc_stderr\": 0.029634838473766006,\n \ \ \"acc_norm\": 0.5567375886524822,\n \"acc_norm_stderr\": 0.029634838473766006\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5501955671447197,\n\ \ \"acc_stderr\": 0.01270572149856497,\n \"acc_norm\": 0.5501955671447197,\n\ \ \"acc_norm_stderr\": 0.01270572149856497\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7463235294117647,\n \"acc_stderr\": 0.026431329870789534,\n\ \ \"acc_norm\": 0.7463235294117647,\n \"acc_norm_stderr\": 0.026431329870789534\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7532679738562091,\n \"acc_stderr\": 0.0174408203674025,\n \ \ \"acc_norm\": 0.7532679738562091,\n \"acc_norm_stderr\": 0.0174408203674025\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7636363636363637,\n\ \ \"acc_stderr\": 0.040693063197213775,\n \"acc_norm\": 0.7636363636363637,\n\ \ \"acc_norm_stderr\": 0.040693063197213775\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7673469387755102,\n \"acc_stderr\": 0.027049257915896182,\n\ \ \"acc_norm\": 0.7673469387755102,\n \"acc_norm_stderr\": 0.027049257915896182\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.900497512437811,\n\ \ \"acc_stderr\": 0.021166216304659386,\n \"acc_norm\": 0.900497512437811,\n\ \ \"acc_norm_stderr\": 0.021166216304659386\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.92,\n \"acc_stderr\": 0.0272659924344291,\n \ \ \"acc_norm\": 0.92,\n \"acc_norm_stderr\": 0.0272659924344291\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.038695433234721015,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.038695433234721015\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.027097290118070813,\n\ \ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.027097290118070813\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3157894736842105,\n\ \ \"mc1_stderr\": 0.016272287957916916,\n \"mc2\": 0.4692416686068408,\n\ \ \"mc2_stderr\": 0.014108890624515822\n }\n}\n```" repo_url: https://huggingface.co/_fsx_shared-falcon-180B_2100 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_11T14_38_41.751680 path: - '/details_harness\|arc:challenge\|25_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hellaswag\|10_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T14-38-41.751680.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-11T14-38-41.751680.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_11T11_31_21.074717 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-11T11-31-21.074717.parquet' - split: 2023_09_11T14_38_41.751680 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-11T14-38-41.751680.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-11T14-38-41.751680.parquet' - config_name: results data_files: - split: 2023_09_11T11_31_21.074717 path: - results_2023-09-11T11-31-21.074717.parquet - split: 2023_09_11T14_38_41.751680 path: - results_2023-09-11T14-38-41.751680.parquet - split: latest path: - results_2023-09-11T14-38-41.751680.parquet --- # Dataset Card for Evaluation run of _fsx_shared-falcon-180B_2100 ## Dataset Description - Homepage: - Repository: https://huggingface.co/_fsx_shared-falcon-180B_2100 - 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 [_fsx_shared-falcon-180B_2100](https://huggingface.co/_fsx_shared-falcon-180B_2100) 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__fsx_shared-falcon-180B_2100", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-11T14:38:41.751680](https://huggingface.co/datasets/open-llm-leaderboard/details__fsx_shared-falcon-180B_2100/blob/main/results_2023-09-11T14-38-41.751680.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": 0.7013964110418803, "acc_stderr": 0.030702382053756392, "acc_norm": 0.7050725401087311, "acc_norm_stderr": 0.030672281323978368, "mc1": 0.3157894736842105, "mc1_stderr": 0.016272287957916916, "mc2": 0.4692416686068408, "mc2_stderr": 0.014108890624515822 }, "harness\|arc:challenge\|25": { "acc": 0.6544368600682594, "acc_stderr": 0.013896938461145677, "acc_norm": 0.6860068259385665, "acc_norm_stderr": 0.013562691224726288 }, "harness\|hellaswag\|10": { "acc": 0.7061342362079267, "acc_stderr": 0.004546002255456772, "acc_norm": 0.8914558852818164, "acc_norm_stderr": 0.003104306434972476 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7763157894736842, "acc_stderr": 0.033911609343436046, "acc_norm": 0.7763157894736842, "acc_norm_stderr": 0.033911609343436046 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.74, "acc_stderr": 0.04408440022768081, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768081 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7471698113207547, "acc_stderr": 0.026749899771241214, "acc_norm": 0.7471698113207547, "acc_norm_stderr": 0.026749899771241214 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.031164899666948607, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.031164899666948607 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.7283236994219653, "acc_stderr": 0.03391750322321659, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.03391750322321659 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082635, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082635 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6595744680851063, "acc_stderr": 0.030976692998534446, "acc_norm": 0.6595744680851063, "acc_norm_stderr": 0.030976692998534446 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6344827586206897, "acc_stderr": 0.04013124195424386, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.04013124195424386 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4947089947089947, "acc_stderr": 0.02574986828855657, "acc_norm": 0.4947089947089947, "acc_norm_stderr": 0.02574986828855657 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8451612903225807, "acc_stderr": 0.020579287326583227, "acc_norm": 0.8451612903225807, "acc_norm_stderr": 0.020579287326583227 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5615763546798029, "acc_stderr": 0.03491207857486519, "acc_norm": 0.5615763546798029, "acc_norm_stderr": 0.03491207857486519 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8242424242424242, "acc_stderr": 0.02972094300622445, "acc_norm": 0.8242424242424242, "acc_norm_stderr": 0.02972094300622445 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8787878787878788, "acc_stderr": 0.023253157951942084, "acc_norm": 0.8787878787878788, "acc_norm_stderr": 0.023253157951942084 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9430051813471503, "acc_stderr": 0.016731085293607548, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.016731085293607548 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.7333333333333333, "acc_stderr": 0.022421273612923714, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.022421273612923714 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.35185185185185186, "acc_stderr": 0.029116617606083025, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.029116617606083025 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.7815126050420168, "acc_stderr": 0.026841514322958938, "acc_norm": 0.7815126050420168, "acc_norm_stderr": 0.026841514322958938 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.4304635761589404, "acc_stderr": 0.04042809961395634, "acc_norm": 0.4304635761589404, "acc_norm_stderr": 0.04042809961395634 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8935779816513761, "acc_stderr": 0.013221554674594372, "acc_norm": 0.8935779816513761, "acc_norm_stderr": 0.013221554674594372 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.6064814814814815, "acc_stderr": 0.03331747876370312, "acc_norm": 0.6064814814814815, "acc_norm_stderr": 0.03331747876370312 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9166666666666666, "acc_stderr": 0.019398452135813902, "acc_norm": 0.9166666666666666, "acc_norm_stderr": 0.019398452135813902 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8987341772151899, "acc_stderr": 0.019637720526065494, "acc_norm": 0.8987341772151899, "acc_norm_stderr": 0.019637720526065494 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7847533632286996, "acc_stderr": 0.027584066602208274, "acc_norm": 0.7847533632286996, "acc_norm_stderr": 0.027584066602208274 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8320610687022901, "acc_stderr": 0.032785485373431386, "acc_norm": 0.8320610687022901, "acc_norm_stderr": 0.032785485373431386 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8099173553719008, "acc_stderr": 0.03581796951709282, "acc_norm": 0.8099173553719008, "acc_norm_stderr": 0.03581796951709282 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8240740740740741, "acc_stderr": 0.03680918141673881, "acc_norm": 0.8240740740740741, "acc_norm_stderr": 0.03680918141673881 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.803680981595092, "acc_stderr": 0.031207970394709218, "acc_norm": 0.803680981595092, "acc_norm_stderr": 0.031207970394709218 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.5982142857142857, "acc_stderr": 0.04653333146973646, "acc_norm": 0.5982142857142857, "acc_norm_stderr": 0.04653333146973646 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8446601941747572, "acc_stderr": 0.03586594738573974, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.03586594738573974 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9017094017094017, "acc_stderr": 0.019503444900757567, "acc_norm": 0.9017094017094017, "acc_norm_stderr": 0.019503444900757567 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.879948914431673, "acc_stderr": 0.011622736692041256, "acc_norm": 0.879948914431673, "acc_norm_stderr": 0.011622736692041256 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7890173410404624, "acc_stderr": 0.021966309947043114, "acc_norm": 0.7890173410404624, "acc_norm_stderr": 0.021966309947043114 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.5072625698324023, "acc_stderr": 0.0167207374051795, "acc_norm": 0.5072625698324023, "acc_norm_stderr": 0.0167207374051795 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7810457516339869, "acc_stderr": 0.02367908986180772, "acc_norm": 0.7810457516339869, "acc_norm_stderr": 0.02367908986180772 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.797427652733119, "acc_stderr": 0.022827317491059682, "acc_norm": 0.797427652733119, "acc_norm_stderr": 0.022827317491059682 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8179012345679012, "acc_stderr": 0.021473491834808355, "acc_norm": 0.8179012345679012, "acc_norm_stderr": 0.021473491834808355 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5567375886524822, "acc_stderr": 0.029634838473766006, "acc_norm": 0.5567375886524822, "acc_norm_stderr": 0.029634838473766006 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.5501955671447197, "acc_stderr": 0.01270572149856497, "acc_norm": 0.5501955671447197, "acc_norm_stderr": 0.01270572149856497 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7463235294117647, "acc_stderr": 0.026431329870789534, "acc_norm": 0.7463235294117647, "acc_norm_stderr": 0.026431329870789534 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.7532679738562091, "acc_stderr": 0.0174408203674025, "acc_norm": 0.7532679738562091, "acc_norm_stderr": 0.0174408203674025 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7636363636363637, "acc_stderr": 0.040693063197213775, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.040693063197213775 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7673469387755102, "acc_stderr": 0.027049257915896182, "acc_norm": 0.7673469387755102, "acc_norm_stderr": 0.027049257915896182 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.900497512437811, "acc_stderr": 0.021166216304659386, "acc_norm": 0.900497512437811, "acc_norm_stderr": 0.021166216304659386 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.92, "acc_stderr": 0.0272659924344291, "acc_norm": 0.92, "acc_norm_stderr": 0.0272659924344291 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5542168674698795, "acc_stderr": 0.038695433234721015, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.038695433234721015 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8538011695906432, "acc_stderr": 0.027097290118070813, "acc_norm": 0.8538011695906432, "acc_norm_stderr": 0.027097290118070813 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3157894736842105, "mc1_stderr": 0.016272287957916916, "mc2": 0.4692416686068408, "mc2_stderr": 0.014108890624515822 } } ``` ### 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]	[ -0.7535825371742249, -0.853639543056488, 0.295215368270874, 0.23794740438461304, -0.12532752752304077, -0.010423021391034126, 0.04499358311295509, -0.21341760456562042, 0.6064900755882263, -0.044408999383449554, -0.5259858965873718, -0.6675886511802673, -0.4769115447998047, 0.2665550112724304, -0.07879649847745895, 0.8127728700637817, -0.20428912341594696, -0.16251271963119507, 0.049003347754478455, -0.03395044803619385, -0.2181154191493988, -0.3551614284515381, -0.5056218504905701, 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