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 |
|---|---|---|---|---|---|---|---|---|---|
d0rj/curation-corpus | d0rj | 2023-06-13T13:25:32Z | 361 | 1 | [
"task_categories:summarization",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"news",
"summarization",
"region:us"
]
| [
"summarization"
]
| 2023-06-12T19:22:21Z | ---
dataset_info:
features:
- name: title
dtype: string
- name: summary
dtype: string
- name: url
dtype: string
- name: date
dtype: string
- name: article_content
dtype: string
splits:
- name: train
num_bytes: 127948910
num_examples: 30455
download_size: 76620775
dataset_size: 127948910
license: cc-by-4.0
task_categories:
- summarization
multilinguality:
- monolingual
language:
- en
source_datasets:
- original
tags:
- news
- summarization
pretty_name: Curation Corpus for Abstractive Text Summarisation
paperswithcode_id: curation-corpus
size_categories:
- 10K<n<100K
---
# curation-corpus
## Dataset Description
- **Homepage:** [https://github.com/CurationCorp/curation-corpus](https://github.com/CurationCorp/curation-corpus)
- **Repository:** [https://github.com/CurationCorp/curation-corpus](https://github.com/CurationCorp/curation-corpus)
## Source
Data from [this official repo](https://github.com/CurationCorp/curation-corpus) with downloaded news articles content.
## Citation
```
@misc{curationcorpusbase:2020,
title={Curation Corpus Base},
author={Curation},
year={2020}
}
``` | [
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|
vwxyzjn/summarize_from_feedback_oai_preprocessing_pythia | vwxyzjn | 2023-11-02T19:31:21Z | 361 | 0 | [
"region:us"
]
| null | 2023-11-02T19:31:02Z | ---
dataset_info:
features:
- name: info
struct:
- name: id
dtype: string
- name: post
dtype: string
- name: title
dtype: string
- name: subreddit
dtype: string
- name: site
dtype: string
- name: article
dtype: string
- name: summaries
list:
- name: text
dtype: string
- name: policy
dtype: string
- name: note
dtype: string
- name: choice
dtype: int32
- name: worker
dtype: string
- name: batch
dtype: string
- name: split
dtype: string
- name: extra
struct:
- name: confidence
dtype: int32
- name: query_token
sequence: int64
- name: query
dtype: string
- name: response0
dtype: string
- name: response0_token
sequence: int64
- name: response1
dtype: string
- name: response1_token
sequence: int64
splits:
- name: train
num_bytes: 782558889
num_examples: 92858
- name: validation
num_bytes: 734266349
num_examples: 86086
download_size: 124011801
dataset_size: 1516825238
---
# Dataset Card for "summarize_from_feedback_oai_preprocessing_pythia"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
bing_coronavirus_query_set | null | 2022-11-03T16:30:54Z | 360 | 0 | [
"task_categories:text-classification",
"task_ids:intent-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:other",
"region:us"
]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- intent-classification
paperswithcode_id: null
pretty_name: BingCoronavirusQuerySet
dataset_info:
features:
- name: id
dtype: int32
- name: Date
dtype: string
- name: Query
dtype: string
- name: IsImplicitIntent
dtype: string
- name: Country
dtype: string
- name: PopularityScore
dtype: int32
config_name: country_2020-09-01_2020-09-30
splits:
- name: train
num_bytes: 22052706
num_examples: 317856
download_size: 16351450
dataset_size: 22052706
---
# Dataset Card for BingCoronavirusQuerySet
## 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:** None
- **Repository:** https://github.com/microsoft/BingCoronavirusQuerySet
- **Paper:** Nonewww
- **Leaderboard:** [More Information Needed]
- **Point of Contact:** [More Information Needed]
### Dataset Summary
Please note that you can specify the start and end date of the data. You can get start and end dates from here: https://github.com/microsoft/BingCoronavirusQuerySet/tree/master/data/2020
example:
```
load_dataset("bing_coronavirus_query_set", queries_by="state", start_date="2020-09-01", end_date="2020-09-30")
```
You can also load the data by country by using `queries_by="country"`.
### 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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|
covid_qa_castorini | null | 2022-11-03T16:30:54Z | 360 | 0 | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:2004.11339",
"region:us"
]
| [
"question-answering"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: covidqa
pretty_name: CovidQaCastorini
dataset_info:
- config_name: covid_qa_deepset
features:
- name: document_id
dtype: int32
- name: context
dtype: string
- name: question
dtype: string
- name: is_impossible
dtype: bool
- name: id
dtype: int32
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: train
num_bytes: 65151262
num_examples: 2019
download_size: 4418117
dataset_size: 65151262
- config_name: covidqa
features:
- name: category_name
dtype: string
- name: question_query
dtype: string
- name: keyword_query
dtype: string
- name: answers
sequence:
- name: id
dtype: string
- name: title
dtype: string
- name: exact_answer
dtype: string
splits:
- name: train
num_bytes: 33757
num_examples: 27
download_size: 51438
dataset_size: 33757
- config_name: covid_qa_castorini
features:
- name: category_name
dtype: string
- name: question_query
dtype: string
- name: keyword_query
dtype: string
- name: answers
sequence:
- name: id
dtype: string
- name: title
dtype: string
- name: exact_answer
dtype: string
splits:
- name: train
num_bytes: 33757
num_examples: 27
download_size: 51438
dataset_size: 33757
---
# Dataset Card for [covid_qa_castorini]
## 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:** http://covidqa.ai
- **Repository:** https://github.com/castorini/pygaggle
- **Paper:** https://arxiv.org/abs/2004.11339
- **Point of Contact:** [Castorini research group @UWaterloo](https://github.com/castorini/)
### Dataset Summary
CovidQA is a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered
from Kaggle’s COVID-19 Open Research Dataset Challenge.
The dataset comprises 156 question-article pairs with 27 questions (topics) and 85 unique articles.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
The text in the dataset is in English.
## Dataset Structure
### Data Instances
**What do the instances that comprise the dataset represent?**
Each represents a question, a context (document passage from the CORD19 dataset) and an answer.
**How many instances are there in total?**
**What data does each instance consist of?**
Each instance is a query (natural language question and keyword-based), a set of answers, and a document id with its title associated with each answer.
[More Information Needed]
### Data Fields
The data was annotated in SQuAD style fashion, where each row contains:
* **question_query**: Natural language question query
* **keyword_query**: Keyword-based query
* **category_name**: Category in which the queries are part of
* **answers**: List of answers
* **id**: The document ID the answer is found on
* **title**: Title of the document of the answer
* **exact_answer**: Text (string) of the exact answer
### Data Splits
**data/kaggle-lit-review-0.2.json**: 156 question-article pairs with 27 questions (topics) and 85 unique articles from
CORD-19.
[More Information Needed]
## Dataset Creation
The dataset aims to help for guiding research until more substantial evaluation resources become available. Being a smaller dataset,
it can be helpful for evaluating the zero-shot or transfer capabilities of existing models on topics specifically related to COVID-19.
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
[More Information Needed]
### Annotations
Five of the co-authors participated in this annotation effort, applying the aforementioned approach, with one lead
annotator responsible for approving topics and answering technical questions from the other annotators. Two annotators are
undergraduate students majoring in computer science, one is a science alumna, another is a computer science professor,
and the lead annotator is a graduate student in computer science—all affiliated with the University of Waterloo.
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
The dataset was intended as a stopgap measure for guiding research until more substantial evaluation resources become available.
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
While this dataset, comprising 124 question–article pairs as of the present version 0.1 release, does not have sufficient
examples for supervised machine learning, it can be helpful for evaluating the zero-shot or transfer capabilities
of existing models on topics specifically related to COVID-19.
## Additional Information
The listed authors in the homepage are maintaining/supporting the dataset.
### Dataset Curators
[More Information Needed]
### Licensing Information
The dataset is licensed under the [Apache License 2.0](https://github.com/castorini/pygaggle/blob/master/LICENSE).
### Citation Information
```
@article{tang2020rapidly,
title={Rapidly Bootstrapping a Question Answering Dataset for COVID-19},
author={Tang, Raphael and Nogueira, Rodrigo and Zhang, Edwin and Gupta, Nikhil and Cam, Phuong and Cho, Kyunghyun and Lin, Jimmy},
journal={arXiv preprint arXiv:2004.11339},
year={2020}
}
```
### Contributions
Thanks to [@olinguyen](https://github.com/olinguyen) for adding this dataset. | [
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|
unitxt/data | unitxt | 2023-12-03T18:09:53Z | 360 | 0 | [
"license:apache-2.0",
"region:us"
]
| null | 2023-07-10T12:11:50Z | ---
license: apache-2.0
---
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|
antolin/python-150_interduplication | antolin | 2023-11-10T11:57:59Z | 360 | 2 | [
"region:us"
]
| null | 2023-09-05T11:21:06Z | ---
dataset_info:
features:
- name: id_within_dataset
dtype: int64
- name: snippet
dtype: string
- name: tokens
sequence: string
- name: nl
dtype: string
- name: split_within_dataset
dtype: string
- name: is_duplicated
dtype: bool
splits:
- name: train
num_bytes: 41621821.20269596
num_examples: 40842
- name: test
num_bytes: 13915723.238891663
num_examples: 13655
- name: valid
num_bytes: 13864768.55841238
num_examples: 13605
download_size: 30588162
dataset_size: 69402313.0
---
# Dataset Card for "python-150_interduplication"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
natyou/freshqa_10_06 | natyou | 2023-10-11T15:26:10Z | 360 | 0 | [
"region:us"
]
| null | 2023-10-11T15:23:22Z | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: dev
path: data/dev-*
dataset_info:
features:
- name: id
dtype: int64
- name: split
dtype: string
- name: question
dtype: string
- name: effective_year
dtype: string
- name: next_review
dtype: string
- name: false_premise
dtype: bool
- name: num_hops
dtype: string
- name: fact_type
dtype: string
- name: source
dtype: string
- name: answer_0
dtype: string
- name: answer_1
dtype: string
- name: answer_2
dtype: string
- name: answer_3
dtype: string
- name: answer_4
dtype: string
- name: answer_5
dtype: string
- name: answer_6
dtype: string
- name: answer_7
dtype: string
- name: answer_8
dtype: string
- name: answer_9
dtype: string
- name: note
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: test
num_bytes: 192891
num_examples: 500
- name: dev
num_bytes: 39203
num_examples: 100
download_size: 129810
dataset_size: 232094
---
# Dataset Card for "freshqa_10_06"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
vgoldberg/longform_article_summarization | vgoldberg | 2023-10-11T19:36:28Z | 360 | 3 | [
"task_categories:summarization",
"size_categories:100K<n<1M",
"language:en",
"license:apache-2.0",
"region:us"
]
| [
"summarization"
]
| 2023-10-11T17:01:42Z | ---
language:
- en
license: apache-2.0
size_categories:
- 100K<n<1M
task_categories:
- summarization
pretty_name: Long-Form Article Summarization Dataset
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: text
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 2243293725
num_examples: 105256
download_size: 880664627
dataset_size: 2243293725
---
**Dataset Name:** Long-Form Article Summarization Dataset
**Description:**
The Long-Form Article Summarization Dataset is meticulously curated for the purpose of fine-tuning Natural Language Processing (NLP) models specifically tailored for summarization tasks. It is a rich collection of long-form articles that have been carefully condensed and summarized. The dataset provides a diverse range of topics and writing styles, making it an invaluable resource for researchers and practitioners working on summarization algorithms and applications.
**Data Sources:**
1. **Billsum:** This dataset includes summaries of U.S. congressional and state bills, providing insights into legislative documents.
2. **Scientific Papers:** A collection of scientific papers covering various disciplines, enabling a deep dive into research-oriented content.
3. **Multi_news:** This dataset incorporates news articles, offering a blend of current events and journalistic writing styles.
4. **CCDV/Pubmed-Summarization:** Focused on biomedical literature, this dataset contains summaries from Pubmed articles, offering specialized content related to the field of medicine and life sciences.
**Data Combination:**
The Long-Form Article Summarization Dataset is an amalgamation of the above-mentioned datasets. By combining these diverse sources, the dataset achieves a comprehensive coverage of topics, styles, and domains. This fusion enhances the dataset's versatility and applicability across a wide array of domains, making it a valuable asset for NLP research and development.
**Data Preprocessing:**
To ensure equal representation of unique domains and to manage the scale of the dataset, large datasets were down-sampled. This meticulous preprocessing step guarantees that each domain is adequately represented, promoting a balanced and unbiased training environment for NLP models.
**Intended Use:**
This dataset is specifically designed for fine-tuning NLP models focused on summarization tasks. Researchers and developers can utilize this dataset to train and evaluate their algorithms for generating concise and informative summaries from long-form articles. The dataset's diverse origins and careful preprocessing make it an ideal choice for enhancing the summarization capabilities of NLP models.
**Access:**
The Long-Form Article Summarization Dataset is available for research purposes and can be accessed through authorized channels. Researchers and developers interested in using this dataset are encouraged to adhere to ethical guidelines and data usage policies governing the respective sources.
**Citation:**
Researchers and practitioners are expected to cite the original sources of the datasets used in this amalgamation, namely "Billsum," "Scientific Papers," "Multi_news," and "CCDV/Pubmed-Summarization," in addition to acknowledging the creation of the Long-Form Article Summarization Dataset in their publications and research outputs.
This dataset card provides an overview of the Long-Form Article Summarization Dataset, outlining its sources, preprocessing methods, intended use, and access guidelines, ensuring transparent and responsible utilization of the valuable data it encapsulates.
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|
hate_speech_portuguese | null | 2023-11-24T10:27:25Z | 359 | 2 | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pt",
"license:unknown",
"hate-speech-detection",
"region:us"
]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
pretty_name: HateSpeechPortuguese
tags:
- hate-speech-detection
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': no-hate
'1': hate
- name: hatespeech_G1
dtype: string
- name: annotator_G1
dtype: string
- name: hatespeech_G2
dtype: string
- name: annotator_G2
dtype: string
- name: hatespeech_G3
dtype: string
- name: annotator_G3
dtype: string
splits:
- name: train
num_bytes: 826130
num_examples: 5670
download_size: 763846
dataset_size: 826130
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
- **Repository:** https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
- **Paper:** https://www.aclweb.org/anthology/W19-3510/
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').
### 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
```
@inproceedings{fortuna-etal-2019-hierarchically,
title = "A Hierarchically-Labeled {P}ortuguese Hate Speech Dataset",
author = "Fortuna, Paula and
Rocha da Silva, Jo{\~a}o and
Soler-Company, Juan and
Wanner, Leo and
Nunes, S{\'e}rgio",
editor = "Roberts, Sarah T. and
Tetreault, Joel and
Prabhakaran, Vinodkumar and
Waseem, Zeerak",
booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-3510",
doi = "10.18653/v1/W19-3510",
pages = "94--104",
}
```
### Contributions
Thanks to [@hugoabonizio](https://github.com/hugoabonizio) for adding this dataset. | [
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|
ScandEval/dane-mini | ScandEval | 2023-07-05T09:40:02Z | 359 | 0 | [
"task_categories:token-classification",
"size_categories:1K<n<10K",
"language:da",
"license:cc-by-sa-4.0",
"region:us"
]
| [
"token-classification"
]
| 2022-06-14T18:20:34Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: tokens
sequence: string
- name: labels
sequence: string
splits:
- name: train
num_bytes: 355712
num_examples: 1024
- name: test
num_bytes: 747809
num_examples: 2048
- name: val
num_bytes: 92001
num_examples: 256
download_size: 532720
dataset_size: 1195522
license: cc-by-sa-4.0
task_categories:
- token-classification
language:
- da
size_categories:
- 1K<n<10K
---
# Dataset Card for "dane-mini"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
dennlinger/klexikon | dennlinger | 2022-10-25T15:03:56Z | 358 | 6 | [
"task_categories:summarization",
"task_categories:text2text-generation",
"task_ids:text-simplification",
"annotations_creators:found",
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:de",
"license:cc-by-sa-4.0",
"conditional-text-generation",
"simplification",
"document-level",
"arxiv:2201.07198",
"region:us"
]
| [
"summarization",
"text2text-generation"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- found
- expert-generated
language_creators:
- found
- machine-generated
language:
- de
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- summarization
- text2text-generation
task_ids:
- text-simplification
paperswithcode_id: klexikon
pretty_name: Klexikon
tags:
- conditional-text-generation
- simplification
- document-level
---
# Dataset Card for the Klexikon Dataset
## Table of Contents
- [Version History](#version-history)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Version History
- **v0.3** (2022-09-01): Removing some five samples from the dataset due to duplication conflicts with other samples.
- **v0.2** (2022-02-28): Updated the files to no longer contain empty sections and removing otherwise empty lines at the end of files. Also removing lines with some sort of coordinate.
- **v0.1** (2022-01-19): Initial data release on Huggingface datasets.
## Dataset Description
- **Homepage:** [N/A]
- **Repository:** [Klexikon repository](https://github.com/dennlinger/klexikon)
- **Paper:** [Klexikon: A German Dataset for Joint Summarization and Simplification](https://arxiv.org/abs/2201.07198)
- **Leaderboard:** [N/A]
- **Point of Contact:** [Dennis Aumiller](mailto:[email protected])
### Dataset Summary
The Klexikon dataset is a German resource of document-aligned texts between German Wikipedia and the children's lexicon "Klexikon". The dataset was created for the purpose of joint text simplification and summarization, and contains almost 2900 aligned article pairs.
Notably, the children's articles use a simpler language than the original Wikipedia articles; this is in addition to a clear length discrepancy between the source (Wikipedia) and target (Klexikon) domain.
### Supported Tasks and Leaderboards
- `summarization`: The dataset can be used to train a model for summarization. In particular, it poses a harder challenge than some of the commonly used datasets (CNN/DailyMail), which tend to suffer from positional biases in the source text. This makes it very easy to generate high (ROUGE) scoring solutions, by simply taking the leading 3 sentences. Our dataset provides a more challenging extraction task, combined with the additional difficulty of finding lexically appropriate simplifications.
- `simplification`: While not currently supported by the HF task board, text simplification is concerned with the appropriate representation of a text for disadvantaged readers (e.g., children, language learners, dyslexic,...).
For scoring, we ran preliminary experiments based on [ROUGE](https://huggingface.co/metrics/rouge), however, we want to cautiously point out that ROUGE is incapable of accurately depicting simplification appropriateness.
We combined this with looking at Flesch readability scores, as implemented by [textstat](https://github.com/shivam5992/textstat).
Note that simplification metrics such as [SARI](https://huggingface.co/metrics/sari) are not applicable here, since they require sentence alignments, which we do not provide.
### Languages
The associated BCP-47 code is `de-DE`.
The text of the articles is in German. Klexikon articles are further undergoing a simple form of peer-review before publication, and aim to simplify language for 8-13 year old children. This means that the general expected text difficulty for Klexikon articles is lower than Wikipedia's entries.
## Dataset Structure
### Data Instances
One datapoint represents the Wikipedia text (`wiki_text`), as well as the Klexikon text (`klexikon_text`).
Sentences are separated by newlines for both datasets, and section headings are indicated by leading `==` (or `===` for subheadings, `====` for sub-subheading, etc.).
Further, it includes the `wiki_url` and `klexikon_url`, pointing to the respective source texts. Note that the original articles were extracted in April 2021, so re-crawling the texts yourself will likely change some content.
Lastly, we include a unique identifier `u_id` as well as the page title `title` of the Klexikon page.
Sample (abridged texts for clarity):
```
{
"u_id": 0,
"title": "ABBA",
"wiki_url": "https://de.wikipedia.org/wiki/ABBA",
"klexikon_url": "https://klexikon.zum.de/wiki/ABBA",
"wiki_sentences": [
"ABBA ist eine schwedische Popgruppe, die aus den damaligen Paaren Agnetha Fältskog und Björn Ulvaeus sowie Benny Andersson und Anni-Frid Lyngstad besteht und sich 1972 in Stockholm formierte.",
"Sie gehört mit rund 400 Millionen verkauften Tonträgern zu den erfolgreichsten Bands der Musikgeschichte.",
"Bis in die 1970er Jahre hatte es keine andere Band aus Schweden oder Skandinavien gegeben, der vergleichbare Erfolge gelungen waren.",
"Trotz amerikanischer und britischer Dominanz im Musikgeschäft gelang der Band ein internationaler Durchbruch.",
"Sie hat die Geschichte der Popmusik mitgeprägt.",
"Zu ihren bekanntesten Songs zählen Mamma Mia, Dancing Queen und The Winner Takes It All.",
"1982 beendeten die Gruppenmitglieder aufgrund privater Differenzen ihre musikalische Zusammenarbeit.",
"Seit 2016 arbeiten die vier Musiker wieder zusammen an neuer Musik, die 2021 erscheinen soll.",
],
"klexikon_sentences": [
"ABBA war eine Musikgruppe aus Schweden.",
"Ihre Musikrichtung war die Popmusik.",
"Der Name entstand aus den Anfangsbuchstaben der Vornamen der Mitglieder, Agnetha, Björn, Benny und Anni-Frid.",
"Benny Andersson und Björn Ulvaeus, die beiden Männer, schrieben die Lieder und spielten Klavier und Gitarre.",
"Anni-Frid Lyngstad und Agnetha Fältskog sangen."
]
},
```
### Data Fields
* `u_id` (`int`): A unique identifier for each document pair in the dataset. 0-2349 are reserved for training data, 2350-2623 for testing, and 2364-2897 for validation.
* `title` (`str`): Title of the Klexikon page for this sample.
* `wiki_url` (`str`): URL of the associated Wikipedia article. Notably, this is non-trivial, since we potentially have disambiguated pages, where the Wikipedia title is not exactly the same as the Klexikon one.
* `klexikon_url` (`str`): URL of the Klexikon article.
* `wiki_text` (`List[str]`): List of sentences of the Wikipedia article. We prepare a pre-split document with spacy's sentence splitting (model: `de_core_news_md`). Additionally, please note that we do not include page contents outside of `<p>` tags, which excludes lists, captions and images.
* `klexikon_text` (`List[str]`): List of sentences of the Klexikon article. We apply the same processing as for the Wikipedia texts.
### Data Splits
We provide a stratified split of the dataset, based on the length of the respective Wiki article/Klexikon article pair (according to number of sentences).
The x-axis represents the length of the Wikipedia article, and the y-axis the length of the Klexikon article.
We segment the coordinate systems into rectangles of shape `(100, 10)`, and randomly sample a split of 80/10/10 for training/validation/test from each rectangle to ensure stratification. In case of rectangles with less than 10 entries, we put all samples into training.
The final splits have the following size:
* 2350 samples for training
* 274 samples for validation
* 274 samples for testing
## Dataset Creation
### Curation Rationale
As previously described, the Klexikon resource was created as an attempt to bridge the two fields of text summarization and text simplification. Previous datasets suffer from either one or more of the following shortcomings:
* They primarily focus on input/output pairs of similar lengths, which does not reflect longer-form texts.
* Data exists primarily for English, and other languages are notoriously understudied.
* Alignments exist for sentence-level, but not document-level.
This dataset serves as a starting point to investigate the feasibility of end-to-end simplification systems for longer input documents.
### Source Data
#### Initial Data Collection and Normalization
Data was collected from [Klexikon](klexikon.zum.de), and afterwards aligned with corresponding texts from [German Wikipedia](de.wikipedia.org).
Specifically, the collection process was performed in April 2021, and 3145 articles could be extracted from Klexikon back then. Afterwards, we semi-automatically align the articles with Wikipedia, by looking up articles with the same title.
For articles that do not exactly match, we manually review their content, and decide to match to an appropriate substitute if the content can be matched by at least 66% of the Klexikon paragraphs.
Similarly, we proceed to manually review disambiguation pages on Wikipedia.
We extract only full-text content, excluding figures, captions, and list elements from the final text corpus, and only retain articles for which the respective Wikipedia document consists of at least 15 paragraphs after pre-processing.
#### Who are the source language producers?
The language producers are contributors to Klexikon and Wikipedia. No demographic information was available from the data sources.
### Annotations
#### Annotation process
Annotations were performed by manually reviewing the URLs of the ambiguous article pairs. No annotation platforms or existing tools were used in the process.
Otherwise, articles were matched based on the exact title.
#### Who are the annotators?
The manually aligned articles were reviewed by the dataset author (Dennis Aumiller).
### Personal and Sensitive Information
Since Klexikon and Wikipedia are public encyclopedias, no further personal or sensitive information is included. We did not investigate to what extent information about public figures is included in the dataset.
## Considerations for Using the Data
### Social Impact of Dataset
Accessibility on the web is still a big issue, particularly for disadvantaged readers.
This dataset has the potential to strengthen text simplification systems, which can improve the situation.
In terms of language coverage, this dataset also has a beneficial impact on the availability of German data.
Potential negative biases include the problems of automatically aligned articles. The alignments may never be 100% perfect, and can therefore cause mis-aligned articles (or associations), despite the best of our intentions.
### Discussion of Biases
We have not tested whether any particular bias towards a specific article *type* (i.e., "person", "city", etc.) exists.
Similarly, we attempted to present an unbiased (stratified) split for validation and test set, but given that we only cover around 2900 articles, it is possible that these articles represent a particular focal lense on the overall distribution of lexical content.
### Other Known Limitations
Since the articles were written independently of each other, it is not guaranteed that there exists an exact coverage of each sentence in the simplified article, which could also stem from the fact that sometimes Wikipedia pages have separate article pages for aspects (e.g., the city of "Aarhus" has a separate page for its art museum (ARoS). However, Klexikon lists content and description for ARoS on the page of the city itself.
## Additional Information
### Dataset Curators
The dataset was curated only by the author of this dataset, Dennis Aumiller.
### Licensing Information
Klexikon and Wikipedia make their textual contents available under the CC BY-SA license, which will be inherited for this dataset.
### Citation Information
If you use our dataset or associated code, please cite our paper:
```
@inproceedings{aumiller-gertz-2022-klexikon,
title = "Klexikon: A {G}erman Dataset for Joint Summarization and Simplification",
author = "Aumiller, Dennis and
Gertz, Michael",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.288",
pages = "2693--2701"
}
```
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|
rahular/itihasa | rahular | 2022-10-24T18:06:01Z | 358 | 4 | [
"task_categories:text2text-generation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:unknown",
"source_datasets:original",
"language:sa",
"language:en",
"license:apache-2.0",
"conditional-text-generation",
"region:us"
]
| [
"text2text-generation"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- sa
- en
license:
- apache-2.0
multilinguality:
- translation
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
pretty_name: Itihasa
metrics:
- bleu
- sacrebleu
- rouge
- ter
- chrF
tags:
- conditional-text-generation
---
# Itihāsa
Itihāsa is a Sanskrit-English translation corpus containing 93,000 Sanskrit shlokas and their English translations extracted from M. N. Dutt's seminal works on The Rāmāyana and The Mahābhārata. The paper which introduced this dataset can be found [here](https://aclanthology.org/2021.wat-1.22/).
This repository contains the randomized train, development, and test sets. The original extracted data can be found [here](https://github.com/rahular/itihasa/tree/gh-pages/res) in JSON format. If you just want to browse the data, you can go [here](http://rahular.com/itihasa/).
## Usage
```
>> from datasets import load_dataset
>> dataset = load_dataset("rahular/itihasa")
>> dataset
DatasetDict({
train: Dataset({
features: ['translation'],
num_rows: 75162
})
validation: Dataset({
features: ['translation'],
num_rows: 6149
})
test: Dataset({
features: ['translation'],
num_rows: 11722
})
})
>> dataset['train'][0]
{'translation': {'en': 'The ascetic Vālmīki asked Nārada, the best of sages and foremost of those conversant with words, ever engaged in austerities and Vedic studies.',
'sn': 'ॐ तपः स्वाध्यायनिरतं तपस्वी वाग्विदां वरम्। नारदं परिपप्रच्छ वाल्मीकिर्मुनिपुङ्गवम्॥'}}
```
## Citation
If you found this dataset to be useful, please consider citing the paper as follows:
```
@inproceedings{aralikatte-etal-2021-itihasa,
title = "Itihasa: A large-scale corpus for {S}anskrit to {E}nglish translation",
author = "Aralikatte, Rahul and
de Lhoneux, Miryam and
Kunchukuttan, Anoop and
S{\o}gaard, Anders",
booktitle = "Proceedings of the 8th Workshop on Asian Translation (WAT2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wat-1.22",
pages = "191--197",
abstract = "This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two Indian epics viz., The Ramayana and The Mahabharata. We first describe the motivation behind the curation of such a dataset and follow up with empirical analysis to bring out its nuances. We then benchmark the performance of standard translation models on this corpus and show that even state-of-the-art transformer architectures perform poorly, emphasizing the complexity of the dataset.",
}
``` | [
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|
mteb/biorxiv-clustering-p2p | mteb | 2022-09-27T19:15:27Z | 358 | 0 | [
"language:en",
"region:us"
]
| null | 2022-05-11T06:46:41Z | ---
language:
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|
open-llm-leaderboard/details_clibrain__Llama-2-7b-ft-instruct-es | open-llm-leaderboard | 2023-09-17T14:05:23Z | 358 | 0 | [
"region:us"
]
| null | 2023-08-18T00:00:44Z | ---
pretty_name: Evaluation run of clibrain/Llama-2-7b-ft-instruct-es
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [clibrain/Llama-2-7b-ft-instruct-es](https://huggingface.co/clibrain/Llama-2-7b-ft-instruct-es)\
\ 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_clibrain__Llama-2-7b-ft-instruct-es\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-17T14:05:09.748904](https://huggingface.co/datasets/open-llm-leaderboard/details_clibrain__Llama-2-7b-ft-instruct-es/blob/main/results_2023-09-17T14-05-09.748904.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\": 0.00037786091964606556,\n \"f1\": 0.059617239932886215,\n\
\ \"f1_stderr\": 0.0013507073733013888,\n \"acc\": 0.4045158699907191,\n\
\ \"acc_stderr\": 0.009256588130982506\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.001363255033557047,\n \"em_stderr\": 0.00037786091964606556,\n\
\ \"f1\": 0.059617239932886215,\n \"f1_stderr\": 0.0013507073733013888\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.05686125852918878,\n \
\ \"acc_stderr\": 0.006378790242099664\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7521704814522494,\n \"acc_stderr\": 0.01213438601986535\n\
\ }\n}\n```"
repo_url: https://huggingface.co/clibrain/Llama-2-7b-ft-instruct-es
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_09T22_51_22.839971
path:
- '**/details_harness|arc:challenge|25_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T14_05_09.748904
path:
- '**/details_harness|drop|3_2023-09-17T14-05-09.748904.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T14-05-09.748904.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T14_05_09.748904
path:
- '**/details_harness|gsm8k|5_2023-09-17T14-05-09.748904.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T14-05-09.748904.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hellaswag|10_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T22:51:22.839971.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T22:51:22.839971.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T22:51:22.839971.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T14_05_09.748904
path:
- '**/details_harness|winogrande|5_2023-09-17T14-05-09.748904.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T14-05-09.748904.parquet'
- config_name: results
data_files:
- split: 2023_08_09T22_51_22.839971
path:
- results_2023-08-09T22:51:22.839971.parquet
- split: 2023_09_17T14_05_09.748904
path:
- results_2023-09-17T14-05-09.748904.parquet
- split: latest
path:
- results_2023-09-17T14-05-09.748904.parquet
---
# Dataset Card for Evaluation run of clibrain/Llama-2-7b-ft-instruct-es
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/clibrain/Llama-2-7b-ft-instruct-es
- **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 [clibrain/Llama-2-7b-ft-instruct-es](https://huggingface.co/clibrain/Llama-2-7b-ft-instruct-es) 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_clibrain__Llama-2-7b-ft-instruct-es",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-17T14:05:09.748904](https://huggingface.co/datasets/open-llm-leaderboard/details_clibrain__Llama-2-7b-ft-instruct-es/blob/main/results_2023-09-17T14-05-09.748904.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": 0.00037786091964606556,
"f1": 0.059617239932886215,
"f1_stderr": 0.0013507073733013888,
"acc": 0.4045158699907191,
"acc_stderr": 0.009256588130982506
},
"harness|drop|3": {
"em": 0.001363255033557047,
"em_stderr": 0.00037786091964606556,
"f1": 0.059617239932886215,
"f1_stderr": 0.0013507073733013888
},
"harness|gsm8k|5": {
"acc": 0.05686125852918878,
"acc_stderr": 0.006378790242099664
},
"harness|winogrande|5": {
"acc": 0.7521704814522494,
"acc_stderr": 0.01213438601986535
}
}
```
### 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] | [
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|
com_qa | null | 2023-06-27T07:38:08Z | 357 | 2 | [
"task_categories:question-answering",
"language:en",
"region:us"
]
| [
"question-answering"
]
| 2022-03-02T23:29:22Z | ---
language:
- en
paperswithcode_id: comqa
pretty_name: ComQA
dataset_info:
features:
- name: cluster_id
dtype: string
- name: questions
sequence: string
- name: answers
sequence: string
splits:
- name: train
num_bytes: 696645
num_examples: 3966
- name: test
num_bytes: 273384
num_examples: 2243
- name: validation
num_bytes: 131945
num_examples: 966
download_size: 1671684
dataset_size: 1101974
task_categories:
- question-answering
---
# Dataset Card for "com_qa"
## 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:** [http://qa.mpi-inf.mpg.de/comqa/](http://qa.mpi-inf.mpg.de/comqa/)
- **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:** 1.67 MB
- **Size of the generated dataset:** 1.10 MB
- **Total amount of disk used:** 2.78 MB
### Dataset Summary
ComQA is a dataset of 11,214 questions, which were collected from WikiAnswers, a community question answering website.
By collecting questions from such a site we ensure that the information needs are ones of interest to actual users.
Moreover, questions posed there are often cannot be answered by commercial search engines or QA technology, making them
more interesting for driving future research compared to those collected from an engine's query log. The dataset contains
questions with various challenging phenomena such as the need for temporal reasoning, comparison (e.g., comparatives,
superlatives, ordinals), compositionality (multiple, possibly nested, subquestions with multiple entities), and
unanswerable questions (e.g., Who was the first human being on Mars?). Through a large crowdsourcing effort, questions
in ComQA are grouped into 4,834 paraphrase clusters that express the same information need. Each cluster is annotated
with its answer(s). ComQA answers come in the form of Wikipedia entities wherever possible. Wherever the answers are
temporal or measurable quantities, TIMEX3 and the International System of Units (SI) are used for normalization.
### 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
#### default
- **Size of downloaded dataset files:** 1.67 MB
- **Size of the generated dataset:** 1.10 MB
- **Total amount of disk used:** 2.78 MB
An example of 'validation' looks as follows.
```
{
"answers": ["https://en.wikipedia.org/wiki/north_sea"],
"cluster_id": "cluster-922",
"questions": ["what sea separates the scandinavia peninsula from britain?", "which sea separates britain from scandinavia?"]
}
```
### Data Fields
The data fields are the same among all splits.
#### default
- `cluster_id`: a `string` feature.
- `questions`: a `list` of `string` features.
- `answers`: a `list` of `string` features.
### Data Splits
| name |train|validation|test|
|-------|----:|---------:|---:|
|default| 3966| 966|2243|
## 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{abujabal-etal-2019-comqa,
title = "{ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters",
author = {Abujabal, Abdalghani and
Saha Roy, Rishiraj and
Yahya, Mohamed and
Weikum, Gerhard},
booktitle = {Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
month = {jun},
year = {2019},
address = {Minneapolis, Minnesota},
publisher = {Association for Computational Linguistics},
url = {https://www.aclweb.org/anthology/N19-1027},
doi = {10.18653/v1/N19-1027{,
pages = {307--317},
}
```
### Contributions
Thanks to [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten), [@albertvillanova](https://github.com/albertvillanova) for adding this dataset. | [
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|
JeremyArancio/lotr-book | JeremyArancio | 2023-06-02T12:30:41Z | 357 | 0 | [
"region:us"
]
| null | 2023-05-18T09:53:28Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 2432593
num_examples: 1
download_size: 0
dataset_size: 2432593
---
# Dataset Card for "lotr-book"
The Lord of the Rings books extracted into one dataset.
[Source](https://github.com/jeremyarancio/llm-rpg/blob/main/llm/prepare_dataset.py)
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
# Notes
* Book [link](https://gosafir.com/mag/wp-content/uploads/2019/12/Tolkien-J.-The-lord-of-the-rings-HarperCollins-ebooks-2010.pdf)
* Footers and header were removed.
* Starts at page 45 and ends at page 1055 | [
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|
result-kand2-sdxl-wuerst-karlo/70a3f689 | result-kand2-sdxl-wuerst-karlo | 2023-11-10T00:19:20Z | 357 | 0 | [
"region:us"
]
| null | 2023-11-10T00:19:19Z | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 163
num_examples: 10
download_size: 1345
dataset_size: 163
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "70a3f689"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
result-kand2-sdxl-wuerst-karlo/ae385042 | result-kand2-sdxl-wuerst-karlo | 2023-11-10T00:22:08Z | 357 | 0 | [
"region:us"
]
| null | 2023-11-10T00:22:08Z | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 161
num_examples: 10
download_size: 1340
dataset_size: 161
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ae385042"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
sem_eval_2020_task_11 | null | 2023-01-25T14:43:56Z | 356 | 5 | [
"task_categories:text-classification",
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:unknown",
"propaganda-span-identification",
"propaganda-technique-classification",
"arxiv:2009.02696",
"region:us"
]
| [
"text-classification",
"token-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
- token-classification
task_ids: []
pretty_name: SemEval-2020 Task 11
tags:
- propaganda-span-identification
- propaganda-technique-classification
dataset_info:
features:
- name: article_id
dtype: string
- name: text
dtype: string
- name: span_identification
sequence:
- name: start_char_offset
dtype: int64
- name: end_char_offset
dtype: int64
- name: technique_classification
sequence:
- name: start_char_offset
dtype: int64
- name: end_char_offset
dtype: int64
- name: technique
dtype:
class_label:
names:
'0': Appeal_to_Authority
'1': Appeal_to_fear-prejudice
'2': Bandwagon,Reductio_ad_hitlerum
'3': Black-and-White_Fallacy
'4': Causal_Oversimplification
'5': Doubt
'6': Exaggeration,Minimisation
'7': Flag-Waving
'8': Loaded_Language
'9': Name_Calling,Labeling
'10': Repetition
'11': Slogans
'12': Thought-terminating_Cliches
'13': Whataboutism,Straw_Men,Red_Herring
splits:
- name: train
num_bytes: 2358613
num_examples: 371
- name: test
num_bytes: 454100
num_examples: 90
- name: validation
num_bytes: 396410
num_examples: 75
download_size: 0
dataset_size: 3209123
---
# Dataset Card for SemEval-2020 Task 11
## 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:** [PTC TASKS ON "DETECTION OF PROPAGANDA TECHNIQUES IN NEWS ARTICLES"](https://propaganda.qcri.org/ptc/index.html)
- **Paper:** [SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles](https://arxiv.org/abs/2009.02696)
- **Leaderboard:** [PTC Tasks Leaderboard](https://propaganda.qcri.org/ptc/leaderboard.php)
- **Point of Contact:** [Task organizers contact]([email protected])
### Dataset Summary
Propagandistic news articles use specific techniques to convey their message, such as whataboutism, red Herring, and name calling, among many others. The Propaganda Techniques Corpus (PTC) allows to study automatic algorithms to detect them. We provide a permanent leaderboard to allow researchers both to advertise their progress and to be up-to-speed with the state of the art on the tasks offered (see below for a definition).
### Supported Tasks and Leaderboards
More information on scoring methodology can be found in [propaganda tasks evaluation document](https://propaganda.qcri.org/ptc/data/propaganda_tasks_evaluation.pdf)
### Languages
This dataset consists of English news articles
## Dataset Structure
### Data Instances
Each example is structured as follows:
```
{
"span_identification": {
"end_char_offset": [720, 6322, ...],
"start_char_offset": [683, 6314, ...]
},
"technique_classification": {
"end_char_offset": [720,6322, ...],
"start_char_offset": [683,6314, ...],
"technique": [7,8, ...]
},
"text": "Newt Gingrich: The truth about Trump, Putin, and Obama\n\nPresident Trump..."
}
```
### Data Fields
- `text`: The full text of the news article.
- `span_identification`: a dictionary feature containing:
- `start_char_offset`: The start character offset of the span for the SI task
- `end_char_offset`: The end character offset of the span for the SI task
- `technique_classification`: a dictionary feature containing:
- `start_char_offset`: The start character offset of the span for the TC task
- `end_char_offset`: The start character offset of the span for the TC task
- `technique`: the propaganda technique classification label, with possible values including `Appeal_to_Authority`, `Appeal_to_fear-prejudice`, `Bandwagon,Reductio_ad_hitlerum`, `Black-and-White_Fallacy`, `Causal_Oversimplification`.
### Data Splits
| | Train | Valid | Test |
| ----- | ------ | ----- | ---- |
| Input Sentences | 371 | 75 | 90 |
| Total Annotations SI | 5468 | 940 | 0 |
| Total Annotations TC | 6128 | 1063 | 0 |
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
In order to build the PTC-SemEval20 corpus, we retrieved a sample of news articles from the period
starting in mid-2017 and ending in early 2019. We selected 13 propaganda and 36 non-propaganda news
media outlets, as labeled by Media Bias/Fact Check,3
and we retrieved articles from these sources. We
deduplicated the articles on the basis of word n-grams matching (Barron-Cede ´ no and Rosso, 2009) and ˜
we discarded faulty entries (e.g., empty entries from blocking websites).
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
The annotation job consisted of both spotting a propaganda snippet and, at the same time, labeling
it with a specific propaganda technique. The annotation guidelines are shown in the appendix; they
are also available online.4 We ran the annotation in two phases: (i) two annotators label an article
independently and (ii) the same two annotators gather together with a consolidator to discuss dubious
instances (e.g., spotted only by one annotator, boundary discrepancies, label mismatch, etc.). This protocol
was designed after a pilot annotation stage, in which a relatively large number of snippets had been spotted
by one annotator only. The annotation team consisted of six professional annotators from A Data Pro trained to spot and label the propaganda snippets from free text. The job was carried out on an instance of
the Anafora annotation platform (Chen and Styler, 2013), which we tailored for our propaganda annotation
task.
We evaluated the annotation process in terms of γ agreement (Mathet et al., 2015) between each of
the annotators and the final gold labels. The γ agreement on the annotated articles is on average 0.6;
see (Da San Martino et al., 2019b) for a more detailed discussion of inter-annotator agreement. The
training and the development part of the PTC-SemEval20 corpus are the same as the training and the
testing datasets described in (Da San Martino et al., 2019b). The test part of the PTC-SemEval20 corpus
consists of 90 additional articles selected from the same sources as for training and development. For
the test articles, we further extended the annotation process by adding one extra consolidation step: we
revisited all the articles in that partition and we performed the necessary adjustments to the spans and to
the labels as necessary, after a thorough discussion and convergence among at least three experts who
were not involved in the initial annotations.
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```
@misc{martino2020semeval2020,
title={SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles},
author={G. Da San Martino and A. Barrón-Cedeño and H. Wachsmuth and R. Petrov and P. Nakov},
year={2020},
eprint={2009.02696},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
Thanks to [@ZacharySBrown](https://github.com/ZacharySBrown) for adding this dataset. | [
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|
hezarai/xlsum-fa | hezarai | 2023-11-14T14:10:21Z | 356 | 1 | [
"task_categories:summarization",
"language:fa",
"region:us"
]
| [
"summarization"
]
| 2023-07-31T07:58:00Z | ---
task_categories:
- summarization
language:
- fa
pretty_name: XLSum Persian
---
The Persian portion of the [XLSum](https://huggingface.co/datasets/csebuetnlp/xlsum) dataset.
### Citation
```bibtex
@inproceedings{hasan-etal-2021-xl,
title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",
author = "Hasan, Tahmid and
Bhattacharjee, Abhik and
Islam, Md. Saiful and
Mubasshir, Kazi and
Li, Yuan-Fang and
Kang, Yong-Bin and
Rahman, M. Sohel and
Shahriyar, Rifat",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.413",
pages = "4693--4703",
}
``` | [
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|
hkcancor | null | 2023-02-23T08:43:12Z | 355 | 11 | [
"task_categories:translation",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:yue",
"license:cc-by-4.0",
"region:us"
]
| [
"translation",
"text-generation",
"fill-mask"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- yue
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
- text-generation
- fill-mask
task_ids:
- dialogue-modeling
paperswithcode_id: hong-kong-cantonese-corpus
pretty_name: The Hong Kong Cantonese Corpus (HKCanCor)
dataset_info:
features:
- name: conversation_id
dtype: string
- name: speaker
dtype: string
- name: turn_number
dtype: int16
- name: tokens
sequence: string
- name: transcriptions
sequence: string
- name: pos_tags_prf
sequence:
class_label:
names:
'0': '!'
'1': '"'
'2': '#'
'3': ''''
'4': ','
'5': '-'
'6': .
'7': '...'
'8': '?'
'9': A
'10': AD
'11': AG
'12': AIRWAYS0
'13': AN
'14': AND
'15': B
'16': BG
'17': BEAN0
'18': C
'19': CENTRE0
'20': CG
'21': D
'22': D1
'23': DG
'24': E
'25': ECHO0
'26': F
'27': G
'28': G1
'29': G2
'30': H
'31': HILL0
'32': I
'33': IG
'34': J
'35': JB
'36': JM
'37': JN
'38': JNS
'39': JNT
'40': JNZ
'41': K
'42': KONG
'43': L
'44': L1
'45': LG
'46': M
'47': MG
'48': MONTY0
'49': MOUNTAIN0
'50': N
'51': N1
'52': NG
'53': NR
'54': NS
'55': NSG
'56': NT
'57': NX
'58': NZ
'59': O
'60': P
'61': PEPPER0
'62': Q
'63': QG
'64': R
'65': RG
'66': S
'67': SOUND0
'68': T
'69': TELECOM0
'70': TG
'71': TOUCH0
'72': U
'73': UG
'74': U0
'75': V
'76': V1
'77': VD
'78': VG
'79': VK
'80': VN
'81': VU
'82': VUG
'83': W
'84': X
'85': XA
'86': XB
'87': XC
'88': XD
'89': XE
'90': XJ
'91': XJB
'92': XJN
'93': XJNT
'94': XJNZ
'95': XJV
'96': XJA
'97': XL1
'98': XM
'99': XN
'100': XNG
'101': XNR
'102': XNS
'103': XNT
'104': XNX
'105': XNZ
'106': XO
'107': XP
'108': XQ
'109': XR
'110': XS
'111': XT
'112': XV
'113': XVG
'114': XVN
'115': XX
'116': Y
'117': YG
'118': Y1
'119': Z
- name: pos_tags_ud
sequence:
class_label:
names:
'0': DET
'1': PRON
'2': VERB
'3': NOUN
'4': ADJ
'5': PUNCT
'6': INTJ
'7': ADV
'8': V
'9': PART
'10': X
'11': NUM
'12': PROPN
'13': AUX
'14': CCONJ
'15': ADP
splits:
- name: train
num_bytes: 5746381
num_examples: 10801
download_size: 961514
dataset_size: 5746381
---
# Dataset Card for The Hong Kong Cantonese Corpus (HKCanCor)
## 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:** http://compling.hss.ntu.edu.sg/hkcancor/
- **Repository:** https://github.com/fcbond/hkcancor
- **Paper:** [Luke and Wang, 2015](https://github.com/fcbond/hkcancor/blob/master/data/LukeWong_Hong-Kong-Cantonese-Corpus.pdf)
- **Leaderboard:** N/A
- **Point of Contact:** Luke Kang Kwong
### Dataset Summary
The Hong Kong Cantonese Corpus (HKCanCor) comprise transcribed conversations recorded
between March 1997 and August 1998. It contains recordings of spontaneous speech (51 texts)
and radio programmes (42 texts), which involve 2 to 4 speakers, with 1 text of monologue.
In total, the corpus contains around 230,000 Chinese words. The text is word-segmented (i.e., tokenization is at word-level, and each token can span multiple Chinese characters). Tokens are annotated with part-of-speech (POS) tags and romanised Cantonese pronunciation.
* Romanisation
* Follows conventions set by the Linguistic Society of Hong Kong (LSHK).
* POS
* The tagset used by this corpus extends the one in the Peita-Fujitsu-Renmin Ribao (PRF) corpus (Duan et al., 2000). Extensions were made to further capture Cantonese-specific phenomena.
* To facilitate everyday usage and for better comparability across languages and/or corpora, this dataset also includes the tags mapped to the [Universal Dependencies 2.0](https://universaldependencies.org/u/pos/index.html) format. This mapping references the [PyCantonese](https://github.com/jacksonllee/pycantonese) library.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Yue Chinese / Cantonese (Hong Kong).
## Dataset Structure
This corpus has 10801 utterances and approximately 230000 Chinese words.
There is no predefined split.
### Data Instances
Each instance contains a conversation id, speaker id within that conversation,
turn number, part-of-speech tag for each Chinese word in the PRF format and UD2.0 format,
and the utterance written in Chinese characters as well as its LSHK format romanisation.
For example:
```python
{
'conversation_id': 'TNR016-DR070398-HAI6V'
'pos_tags_prf': ['v', 'w'],
'pos_tags_ud': ['VERB', 'PUNCT'],
'speaker': 'B',
'transcriptions': ['hai6', 'VQ1'],
'turn_number': 112,
'tokens': ['係', '。']
}
```
### Data Fields
- conversation_id: unique dialogue-level id
- pos_tags_prf: POS tag using the PRF format at token-level
- pos_tag_ud: POS tag using the UD2.0 format at token-level
- speaker: unique speaker id within dialogue
- transcriptions: token-level romanisation in the LSHK format
- turn_number: turn number in dialogue
- tokens: Chinese word or punctuation at token-level
### Data Splits
There are no specified splits in this dataset.
## 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 4.0 International License](https://creativecommons.org/licenses/by/4.0/deed.ast).
### Citation Information
This corpus was developed by [Luke and Wong, 2015](http://compling.hss.ntu.edu.sg/hkcancor/data/LukeWong_Hong-Kong-Cantonese-Corpus.pdf).
```
@article{luke2015hong,
author={Luke, Kang-Kwong and Wong, May LY},
title={The Hong Kong Cantonese corpus: design and uses},
journal={Journal of Chinese Linguistics},
year={2015},
pages={309-330},
month={12}
}
```
The POS tagset to Universal Dependency tagset mapping is provided by Jackson Lee, as a part of the [PyCantonese](https://github.com/jacksonllee/pycantonese) library.
```
@misc{lee2020,
author = {Lee, Jackson},
title = {PyCantonese: Cantonese Linguistics and NLP in Python},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/jacksonllee/pycantonese}},
commit = {1d58f44e1cb097faa69de6b617e1d28903b84b98}
}
```
### Contributions
Thanks to [@j-chim](https://github.com/j-chim) for adding this dataset. | [
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|
mteb/stackexchange-clustering-p2p | mteb | 2022-09-27T19:14:52Z | 355 | 0 | [
"language:en",
"region:us"
]
| null | 2022-05-11T07:56:54Z | ---
language:
- en
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|
open-llm-leaderboard/details_huggingtweets__jerma985 | open-llm-leaderboard | 2023-09-22T15:13:50Z | 355 | 0 | [
"region:us"
]
| null | 2023-08-18T00:09:04Z | ---
pretty_name: Evaluation run of huggingtweets/jerma985
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [huggingtweets/jerma985](https://huggingface.co/huggingtweets/jerma985) 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_huggingtweets__jerma985\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-22T15:13:39.388412](https://huggingface.co/datasets/open-llm-leaderboard/details_huggingtweets__jerma985/blob/main/results_2023-09-22T15-13-39.388412.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\": 0.014786073825503355,\n\
\ \"em_stderr\": 0.0012360366760473087,\n \"f1\": 0.0371633808724832,\n\
\ \"f1_stderr\": 0.001611424008567761,\n \"acc\": 0.2533543804262036,\n\
\ \"acc_stderr\": 0.0070256103461651745\n },\n \"harness|drop|3\":\
\ {\n \"em\": 0.014786073825503355,\n \"em_stderr\": 0.0012360366760473087,\n\
\ \"f1\": 0.0371633808724832,\n \"f1_stderr\": 0.001611424008567761\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5067087608524072,\n\
\ \"acc_stderr\": 0.014051220692330349\n }\n}\n```"
repo_url: https://huggingface.co/huggingtweets/jerma985
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_19T10_38_23.212427
path:
- '**/details_harness|arc:challenge|25_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_22T15_13_39.388412
path:
- '**/details_harness|drop|3_2023-09-22T15-13-39.388412.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-22T15-13-39.388412.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_22T15_13_39.388412
path:
- '**/details_harness|gsm8k|5_2023-09-22T15-13-39.388412.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-22T15-13-39.388412.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hellaswag|10_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T10:38:23.212427.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T10:38:23.212427.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T10:38:23.212427.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_22T15_13_39.388412
path:
- '**/details_harness|winogrande|5_2023-09-22T15-13-39.388412.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-22T15-13-39.388412.parquet'
- config_name: results
data_files:
- split: 2023_07_19T10_38_23.212427
path:
- results_2023-07-19T10:38:23.212427.parquet
- split: 2023_09_22T15_13_39.388412
path:
- results_2023-09-22T15-13-39.388412.parquet
- split: latest
path:
- results_2023-09-22T15-13-39.388412.parquet
---
# Dataset Card for Evaluation run of huggingtweets/jerma985
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/huggingtweets/jerma985
- **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 [huggingtweets/jerma985](https://huggingface.co/huggingtweets/jerma985) 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_huggingtweets__jerma985",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-22T15:13:39.388412](https://huggingface.co/datasets/open-llm-leaderboard/details_huggingtweets__jerma985/blob/main/results_2023-09-22T15-13-39.388412.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": 0.014786073825503355,
"em_stderr": 0.0012360366760473087,
"f1": 0.0371633808724832,
"f1_stderr": 0.001611424008567761,
"acc": 0.2533543804262036,
"acc_stderr": 0.0070256103461651745
},
"harness|drop|3": {
"em": 0.014786073825503355,
"em_stderr": 0.0012360366760473087,
"f1": 0.0371633808724832,
"f1_stderr": 0.001611424008567761
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
},
"harness|winogrande|5": {
"acc": 0.5067087608524072,
"acc_stderr": 0.014051220692330349
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Chat-LLaMAfied | open-llm-leaderboard | 2023-10-27T01:55:32Z | 355 | 0 | [
"region:us"
]
| null | 2023-10-10T07:31:24Z | ---
pretty_name: Evaluation run of hiyouga/Baichuan2-7B-Chat-LLaMAfied
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [hiyouga/Baichuan2-7B-Chat-LLaMAfied](https://huggingface.co/hiyouga/Baichuan2-7B-Chat-LLaMAfied)\
\ 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_hiyouga__Baichuan2-7B-Chat-LLaMAfied\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-27T01:55:17.464897](https://huggingface.co/datasets/open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Chat-LLaMAfied/blob/main/results_2023-10-27T01-55-17.464897.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\": 0.2062709731543624,\n\
\ \"em_stderr\": 0.004143762363131985,\n \"f1\": 0.26938129194630883,\n\
\ \"f1_stderr\": 0.004172682699820514,\n \"acc\": 0.40028530858265426,\n\
\ \"acc_stderr\": 0.010786124750718863\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.2062709731543624,\n \"em_stderr\": 0.004143762363131985,\n\
\ \"f1\": 0.26938129194630883,\n \"f1_stderr\": 0.004172682699820514\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.10917361637604246,\n \
\ \"acc_stderr\": 0.008590089300511151\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.691397000789266,\n \"acc_stderr\": 0.012982160200926577\n\
\ }\n}\n```"
repo_url: https://huggingface.co/hiyouga/Baichuan2-7B-Chat-LLaMAfied
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_10T07_31_02.024016
path:
- '**/details_harness|arc:challenge|25_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_27T01_55_17.464897
path:
- '**/details_harness|drop|3_2023-10-27T01-55-17.464897.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-27T01-55-17.464897.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_27T01_55_17.464897
path:
- '**/details_harness|gsm8k|5_2023-10-27T01-55-17.464897.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-27T01-55-17.464897.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hellaswag|10_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-31-02.024016.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T07-31-02.024016.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T07-31-02.024016.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_27T01_55_17.464897
path:
- '**/details_harness|winogrande|5_2023-10-27T01-55-17.464897.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-27T01-55-17.464897.parquet'
- config_name: results
data_files:
- split: 2023_10_10T07_31_02.024016
path:
- results_2023-10-10T07-31-02.024016.parquet
- split: 2023_10_27T01_55_17.464897
path:
- results_2023-10-27T01-55-17.464897.parquet
- split: latest
path:
- results_2023-10-27T01-55-17.464897.parquet
---
# Dataset Card for Evaluation run of hiyouga/Baichuan2-7B-Chat-LLaMAfied
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/hiyouga/Baichuan2-7B-Chat-LLaMAfied
- **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 [hiyouga/Baichuan2-7B-Chat-LLaMAfied](https://huggingface.co/hiyouga/Baichuan2-7B-Chat-LLaMAfied) 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_hiyouga__Baichuan2-7B-Chat-LLaMAfied",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-27T01:55:17.464897](https://huggingface.co/datasets/open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Chat-LLaMAfied/blob/main/results_2023-10-27T01-55-17.464897.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": 0.2062709731543624,
"em_stderr": 0.004143762363131985,
"f1": 0.26938129194630883,
"f1_stderr": 0.004172682699820514,
"acc": 0.40028530858265426,
"acc_stderr": 0.010786124750718863
},
"harness|drop|3": {
"em": 0.2062709731543624,
"em_stderr": 0.004143762363131985,
"f1": 0.26938129194630883,
"f1_stderr": 0.004172682699820514
},
"harness|gsm8k|5": {
"acc": 0.10917361637604246,
"acc_stderr": 0.008590089300511151
},
"harness|winogrande|5": {
"acc": 0.691397000789266,
"acc_stderr": 0.012982160200926577
}
}
```
### 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] | [
-0.34073829650878906,
-0.7725176811218262,
0.10062900185585022,
0.3818545639514923,
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|
Braddy/xview_captions_v3 | Braddy | 2023-10-23T19:52:00Z | 355 | 0 | [
"region:us"
]
| null | 2023-10-23T19:51:54Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: text
sequence: string
- name: file_id
dtype: string
splits:
- name: train
num_bytes: 94674025.0
num_examples: 949
download_size: 94634260
dataset_size: 94674025.0
---
# Dataset Card for "xview_captions_v3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
FINDA-FIT/Fin_Corpus_EarningCall | FINDA-FIT | 2023-02-14T04:58:13Z | 354 | 1 | [
"region:us"
]
| null | 2023-02-11T07:31:37Z | ---
dataset_info:
features:
- name: ID
dtype: string
- name: CONTEXT
dtype: string
splits:
- name: train
num_bytes: 8724423352
num_examples: 234119
download_size: 4615593313
dataset_size: 8724423352
---
# Dataset Card for "Fin_Corpus_EarningCall"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
lmsys/mt_bench_human_judgments | lmsys | 2023-07-20T18:28:15Z | 354 | 41 | [
"task_categories:conversational",
"task_categories:question-answering",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"arxiv:2306.05685",
"region:us"
]
| [
"conversational",
"question-answering"
]
| 2023-07-04T14:03:03Z | ---
dataset_info:
features:
- name: question_id
dtype: int64
- name: model_a
dtype: string
- name: model_b
dtype: string
- name: winner
dtype: string
- name: judge
dtype: string
- name: conversation_a
list:
- name: content
dtype: string
- name: role
dtype: string
- name: conversation_b
list:
- name: content
dtype: string
- name: role
dtype: string
- name: turn
dtype: int64
splits:
- name: human
num_bytes: 15003469
num_examples: 3355
- name: gpt4_pair
num_bytes: 10679650
num_examples: 2400
download_size: 1388888
dataset_size: 25683119
license: cc-by-4.0
task_categories:
- conversational
- question-answering
language:
- en
size_categories:
- 1K<n<10K
---
## Content
This dataset contains 3.3K expert-level pairwise human preferences for model responses generated by 6 models in response to 80 MT-bench questions.
The 6 models are GPT-4, GPT-3.5, Claud-v1, Vicuna-13B, Alpaca-13B, and LLaMA-13B. The annotators are mostly graduate students with expertise in the topic areas of each of the questions. The details of data collection can be found in our [paper](https://arxiv.org/abs/2306.05685).
## Agreement Calculation
This Colab [notebook](https://colab.research.google.com/drive/1ctgygDRJhVGUJTQy8-bRZCl1WNcT8De6?usp=sharing) shows how to compute the agreement between humans and GPT-4 judge with the dataset. Our results show that humans and GPT-4 judge achieve over 80\% agreement, the same level of agreement between humans.
## Citation
```
@misc{zheng2023judging,
title={Judging LLM-as-a-judge with MT-Bench and Chatbot Arena},
author={Lianmin Zheng and Wei-Lin Chiang and Ying Sheng and Siyuan Zhuang and Zhanghao Wu and Yonghao Zhuang and Zi Lin and Zhuohan Li and Dacheng Li and Eric. P Xing and Hao Zhang and Joseph E. Gonzalez and Ion Stoica},
year={2023},
eprint={2306.05685},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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|
open-llm-leaderboard/details_h2oai__h2ogpt-oig-oasst1-512-6_9b | open-llm-leaderboard | 2023-09-22T15:42:21Z | 354 | 0 | [
"region:us"
]
| null | 2023-08-18T11:53:23Z | ---
pretty_name: Evaluation run of h2oai/h2ogpt-oig-oasst1-512-6_9b
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [h2oai/h2ogpt-oig-oasst1-512-6_9b](https://huggingface.co/h2oai/h2ogpt-oig-oasst1-512-6_9b)\
\ 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_h2oai__h2ogpt-oig-oasst1-512-6_9b\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-22T15:42:09.246441](https://huggingface.co/datasets/open-llm-leaderboard/details_h2oai__h2ogpt-oig-oasst1-512-6_9b/blob/main/results_2023-09-22T15-42-09.246441.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\": 0.00041946308724832214,\n\
\ \"em_stderr\": 0.00020969854707829136,\n \"f1\": 0.04082843959731554,\n\
\ \"f1_stderr\": 0.00109074720252004,\n \"acc\": 0.3174773048631111,\n\
\ \"acc_stderr\": 0.00816331055041483\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.00041946308724832214,\n \"em_stderr\": 0.00020969854707829136,\n\
\ \"f1\": 0.04082843959731554,\n \"f1_stderr\": 0.00109074720252004\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.009855951478392721,\n \
\ \"acc_stderr\": 0.002721076577041661\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6250986582478295,\n \"acc_stderr\": 0.013605544523787998\n\
\ }\n}\n```"
repo_url: https://huggingface.co/h2oai/h2ogpt-oig-oasst1-512-6_9b
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|arc:challenge|25_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_22T15_42_09.246441
path:
- '**/details_harness|drop|3_2023-09-22T15-42-09.246441.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-22T15-42-09.246441.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_22T15_42_09.246441
path:
- '**/details_harness|gsm8k|5_2023-09-22T15-42-09.246441.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-22T15-42-09.246441.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hellaswag|10_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:42:14.893645.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T17:42:14.893645.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T17:42:14.893645.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_22T15_42_09.246441
path:
- '**/details_harness|winogrande|5_2023-09-22T15-42-09.246441.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-22T15-42-09.246441.parquet'
- config_name: results
data_files:
- split: 2023_07_19T17_42_14.893645
path:
- results_2023-07-19T17:42:14.893645.parquet
- split: 2023_09_22T15_42_09.246441
path:
- results_2023-09-22T15-42-09.246441.parquet
- split: latest
path:
- results_2023-09-22T15-42-09.246441.parquet
---
# Dataset Card for Evaluation run of h2oai/h2ogpt-oig-oasst1-512-6_9b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/h2oai/h2ogpt-oig-oasst1-512-6_9b
- **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 [h2oai/h2ogpt-oig-oasst1-512-6_9b](https://huggingface.co/h2oai/h2ogpt-oig-oasst1-512-6_9b) 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_h2oai__h2ogpt-oig-oasst1-512-6_9b",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-22T15:42:09.246441](https://huggingface.co/datasets/open-llm-leaderboard/details_h2oai__h2ogpt-oig-oasst1-512-6_9b/blob/main/results_2023-09-22T15-42-09.246441.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": 0.00041946308724832214,
"em_stderr": 0.00020969854707829136,
"f1": 0.04082843959731554,
"f1_stderr": 0.00109074720252004,
"acc": 0.3174773048631111,
"acc_stderr": 0.00816331055041483
},
"harness|drop|3": {
"em": 0.00041946308724832214,
"em_stderr": 0.00020969854707829136,
"f1": 0.04082843959731554,
"f1_stderr": 0.00109074720252004
},
"harness|gsm8k|5": {
"acc": 0.009855951478392721,
"acc_stderr": 0.002721076577041661
},
"harness|winogrande|5": {
"acc": 0.6250986582478295,
"acc_stderr": 0.013605544523787998
}
}
```
### 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] | [
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|
Sleoruiz/disc_cla_segunda | Sleoruiz | 2023-03-21T17:52:27Z | 353 | 0 | [
"region:us"
]
| null | 2023-03-21T17:52:22Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: inputs
struct:
- name: text
dtype: string
- name: prediction
list:
- name: label
dtype: string
- name: score
dtype: float64
- name: prediction_agent
dtype: string
- name: annotation
sequence: string
- name: annotation_agent
dtype: string
- name: multi_label
dtype: bool
- name: explanation
dtype: 'null'
- name: id
dtype: string
- name: metadata
dtype: 'null'
- name: status
dtype: string
- name: event_timestamp
dtype: timestamp[us]
- name: metrics
struct:
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 30333232
num_examples: 7327
download_size: 15864012
dataset_size: 30333232
---
# Dataset Card for "disc_cla_segunda"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
open-llm-leaderboard/details_DevaMalla__llama_7b_lora | open-llm-leaderboard | 2023-10-26T14:26:52Z | 353 | 0 | [
"region:us"
]
| null | 2023-09-13T05:07:51Z | ---
pretty_name: Evaluation run of DevaMalla/llama_7b_lora
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [DevaMalla/llama_7b_lora](https://huggingface.co/DevaMalla/llama_7b_lora) on the\
\ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_DevaMalla__llama_7b_lora\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-26T14:26:37.860045](https://huggingface.co/datasets/open-llm-leaderboard/details_DevaMalla__llama_7b_lora/blob/main/results_2023-10-26T14-26-37.860045.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0012583892617449664,\n\
\ \"em_stderr\": 0.0003630560893118953,\n \"f1\": 0.0611650587248323,\n\
\ \"f1_stderr\": 0.0013990352489173911,\n \"acc\": 0.3915240971461363,\n\
\ \"acc_stderr\": 0.00940445989381676\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0012583892617449664,\n \"em_stderr\": 0.0003630560893118953,\n\
\ \"f1\": 0.0611650587248323,\n \"f1_stderr\": 0.0013990352489173911\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.05534495830174375,\n \
\ \"acc_stderr\": 0.0062982217961795855\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7277032359905288,\n \"acc_stderr\": 0.012510697991453934\n\
\ }\n}\n```"
repo_url: https://huggingface.co/DevaMalla/llama_7b_lora
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|arc:challenge|25_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_26T14_26_37.860045
path:
- '**/details_harness|drop|3_2023-10-26T14-26-37.860045.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-26T14-26-37.860045.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_26T14_26_37.860045
path:
- '**/details_harness|gsm8k|5_2023-10-26T14-26-37.860045.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-26T14-26-37.860045.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hellaswag|10_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T05-07-37.970407.parquet'
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- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T05-07-37.970407.parquet'
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- '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T05-07-37.970407.parquet'
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path:
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- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-13T05-07-37.970407.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-13T05-07-37.970407.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-13T05-07-37.970407.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_26T14_26_37.860045
path:
- '**/details_harness|winogrande|5_2023-10-26T14-26-37.860045.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-26T14-26-37.860045.parquet'
- config_name: results
data_files:
- split: 2023_09_13T05_07_37.970407
path:
- results_2023-09-13T05-07-37.970407.parquet
- split: 2023_10_26T14_26_37.860045
path:
- results_2023-10-26T14-26-37.860045.parquet
- split: latest
path:
- results_2023-10-26T14-26-37.860045.parquet
---
# Dataset Card for Evaluation run of DevaMalla/llama_7b_lora
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/DevaMalla/llama_7b_lora
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [DevaMalla/llama_7b_lora](https://huggingface.co/DevaMalla/llama_7b_lora) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_DevaMalla__llama_7b_lora",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-26T14:26:37.860045](https://huggingface.co/datasets/open-llm-leaderboard/details_DevaMalla__llama_7b_lora/blob/main/results_2023-10-26T14-26-37.860045.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.0012583892617449664,
"em_stderr": 0.0003630560893118953,
"f1": 0.0611650587248323,
"f1_stderr": 0.0013990352489173911,
"acc": 0.3915240971461363,
"acc_stderr": 0.00940445989381676
},
"harness|drop|3": {
"em": 0.0012583892617449664,
"em_stderr": 0.0003630560893118953,
"f1": 0.0611650587248323,
"f1_stderr": 0.0013990352489173911
},
"harness|gsm8k|5": {
"acc": 0.05534495830174375,
"acc_stderr": 0.0062982217961795855
},
"harness|winogrande|5": {
"acc": 0.7277032359905288,
"acc_stderr": 0.012510697991453934
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_Undi95__UndiMix-v4-13B | open-llm-leaderboard | 2023-10-27T04:12:14Z | 353 | 0 | [
"region:us"
]
| null | 2023-09-18T13:46:18Z | ---
pretty_name: Evaluation run of Undi95/UndiMix-v4-13B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Undi95/UndiMix-v4-13B](https://huggingface.co/Undi95/UndiMix-v4-13B) 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_Undi95__UndiMix-v4-13B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-27T04:12:01.560692](https://huggingface.co/datasets/open-llm-leaderboard/details_Undi95__UndiMix-v4-13B/blob/main/results_2023-10-27T04-12-01.560692.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\": 0.14146392617449666,\n\
\ \"em_stderr\": 0.003568960808825645,\n \"f1\": 0.20818477348993217,\n\
\ \"f1_stderr\": 0.0036692979641845653,\n \"acc\": 0.4494334219138294,\n\
\ \"acc_stderr\": 0.010726378456151354\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.14146392617449666,\n \"em_stderr\": 0.003568960808825645,\n\
\ \"f1\": 0.20818477348993217,\n \"f1_stderr\": 0.0036692979641845653\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.1372251705837756,\n \
\ \"acc_stderr\": 0.009477808244600401\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7616416732438832,\n \"acc_stderr\": 0.011974948667702308\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Undi95/UndiMix-v4-13B
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_09_18T13_45_54.862257
path:
- '**/details_harness|arc:challenge|25_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_27T04_12_01.560692
path:
- '**/details_harness|drop|3_2023-10-27T04-12-01.560692.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-27T04-12-01.560692.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_27T04_12_01.560692
path:
- '**/details_harness|gsm8k|5_2023-10-27T04-12-01.560692.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-27T04-12-01.560692.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hellaswag|10_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
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- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T13-45-54.862257.parquet'
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- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T13-45-54.862257.parquet'
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- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T13-45-54.862257.parquet'
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- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T13-45-54.862257.parquet'
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- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T13-45-54.862257.parquet'
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- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T13-45-54.862257.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
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path:
- '**/details_harness|truthfulqa:mc|0_2023-09-18T13-45-54.862257.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-18T13-45-54.862257.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_27T04_12_01.560692
path:
- '**/details_harness|winogrande|5_2023-10-27T04-12-01.560692.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-27T04-12-01.560692.parquet'
- config_name: results
data_files:
- split: 2023_09_18T13_45_54.862257
path:
- results_2023-09-18T13-45-54.862257.parquet
- split: 2023_10_27T04_12_01.560692
path:
- results_2023-10-27T04-12-01.560692.parquet
- split: latest
path:
- results_2023-10-27T04-12-01.560692.parquet
---
# Dataset Card for Evaluation run of Undi95/UndiMix-v4-13B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Undi95/UndiMix-v4-13B
- **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 [Undi95/UndiMix-v4-13B](https://huggingface.co/Undi95/UndiMix-v4-13B) 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_Undi95__UndiMix-v4-13B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-27T04:12:01.560692](https://huggingface.co/datasets/open-llm-leaderboard/details_Undi95__UndiMix-v4-13B/blob/main/results_2023-10-27T04-12-01.560692.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": 0.14146392617449666,
"em_stderr": 0.003568960808825645,
"f1": 0.20818477348993217,
"f1_stderr": 0.0036692979641845653,
"acc": 0.4494334219138294,
"acc_stderr": 0.010726378456151354
},
"harness|drop|3": {
"em": 0.14146392617449666,
"em_stderr": 0.003568960808825645,
"f1": 0.20818477348993217,
"f1_stderr": 0.0036692979641845653
},
"harness|gsm8k|5": {
"acc": 0.1372251705837756,
"acc_stderr": 0.009477808244600401
},
"harness|winogrande|5": {
"acc": 0.7616416732438832,
"acc_stderr": 0.011974948667702308
}
}
```
### 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] | [
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|
cdt | null | 2023-01-25T14:27:46Z | 352 | 0 | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:bsd-3-clause",
"region:us"
]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- bsd-3-clause
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: cdt
dataset_info:
features:
- name: sentence
dtype: string
- name: target
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 1104322
num_examples: 10041
- name: test
num_bytes: 109681
num_examples: 1000
download_size: 375476
dataset_size: 1214003
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
http://2019.poleval.pl/index.php/tasks/
- **Repository:**
https://github.com/ptaszynski/cyberbullying-Polish
- **Paper:**
- **Leaderboard:**
https://klejbenchmark.com/leaderboard/
- **Point of Contact:**
### Dataset Summary
The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Polish
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
- sentence: an anonymized tweet in polish
- target: 1 if tweet is described as bullying, 0 otherwise. The test set doesn't have labels so -1 is used instead.
### 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
BSD 3-Clause
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@abecadel](https://github.com/abecadel) for adding this dataset. | [
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|
clickbait_news_bg | null | 2023-01-25T14:28:03Z | 352 | 0 | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:bg",
"license:unknown",
"region:us"
]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- bg
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
pretty_name: Clickbait/Fake News in Bulgarian
dataset_info:
features:
- name: fake_news_score
dtype:
class_label:
names:
'0': legitimate
'1': fake
- name: click_bait_score
dtype:
class_label:
names:
'0': normal
'1': clickbait
- name: content_title
dtype: string
- name: content_url
dtype: string
- name: content_published_time
dtype: string
- name: content
dtype: string
splits:
- name: train
num_bytes: 24480402
num_examples: 2815
- name: validation
num_bytes: 6752242
num_examples: 761
download_size: 8569575
dataset_size: 31232644
---
# Dataset Card for Clickbait/Fake News in Bulgarian
## 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:** [Data Science Society / Case Fake News](https://gitlab.com/datasciencesociety/case_fake_news)
- **Repository:** [Data Science Society / Case Fake News / Data](https://gitlab.com/datasciencesociety/case_fake_news/-/tree/master/data)
- **Paper:** [This paper uses the dataset.](https://www.acl-bg.org/proceedings/2017/RANLP%202017/pdf/RANLP045.pdf)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This is a corpus of Bulgarian news over a fixed period of time, whose factuality had been questioned.
The news come from 377 different sources from various domains, including politics, interesting facts and tips&tricks.
The dataset was prepared for the Hack the
Fake News hackathon. It was provided by the
[Bulgarian Association of PR Agencies](http://www.bapra.bg/) and is
available in [Gitlab](https://gitlab.com/datasciencesociety/).
The corpus was automatically collected, and then annotated by students of journalism.
The training dataset contains 2,815 examples, where 1,940 (i.e., 69%) are fake news
and 1,968 (i.e., 70%) are click-baits; There are 761 testing examples.
There is 98% correlation between fake news and clickbaits.
One important aspect about the training dataset is that it contains many repetitions.
This should not be surprising as it attempts to represent a natural distribution of factual
vs. fake news on-line over a period of time. As publishers of fake news often have a group of
websites that feature the same deceiving content, we should expect some repetition.
In particular, the training dataset contains
434 unique articles with duplicates. These articles have three reposts each on average, with
the most reposted article appearing 45 times.
If we take into account the labels of the reposted articles, we can see that if an article
is reposted, it is more likely to be fake news.
The number of fake news that have a duplicate in the training dataset are 1018 whereas,
the number of articles with genuine content
that have a duplicate article in the training set is 322.
(The dataset description is from the following [paper](https://www.acl-bg.org/proceedings/2017/RANLP%202017/pdf/RANLP045.pdf).)
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Bulgarian
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
Each entry in the dataset consists of the following elements:
* `fake_news_score` - a label indicating whether the article is fake or not
* `click_bait_score` - another label indicating whether it is a click-bait
* `content_title` - article heading
* `content_url` - URL of the original article
* `content_published_time` - date of publication
* `content` - article content
### Data Splits
The **training dataset** contains 2,815 examples, where 1,940 (i.e., 69%) are fake news
and 1,968 (i.e., 70%) are click-baits;
The **validation dataset** contains 761 testing examples.
## 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 [@tsvm](https://github.com/tsvm), [@lhoestq](https://github.com/lhoestq) for adding this dataset. | [
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|
conll2000 | null | 2023-04-05T10:02:23Z | 352 | 2 | [
"language:en",
"region:us"
]
| null | 2022-03-02T23:29:22Z | ---
language:
- en
paperswithcode_id: conll-2000-1
pretty_name: CoNLL-2000
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: pos_tags
sequence:
class_label:
names:
'0': ''''''
'1': '#'
'2': $
'3': (
'4': )
'5': ','
'6': .
'7': ':'
'8': '``'
'9': CC
'10': CD
'11': DT
'12': EX
'13': FW
'14': IN
'15': JJ
'16': JJR
'17': JJS
'18': MD
'19': NN
'20': NNP
'21': NNPS
'22': NNS
'23': PDT
'24': POS
'25': PRP
'26': PRP$
'27': RB
'28': RBR
'29': RBS
'30': RP
'31': SYM
'32': TO
'33': UH
'34': VB
'35': VBD
'36': VBG
'37': VBN
'38': VBP
'39': VBZ
'40': WDT
'41': WP
'42': WP$
'43': WRB
- name: chunk_tags
sequence:
class_label:
names:
'0': O
'1': B-ADJP
'2': I-ADJP
'3': B-ADVP
'4': I-ADVP
'5': B-CONJP
'6': I-CONJP
'7': B-INTJ
'8': I-INTJ
'9': B-LST
'10': I-LST
'11': B-NP
'12': I-NP
'13': B-PP
'14': I-PP
'15': B-PRT
'16': I-PRT
'17': B-SBAR
'18': I-SBAR
'19': B-UCP
'20': I-UCP
'21': B-VP
'22': I-VP
splits:
- name: train
num_bytes: 5356965
num_examples: 8937
- name: test
num_bytes: 1201151
num_examples: 2013
download_size: 3481560
dataset_size: 6558116
---
# Dataset Card for "conll2000"
## 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://www.clips.uantwerpen.be/conll2000/chunking/](https://www.clips.uantwerpen.be/conll2000/chunking/)
- **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:** 3.48 MB
- **Size of the generated dataset:** 6.55 MB
- **Total amount of disk used:** 10.03 MB
### Dataset Summary
Text chunking consists of dividing a text in syntactically correlated parts of words. For example, the sentence
He reckons the current account deficit will narrow to only # 1.8 billion in September . can be divided as follows:
[NP He ] [VP reckons ] [NP the current account deficit ] [VP will narrow ] [PP to ] [NP only # 1.8 billion ]
[PP in ] [NP September ] .
Text chunking is an intermediate step towards full parsing. It was the shared task for CoNLL-2000. Training and test
data for this task is available. This data consists of the same partitions of the Wall Street Journal corpus (WSJ)
as the widely used data for noun phrase chunking: sections 15-18 as training data (211727 tokens) and section 20 as
test data (47377 tokens). The annotation of the data has been derived from the WSJ corpus by a program written by
Sabine Buchholz from Tilburg University, The Netherlands.
### 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
#### conll2000
- **Size of downloaded dataset files:** 3.48 MB
- **Size of the generated dataset:** 6.55 MB
- **Total amount of disk used:** 10.03 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"chunk_tags": [11, 13, 11, 12, 21, 22, 22, 22, 22, 11, 12, 12, 17, 11, 12, 13, 11, 0, 1, 13, 11, 11, 0, 21, 22, 22, 11, 12, 12, 13, 11, 12, 12, 11, 12, 12, 0],
"id": "0",
"pos_tags": [19, 14, 11, 19, 39, 27, 37, 32, 34, 11, 15, 19, 14, 19, 22, 14, 20, 5, 15, 14, 19, 19, 5, 34, 32, 34, 11, 15, 19, 14, 20, 9, 20, 24, 15, 22, 6],
"tokens": "[\"Confidence\", \"in\", \"the\", \"pound\", \"is\", \"widely\", \"expected\", \"to\", \"take\", \"another\", \"sharp\", \"dive\", \"if\", \"trade\", \"figur..."
}
```
### Data Fields
The data fields are the same among all splits.
#### conll2000
- `id`: a `string` feature.
- `tokens`: a `list` of `string` features.
- `pos_tags`: a `list` of classification labels, with possible values including `''` (0), `#` (1), `$` (2), `(` (3), `)` (4).
- `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).
### Data Splits
| name |train|test|
|---------|----:|---:|
|conll2000| 8937|2013|
## 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{tksbuchholz2000conll,
author = "Tjong Kim Sang, Erik F. and Sabine Buchholz",
title = "Introduction to the CoNLL-2000 Shared Task: Chunking",
editor = "Claire Cardie and Walter Daelemans and Claire
Nedellec and Tjong Kim Sang, Erik",
booktitle = "Proceedings of CoNLL-2000 and LLL-2000",
publisher = "Lisbon, Portugal",
pages = "127--132",
year = "2000"
}
```
### Contributions
Thanks to [@vblagoje](https://github.com/vblagoje), [@jplu](https://github.com/jplu) for adding this dataset. | [
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|
few_rel | null | 2023-06-01T14:59:47Z | 352 | 2 | [
"task_categories:other",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:mit",
"relation-extraction",
"arxiv:1810.10147",
"arxiv:1910.07124",
"region:us"
]
| [
"other"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- crowdsourced
- machine-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
- n<1K
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: fewrel
pretty_name: Few-Shot Relation Classification Dataset
tags:
- relation-extraction
dataset_info:
- config_name: default
features:
- name: relation
dtype: string
- name: tokens
sequence: string
- name: head
struct:
- name: text
dtype: string
- name: type
dtype: string
- name: indices
sequence:
sequence: int64
- name: tail
struct:
- name: text
dtype: string
- name: type
dtype: string
- name: indices
sequence:
sequence: int64
- name: names
sequence: string
splits:
- name: train_wiki
num_bytes: 19923155
num_examples: 44800
- name: val_nyt
num_bytes: 1385642
num_examples: 2500
- name: val_pubmed
num_bytes: 488502
num_examples: 1000
- name: val_semeval
num_bytes: 2646249
num_examples: 8851
- name: val_wiki
num_bytes: 5147348
num_examples: 11200
- name: pubmed_unsupervised
num_bytes: 1117703
num_examples: 2500
download_size: 22674323
dataset_size: 30708599
- config_name: pid2name
features:
- name: relation
dtype: string
- name: names
sequence: string
splits:
- name: pid2name
num_bytes: 81607
num_examples: 744
download_size: 22674323
dataset_size: 81607
config_names:
- default
- pid2name
---
# Dataset Card for few_rel
## 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 Page](https://thunlp.github.io/)
- **Repository:** [GitHub](https://github.com/thunlp/FewRel)
- **Paper:** [FewRel](https://arxiv.org/abs/1810.10147), [FewRel 2.0](https://arxiv.org/abs/1910.07124)
- **Leaderboard:** [GitHub Leaderboard](https://thunlp.github.io/fewrel.html)
- **Point of Contact:** [Needs More Information]
### Dataset Summary
FewRel is a large-scale few-shot relation extraction dataset, which contains more than one hundred relations and tens of thousands of annotated instances cross different domains.
### Supported Tasks and Leaderboards
[Needs More Information]
### Languages
The dataset contaings English text, as used by writers on Wikipedia, and crowdsourced English annotations.
## Dataset Structure
### Data Instances
An instance from `train_wiki` split:
```
{'head': {'indices': [[16]], 'text': 'tjq', 'type': 'Q1331049'}, 'names': ['place served by transport hub', 'territorial entity or entities served by this transport hub (airport, train station, etc.)'], 'relation': 'P931', 'tail': {'indices': [[13, 14]], 'text': 'tanjung pandan', 'type': 'Q3056359'}, 'tokens': ['Merpati', 'flight', '106', 'departed', 'Jakarta', '(', 'CGK', ')', 'on', 'a', 'domestic', 'flight', 'to', 'Tanjung', 'Pandan', '(', 'TJQ', ')', '.']}
```
### Data Fields
For `default`:
- `relation`: a `string` feature containing PID of the relation.
- `tokens`: a `list` of `string` features containing tokens for the text.
- `head`: a dictionary containing:
- `text`: a `string` feature representing the head entity.
- `type`: a `string` feature representing the type of the head entity.
- `indices`: a `list` containing `list` of token indices.
- `tail`: a dictionary containing:
- `text`: a `string` feature representing the tail entity.
- `type`: a `string` feature representing the type of the tail entity.
- `indices`: a `list` containing `list` of token indices.
- `names`: a `list` of `string` features containing relation names. For `pubmed_unsupervised` split, this is set to a `list` with an empty `string`. For `val_semeval` and `val_pubmed` split, this is set to a `list` with the `string` from the `relation` field.
### Data Splits
`train_wiki`: 44800
`val_nyt`: 2500
`val_pubmed`: 1000
`val_semeval`: 8851
`val_wiki`: 11200
`pubmed_unsupervised`: 2500
## 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
For FewRel:
Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong
For FewRel 2.0:
Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie
### Licensing Information
```
MIT License
Copyright (c) 2018 THUNLP
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```
### Citation Information
```
@inproceedings{han-etal-2018-fewrel,
title = "{F}ew{R}el: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation",
author = "Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D18-1514",
doi = "10.18653/v1/D18-1514",
pages = "4803--4809"
}
```
```
@inproceedings{gao-etal-2019-fewrel,
title = "{F}ew{R}el 2.0: Towards More Challenging Few-Shot Relation Classification",
author = "Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D19-1649",
doi = "10.18653/v1/D19-1649",
pages = "6251--6256"
}
```
### Contributions
Thanks to [@gchhablani](https://github.com/gchhablani) for adding this dataset. | [
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|
interpress_news_category_tr_lite | null | 2023-01-25T14:33:07Z | 352 | 10 | [
"task_categories:text-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|interpress_news_category_tr",
"language:tr",
"license:unknown",
"news-category-classification",
"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:
- extended|interpress_news_category_tr
task_categories:
- text-classification
task_ids: []
pretty_name: Interpress Turkish News Category Dataset (270K - Lite Version)
tags:
- news-category-classification
dataset_info:
features:
- name: content
dtype: string
- name: category
dtype:
class_label:
names:
'0': kültürsanat
'1': ekonomi
'2': siyaset
'3': eğitim
'4': dünya
'5': spor
'6': teknoloji
'7': magazin
'8': sağlık
'9': gündem
config_name: 270k_10class
splits:
- name: train
num_bytes: 721110711
num_examples: 218880
- name: test
num_bytes: 179348267
num_examples: 54721
download_size: 342920336
dataset_size: 900458978
---
# Dataset Card for Interpress Turkish News Category Dataset (270K - Lite Version)
## 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:** [Interpress](https://www.interpress.com/)
- **Point of Contact:** [Yavuz Komecoglu](mailto:[email protected])
### Dataset Summary
Turkish News Category Dataset (270K - Lite Version) is a Turkish news data set consisting of 273601 news in 10 categories ("kültürsanat", "ekonomi", "siyaset", "eğitim", "dünya", "spor", "teknoloji", "magazin", "sağlık", "gündem"), compiled from printed media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. **It has been rearranged as easily separable and with fewer classes.**
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
The dataset is based on Turkish.
## Dataset Structure
### Data Instances
A text classification dataset with 10 different news category.
Here is an example from the dataset:
```
{
'category': 0,
'content': 'Tarihten Sınıfta Kaldık Bugün tarihe damgasını vuran Osmanlı İmparatorluğu nun kuruluş yıldönümü. Adına dizilerin çekildiği tarihimizi ne kadar biliyoruz? Gerekçeler faklı; ama sonuç aynı çıktı. Tarihten sınıfta kaldık. Sayfa 5r 1 Bugün tarihe damgasını vuran Osmanlı İmparatorluğumun kuruluş yıldönümü. Adına dizilerin çekildiği tarihimizi ne kadar biliyoruz? Gerekçeler faklı; ama sonuç aynı çıktı. Tarihten sınıfta kaldık 7 Ocak 1299... Kıtalara dağılan ücüyle, ülkeler arasında gördüğü aygıyla tarihe damgasını vuran anlı devletin kuruluş tarihi. Peki, anlı tarihimizi ne kadar biliyoruz? on zamanlarda tarihimizi anlatan izilere ilgi nasıl? Bu dizilerde anlatanlar ne kadar sağlıklı? İşte sokaın değerlendirmesi; levlüdiye Karaman (42-Ev lamım): Bir bilgim yok. Tarihle izla ilgilenmiyorum. Eşim daha ilgilidir bu konuda. Evde anlatır, ndan duyduklarımla yetiniyorum esem yalan olmaz. Osmanlı döeminde yaşamak isterdim. Tarih izileri izlerim Muhteşem Yüzyıl izisini çok izledim; hatta hiç kaırmazdım. Ama tarihimiz bu değil. Sunuün bilincindeyim. Muhteşem üzyıl dizisi genelde haremiyle ön landaydı. Onun için tarihi diziden ğrenmeyi de doğru bulmuyorum. )kullarda verilen tarih dersleri yeisiz. Daha çok tanıtabilirler. Görel anlatım yapılsın çocuklarımız aten okumak istemiyor. En azman eğlenceli hale getirip bu şekilde ilgilendirebilirler. erdi Üstün (22-Saatçi): Bu gün Osmanlı Devleti nin kuruluş yıldönümü olduğunu bilmiyordum. O dönemde yaşamak isterdim. Tarih yazılmış neden yaşamak istemeyim ki. Tarihime yeterince hakim olduğumu düşünüyorum. Araştırmalar yapıyorum. Merak ediyorum. Okullarda verilen tarih dersleri yeterli. Tarih dizisi izlemem, televizyondan tarihimi öğrenmek bana mantıklı gelmiyor. Yeterli olabilir; ama hikayeleştiriliyor. Sonuçta olduğu gibi anlatılsa daha iyi olur. Songül Karabacak (40-Ev Hanımı): Kuruluş yıldönümü olduğunu bilmiyordum. Tarih bilgim çok azdır. Zaten biz yaşadığımız dönemde tarih yazıyoruz. Osmanlı Dönemi nde yaşamak istemezdim. Sebebini bilmiyorum; ama hayatımdan memnunum, dönemden de memnunum. Dizileri takip etmiyorum. Ama mutlaka dizilerde tarihimiz doğru yansıtılıyor ki insanlar sürekli takip ediyor. Benim televizyonla pek aram yoktur. Ertuğrul Şahin (47-Çalışmıyor): Kuruluş yıldönümü olduğunu bilmiyordum. Sizden öğrendim. O dönemde yaşamak isterdim. Tarih sonuçta merak ederim. Tarihle ilgili çok bilgim yok. Okumadım, zaten şartlar el vermedi. Okullarda verilen eğitim yeterli değil. Örnek vermek gerekirse; 20 yaşında oğlum var Atatürk ün doğum yılını soruyorum yüzüme bakıyor. Verilen eğitim belli. Konu belirliyorlar onun dışına çıkmıyorlar. Daha fazla bilgi verilebilir. Tabi gençlerimizde de suç var bize baksınlar tarihimizi bilmiyoruz. Onlar araştırma yapsınlar her gün internette geziyorlar faydasız bir şeye bakacaklarına ecdatlarını okusunlar. Tarih dizlerini izlerim. Ama doğru yansıtılıyor mu orasını bilmiyorum sadece izleyiciyim. Ama önceden Süleyman Şah ı duyardım. Büyüklerimiz anlatırdı bunu diziden teyit ettim mesela. Ahmet Efe (22-Muhasebeci): Kuruluş yıldönümü olduğuyla ilgili bir bilgim yok. O dönemde yaşamak isterdim. Aldığımız bilgiler sonucunda illa ki bir özenme oluyor. Tam anlamıyla tarih bilgisine sahip olduğumu düşünmüyorum. Tarihe merakım var aslında; ama çok kısıtlı araştırma yapıyorum. Okullarda verilen tarih dersi yeterli değil. Çünkü şuradan birkaç çocuğu çevirip sorsanız size yeterli bilgi vermez. Veremez onun da bilgisi yok sonuçta. Zaten kısıtlı bilgiler veriliyor. Tarih dizilerini kılıç kalkan kuşanıp izliyorum. Doğru yansıtılıyor bundan dolayı da biraz insanlar tarihini öğrenmeye başladı desek yalan olmaz. Bu ne kadar doğru derseniz de bilgiyi doğru verdikten sonra tabi diziden de tarih öğrenilebilir. Mehmet Ak (28-Satış Danışmanı): Kuruluşunun bugün olduğunu bilmiyordum. O dönemde yaşamak isterdim. Yeterli bilgim yok bence kim tarihi tam anlamıyla öğrenebilir ki zaten. Ama tabi tarih kitapları okuyorum, araştırıyorum. Okullarda verilen tarih derslerini yeterli bulmuyorum; ama daha fazla neler yapılabilir, tarih küçüklere nasıl anlatılır bilmiyorum tek bildiğim yeterli olmadığı. Tarih dizileri gerçeği yüzde 75 yansıtıyor. Bu konuda araştırma yaptım yüzeysel anlatılıyor; fakat yine de bilgi edinilebilecek diziler. En azından rutinleşmiş dizi konularından uzak. Aile ile rahat rahat izleyebilirsin. Hasan Çalık (65-Emekli): Kuruluş yıldönümü olduğunu biliyorum. Araştırma yaparım. O dönemde yaşamak istemezdim Cumhuriyet döneminde yaşamayı daha çok isterdim. Okullarda verilen dersler yeterli. Film ya da dizi okumak yerine kitap okumayı tercih ederim. Bir insan ancak kitap okuyarak aydınlanabilir. Bu şekilde kendini geliştirebilir. Bir ömre ne kadar kitap sığdırırsan o kadar aydın bir insan olursun. Konusu fark etmez ister tarih olsun, ister roman okumak her zaman kazanç sağlar. Bir diziden tarihi ne kadar yeterli öğrenebilirsin ki ya da ne kadar doğru anlatılabilir. Bence diziyi bırakıp kitaplara yönelsinler. Nuray Çelik'
}
```
### Data Fields
- **category** : Indicates to which category the news text belongs.
(Such as "kültürsanat" (0), "ekonomi" (1), "siyaset" (2), "eğitim" (3), "dünya" (4), "spor" (5), "teknoloji" (6), "magazin" (7), "sağlık" (8), "gündem" (9))
- **content** : Contains the text of the news.
### Data Splits
The data is split into a training and testing. The split is organized as the following
| | train | test |
|------------|--------:|-------:|
| data split | 218,880 | 54,721 |
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
[More Information Needed]
#### Initial Data Collection and Normalization
Downloaded over 270,000 news from the printed media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. This data collection compiled from print media and internet news is presented in its raw form. For this reason, it is appropriate to use it with careful pre-processing steps regarding various OCR errors and typos.
#### Who are the source language producers?
Turkish printed news sources and online news sites.
### 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
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
https://www.interpress.com/
### Contributions
Thanks to [@basakbuluz](https://github.com/basakbuluz) & [@yavuzkomecoglu](https://github.com/yavuzkomecoglu) & [@serdarakyol](https://github.com/serdarakyol/) for adding this dataset. | [
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|
zest | null | 2022-11-18T22:05:40Z | 352 | 1 | [
"task_categories:question-answering",
"task_categories:token-classification",
"task_ids:closed-domain-qa",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"output-structure",
"yes-no-qa",
"arxiv:2011.08115",
"region:us"
]
| [
"question-answering",
"token-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
- token-classification
task_ids:
- closed-domain-qa
- extractive-qa
paperswithcode_id: zest
pretty_name: ZEST
tags:
- output-structure
- yes-no-qa
dataset_info:
features:
- name: task_id
dtype: string
- name: question
dtype: string
- name: generalization_type
dtype: string
- name: derives_from
sequence: string
- name: domain
dtype: string
- name: context
dtype: string
- name: answer
sequence: string
- name: all_answers
sequence: string
splits:
- name: train
num_bytes: 9588987
num_examples: 10766
- name: validation
num_bytes: 2056804
num_examples: 2280
- name: test
num_bytes: 9280845
num_examples: 11980
download_size: 5796188
dataset_size: 20926636
---
# Dataset Card for "ZEST: ZEroShot learning from Task descriptions"
## 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://allenai.org/data/zest
- **Repository:** https://github.com/allenai/zest
- **Paper:** https://arxiv.org/abs/2011.08115
- **Leaderboard:** https://leaderboard.allenai.org/zest/submissions/public
- **Point of Contact:**
### Dataset Summary
ZEST tests whether NLP systems can perform unseen tasks in a zero-shot way, given a natural language description of
the task. It is an instantiation of our proposed framework "learning from task descriptions". The tasks include
classification, typed entity extraction and relationship extraction, and each task is paired with 20 different
annotated (input, output) examples. ZEST's structure allows us to systematically test whether models can generalize
in five different ways.
### Supported Tasks and Leaderboards
A [leaderboard](https://leaderboard.allenai.org/zest/submissions/public) is included with accepatbility metrics for
each of the four generalization types outlined in the paper. The metrics are novel acceptability metrics also
proposed by the authors.
### Languages
The dataset is in English.
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
To evaluate the ability of a model to generalize to unseen tasks based only on a task description in a zero-shot
manner.
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
Mechanical Turk crowdsource workers.
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
Mechanical Turk crowdsource workers.
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
The dataset emphasizes a model's ability to generalize to unseen tasks with only a natural language description of
the task. The long-term vision of this type of evaluation is to facilitate the creation of models which can perform
arbitrary tasks with only a prompt from a non-technical user. This could broaden the frontier of what a user can
ask something like a chatbot to do for them, but it is unclear how restrictions would be put in place to prevent
users from prompting a system to perform unethical tasks.
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
This dataset is licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
### Citation Information
```
@inproceedings{weller-etal-2020-learning,
title = "Learning from Task Descriptions",
author = "Weller, Orion and
Lourie, Nicholas and
Gardner, Matt and
Peters, Matthew",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.emnlp-main.105",
pages = "1361--1375",
abstract = "Typically, machine learning systems solve new tasks by training on thousands of examples. In contrast, humans can solve new tasks by reading some instructions, with perhaps an example or two. To take a step toward closing this gap, we introduce a framework for developing NLP systems that solve new tasks after reading their descriptions, synthesizing prior work in this area. We instantiate this frame- work with a new English language dataset, ZEST, structured for task-oriented evaluation on unseen tasks. Formulating task descriptions as questions, we ensure each is general enough to apply to many possible inputs, thus comprehensively evaluating a model{'}s ability to solve each task. Moreover, the dataset{'}s structure tests specific types of systematic generalization. We find that the state-of-the-art T5 model achieves a score of 12% on ZEST, leaving a significant challenge for NLP researchers.",
}
```
### Contributions
Thanks to [@joeddav](https://github.com/joeddav) for adding this dataset. | [
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|
celikmus/mayo_clinic_symptoms_and_diseases_v1 | celikmus | 2023-07-16T19:37:52Z | 352 | 7 | [
"language:en",
"region:us"
]
| null | 2023-03-21T21:31:15Z | ---
language: en
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 1321926
num_examples: 1058
download_size: 626009
dataset_size: 1321926
---
# Dataset Card for "mayo_clinic_symptoms_and_diseases_v1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
C-MTEB/ATEC | C-MTEB | 2023-07-28T13:53:38Z | 352 | 2 | [
"region:us"
]
| null | 2023-07-28T13:53:23Z | ---
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: 5689779
num_examples: 62477
- name: validation
num_bytes: 1823903
num_examples: 20000
- name: test
num_bytes: 1824603
num_examples: 20000
download_size: 5073390
dataset_size: 9338285
---
# Dataset Card for "ATEC"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
OGB/ogbg-molhiv | OGB | 2023-02-07T16:39:46Z | 351 | 3 | [
"task_categories:graph-ml",
"license:mit",
"region:us"
]
| [
"graph-ml"
]
| 2022-07-06T15:28:13Z | ---
license: mit
task_categories:
- graph-ml
---
# Dataset Card for ogbg-molhiv
## 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)
- [External Use](#external-use)
- [PyGeometric](#pygeometric)
- [Dataset Structure](#dataset-structure)
- [Data Properties](#data-properties)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **[Homepage](https://ogb.stanford.edu/docs/graphprop/#ogbg-mol)**
- **[Repository](https://github.com/snap-stanford/ogb):**:
- **Paper:**: Open Graph Benchmark: Datasets for Machine Learning on Graphs (see citation)
- **Leaderboard:**: [OGB leaderboard](https://ogb.stanford.edu/docs/leader_graphprop/#ogbg-molhiv) and [Papers with code leaderboard](https://paperswithcode.com/sota/graph-property-prediction-on-ogbg-molhiv)
### Dataset Summary
The `ogbg-molhiv` dataset is a small molecular property prediction dataset, adapted from MoleculeNet by teams at Stanford, to be a part of the Open Graph Benchmark.
### Supported Tasks and Leaderboards
`ogbg-molhiv` should be used for molecular property prediction (aiming to predict whether molecules inhibit HIV or not), a binary classification task. The score used is ROC-AUC.
The associated leaderboards are here: [OGB leaderboard](https://ogb.stanford.edu/docs/leader_graphprop/#ogbg-molhiv) and [Papers with code leaderboard](https://paperswithcode.com/sota/graph-property-prediction-on-ogbg-molhiv).
## External Use
### PyGeometric
To load in PyGeometric, do the following:
```python
from datasets import load_dataset
from torch_geometric.data import Data
from torch_geometric.loader import DataLoader
ogbg_molhiv = load_dataset("graphs-datasets/ogbg-molhiv")
# For the train set (replace by valid or test as needed)
ogbg_molhiv_pg_list = [Data(graph) for graph in ogbg_molhiv["train"]]
ogbg_molhiv_pg = DataLoader(ogbg_molhiv_pg_list)
```
## Dataset Structure
### Data Properties
| property | value |
|---|---|
| scale | small |
| #graphs | 41,127 |
| average #nodes | 25.5 |
| average #edges | 27.5 |
| average node degree | 2.2 |
| average cluster coefficient | 0.002 |
| MaxSCC ratio | 0.993 |
| graph diameter | 12.0 |
### Data Fields
Each row of a given file is a graph, with:
- `node_feat` (list: #nodes x #node-features): nodes
- `edge_index` (list: 2 x #edges): pairs of nodes constituting edges
- `edge_attr` (list: #edges x #edge-features): for the aforementioned edges, contains their features
- `y` (list: 1 x #labels): contains the number of labels available to predict (here 1, equal to zero or one)
- `num_nodes` (int): number of nodes of the graph
### Data Splits
This data comes from the PyGeometric version of the dataset provided by OGB, and follows the provided data splits.
This information can be found back using
```python
from ogb.graphproppred import PygGraphPropPredDataset
dataset = PygGraphPropPredDataset(name = 'ogbg-molhiv')
split_idx = dataset.get_idx_split()
train = dataset[split_idx['train']] # valid, test
```
## Additional Information
### Licensing Information
The dataset has been released under MIT license.
### Citation Information
```
@inproceedings{hu-etal-2020-open,
author = {Weihua Hu and
Matthias Fey and
Marinka Zitnik and
Yuxiao Dong and
Hongyu Ren and
Bowen Liu and
Michele Catasta and
Jure Leskovec},
editor = {Hugo Larochelle and
Marc Aurelio Ranzato and
Raia Hadsell and
Maria{-}Florina Balcan and
Hsuan{-}Tien Lin},
title = {Open Graph Benchmark: Datasets for Machine Learning on Graphs},
booktitle = {Advances in Neural Information Processing Systems 33: Annual Conference
on Neural Information Processing Systems 2020, NeurIPS 2020, December
6-12, 2020, virtual},
year = {2020},
url = {https://proceedings.neurips.cc/paper/2020/hash/fb60d411a5c5b72b2e7d3527cfc84fd0-Abstract.html},
}
```
### Contributions
Thanks to [@clefourrier](https://github.com/clefourrier) for adding this dataset. | [
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|
reshinthadith/2048_has_code_filtered_base_code_review_python | reshinthadith | 2023-01-19T20:11:02Z | 351 | 0 | [
"region:us"
]
| null | 2023-01-19T20:10:34Z | ---
dataset_info:
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splits:
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num_bytes: 34984009.92705029
num_examples: 6398
download_size: 18050163
dataset_size: 34984009.92705029
---
# Dataset Card for "2048_has_code_filtered_base_code_review_python"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
AnanthZeke/oscar_tamil_2201 | AnanthZeke | 2023-04-05T15:40:53Z | 351 | 0 | [
"region:us"
]
| null | 2023-04-05T04:21:27Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: sent_token
sequence: string
splits:
- name: train
num_bytes: 18576297122
num_examples: 556772
download_size: 6242500521
dataset_size: 18576297122
---
# Dataset Card for "oscar_tamil_2201"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
nampdn-ai/tiny-textbooks | nampdn-ai | 2023-10-04T03:56:50Z | 351 | 67 | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:en",
"license:cc-by-nc-sa-4.0",
"arxiv:2309.05463",
"arxiv:2306.01116",
"arxiv:2304.08442",
"arxiv:2305.07759",
"doi:10.57967/hf/1126",
"region:us"
]
| [
"text-generation"
]
| 2023-08-10T09:21:07Z | ---
task_categories:
- text-generation
language:
- en
pretty_name: Tiny Textbooks
size_categories:
- 100K<n<1M
license: cc-by-nc-sa-4.0
---
# Textbook-like Dataset: A High-Quality Resource for Small Language Models
The idea is simply inspired by the [Textbooks Are All You Need II: phi-1.5 technical report](https://arxiv.org/abs/2309.05463) paper. The source texts in this dataset have been gathered and carefully select the best of the [falcon-refinedweb](https://arxiv.org/abs/2306.01116) and [minipile](https://arxiv.org/abs/2304.08442) datasets to ensure the diversity, quality while tiny in size. The dataset was synthesized using 4x3090 Ti cards over a period of 500 hours, thanks to [Nous-Hermes-Llama2-13b](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b) finetuned model.
Why settle for low-quality text when you can train on a high-quality, textbook-like dataset? Training language models on subpar text can lead to several issues:
1. **Noise**: Such text often contains typos, grammatical errors, and poorly structured sentences, which can confuse models and degrade performance.
2. **Misinformation**: Low-quality web text may contain incorrect or misleading information, leading to models propagating these inaccuracies.
3. **Lack of Depth**: Subpar text often lacks the depth and detail found in high-quality content, limiting a model's understanding of complex topics.
Conversely, training on my clean and high-quality dataset offers numerous advantages:
1. **Accuracy**: The theoretical concepts in my dataset provide near accurate and detailed information, akin to a well-written textbook. (Need more contribute for facts check)
2. **Context**: Practical examples demonstrate how these concepts apply in real-world situations, offering valuable context.
3. **Performance**: Models trained on high-quality data can generate more accurate, insightful, and human-like text.
A standout feature of this dataset is its volume. It boasts a whopping **420,000 textbook documents**. This extensive collection ensures a wide coverage of topics and concepts, providing your models with a comprehensive and diverse learning resource.
Moreover, this dataset is generated using an open-source language model, ensuring the data is open for every researcher to process. I love the openness and that's why I want to contribute this dataset for the community to push over the limit.
Quality over quantity is a principle that holds true even in machine learning. Training on a large amount of low-quality tokens can lead to models learning and propagating the noise, inaccuracies, and poor structures present in the bad text. This can result in models that generate less accurate and less coherent outputs.
On the other hand, training on a smaller amount of high-quality tokens, like those in this dataset, can yield significantly better results. High-quality tokens provide accurate, well-structured, and meaningful information from which models can learn effectively. This leads to models that can generate more accurate, insightful, and human-like text.
In essence, it's about making every token count. Each high-quality token that a model learns from is a step towards better performance. So why waste computational resources and learning capacity on bad tokens when you can focus on high-quality ones? It's a more efficient and effective approach to training language models.
Choosing high-quality dataset over low-quality web text is akin to opting for a reliable textbook over scattered internet articles. This choice can significantly enhance the performance and reliability of your causal language models.
I'm excited to present this unique blend of theoretical concepts and practical examples designed to supercharge your causal language models. This isn't just another dataset; it's a high-quality resource that can help your models learn more effectively and with better common sense.
I hope this dataset is an useful resource for ML researchers working with small causal language models. I eagerly await your feedback and suggestions as I continue to refine and expand the dataset. Together, let's push the boundaries of what's possible with a **tiny language models**!
## Visualization
[Nomic Atlas](https://atlas.nomic.ai/map/0348f3f7-9280-404f-b6d3-d0b5993a6693/846bcd82-fcc5-474d-b24b-82d1b791f80b) 230k data points visualized thanks to Nomic AI platform.
### Disclaimer
While every effort has been made to ensure the accuracy of the information contained within this dataset, please note that it is provided 'as is' and without any warranties.
The use of the `textbook` field in this dataset is intended for research purposes only. You are advised to verify any information obtained from this dataset before acting upon it.
## Tiny Series
Explore the possibilities and limitations of building Small Language Models with these tiny gems of data!
- [TinyStories](https://arxiv.org/abs/2305.07759): The paper that sparked my interest in the journey of the tiny-* series.
- [tiny-codes](https://huggingface.co/datasets/nampdn-ai/tiny-codes): Collection of 1.6M short and clear code snippets that can help LLM models learn how to reason.
- [tiny-orca-textbooks](https://huggingface.co/datasets/nampdn-ai/tiny-orca-textbooks): Synthetic textbook to help model learn in-context on how it should perform task the right way.
- [tiny-webtext](https://huggingface.co/datasets/nampdn-ai/tiny-webtext): A 6GB (4.5M records) variety of diverse webtext enriched with critical thinking methods to make unbiased English dataset.
- [tiny-lessons](https://huggingface.co/datasets/nampdn-ai/tiny-lessons): Subset of this dataset, various lessons about "things of internet" augmented in a bite-sized textbook Markdown format.
- [tiny-bridgedict](https://huggingface.co/datasets/nampdn-ai/tiny-bridgedict): A dataset that links and transfers knowledge between English, Vietnamese, Chinese in a tiny multilingual models.
### Others small HQ datasets with textbook-like quality
- [devdocs.io](https://huggingface.co/datasets/nampdn-ai/devdocs.io): FreeCodeCamp has provided 189k comprehensive API documentation across a wide range of tech stacks and programming languages.
- [sciphi-python-textbook](https://huggingface.co/datasets/emrgnt-cmplxty/sciphi-python-textbook)
- [textbook_quality_programming](https://huggingface.co/datasets/vikp/textbook_quality_programming)
- [sciphi-textbooks-are-all-you-need](https://huggingface.co/datasets/emrgnt-cmplxty/sciphi-textbooks-are-all-you-need) | [
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|
taishi-i/awesome-japanese-nlp-classification-dataset | taishi-i | 2023-09-09T11:09:04Z | 351 | 3 | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"language:ja",
"license:other",
"code",
"region:us"
]
| [
"text-classification"
]
| 2023-09-09T06:37:36Z | ---
license: other
task_categories:
- text-classification
language:
- en
- ja
tags:
- code
size_categories:
- 1K<n<10K
---
# Dataset overview
This dataset identifies whether a GitHub repository description pertains to Japanese natural language processing (NLP).
The labels are categorized as **"Relevant (1)" and "Not Relevant (0)"**.
Problem Setting:
- Training Data: Repository descriptions from before 2022
- Test Data: Repository descriptions from 2023
- Objective: To detect repositories related to Japanese NLP
Data Collection:
- Positive Examples: Repositories listed in "[awesome-japanese-nlp-resources](https://github.com/taishi-i/awesome-japanese-nlp-resources)" as of September 9, 2023
- Negative Examples: Collected from the GitHub API and visually confirmed
- Note: The annotation process is subjective
Dataset Features:
- Subjective labeling
- Mixed English and Japanese descriptions
- Imbalanced label distribution
**These dataset features mirror real-world challenges and are ideal for evaluating models.**
Based on GitHub's terms of service, please use this dataset for research purposes only.
# How to use this dataset
How to load in Python.
```python
from datasets import load_dataset
dataset = load_dataset("taishi-i/awesome-japanese-nlp-classification-dataset")
```
Details of the dataset.
```python
DatasetDict({
train: Dataset({
features: ['label', 'text', 'url', 'created_at'],
num_rows: 5496
})
validation: Dataset({
features: ['label', 'text', 'url', 'created_at'],
num_rows: 400
})
test: Dataset({
features: ['label', 'text', 'url', 'created_at'],
num_rows: 856
})
})
```
# Baseline
Baseline trained with [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased).
Please use the baseline model from [here](https://huggingface.co/taishi-i/awesome-japanese-nlp-classification-model).
The F1-score for label 1 is important for this task.
| Label | Precision | Recall | F1-Score | Support |
|--------------|-----------|--------|----------|---------|
| 0 | 0.98 | 0.99 | 0.98 | 796 |
| 1 | 0.79 | 0.70 | **0.74** | 60 |
| Accuracy | | | 0.97 | 856 |
| Macro Avg | 0.89 | 0.84 | 0.86 | 856 |
| Weighted Avg | 0.96 | 0.97 | 0.97 | 856 |
# Dataset stats
Label distribution:
| Dataset | Label 0 (%) | Label 1 (%) |
|------------|-------------|-------------|
| Train | 92.59 | 7.41 |
| Validation | 95.75 | 4.25 |
| Test | 92.99 | 7.01 |
Relevant sample:
```python
{
"label": 1,
"text": "JGLUE: Japanese General Language Understanding Evaluation for huggingface datasets",
"url": "https://github.com/shunk031/huggingface-datasets_JGLUE",
"created_at": "2023-02-25T04:33:03Z"
}
```
Not Relevant sample:
```python
{
"label": 0,
"text": "Official repository of FaceLit: Neural 3D Relightable Faces (CVPR 2023)",
"url": "https://github.com/apple/ml-facelit",
"created_at": "2023-04-03T22:47:29Z"
}
```
Number of texts, average number of characters per text, minimum number of characters, maximum number of characters:
| Dataset | Text Count | Average Length | Min Length | Max Length |
|------------|------------|----------------|------------|------------|
| Train | 5496 | 58.05 | 2.0 | 609.0 |
| Validation | 400 | 54.33 | 8.0 | 226.0 |
| Test | 856 | 58.85 | 3.0 | 341.0 |
Proportion of text languages:
| Dataset | English (%) | Japanese (%) |
|------------|-------------|--------------|
| Train | 89.34 | 10.66 |
| Validation | 82.00 | 18.00 |
| Test | 83.18 | 16.82 |
Time range:
| Dataset | Start Date | End Date |
|---------|---------------------------|---------------------------|
| Train | 2008-02-11 22:55:26+00:00 | 2022-09-30 19:45:09+00:00 |
| Validation | 2022-10-01 06:02:56+00:00 | 2022-12-31 12:12:41+00:00 |
| Test | 2023-01-01 06:15:03+00:00 | 2023-08-21 15:30:53+00:00 |
# License
We collect and publish this dataset under [GitHub Acceptable Use Policies - 7. Information Usage Restrictions](https://docs.github.com/en/site-policy/acceptable-use-policies/github-acceptable-use-policies#7-information-usage-restrictions) and [GitHub Terms of Service - H. API Terms](https://docs.github.com/en/site-policy/github-terms/github-terms-of-service#h-api-terms) for research purposes. This dataset should be used solely for research verification purposes. Adhering to GitHub's regulations is mandatory.
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|
open-llm-leaderboard/details_chavinlo__alpaca-native | open-llm-leaderboard | 2023-09-21T20:24:38Z | 351 | 0 | [
"region:us"
]
| null | 2023-09-17T15:14:52Z | ---
pretty_name: Evaluation run of chavinlo/alpaca-native
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [chavinlo/alpaca-native](https://huggingface.co/chavinlo/alpaca-native) 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_chavinlo__alpaca-native\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-09-21T20:23:20.255556](https://huggingface.co/datasets/open-llm-leaderboard/details_chavinlo__alpaca-native/blob/main/results_2023-09-21T20-23-20.255556.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\": 0.41927597389078103,\n\
\ \"acc_stderr\": 0.035302205782678654,\n \"acc_norm\": 0.42235476219088836,\n\
\ \"acc_norm_stderr\": 0.035290265393035695,\n \"mc1\": 0.2484700122399021,\n\
\ \"mc1_stderr\": 0.015127427096520674,\n \"mc2\": 0.3759916250814691,\n\
\ \"mc2_stderr\": 0.015396201572279763\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5127986348122867,\n \"acc_stderr\": 0.014606603181012538,\n\
\ \"acc_norm\": 0.5204778156996587,\n \"acc_norm_stderr\": 0.01459913135303501\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5959968133837881,\n\
\ \"acc_stderr\": 0.004896952378506926,\n \"acc_norm\": 0.7699661422027485,\n\
\ \"acc_norm_stderr\": 0.004199941217549452\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542129,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542129\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.45925925925925926,\n\
\ \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.45925925925925926,\n\
\ \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.3618421052631579,\n \"acc_stderr\": 0.03910525752849724,\n\
\ \"acc_norm\": 0.3618421052631579,\n \"acc_norm_stderr\": 0.03910525752849724\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.46,\n\
\ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.46,\n \
\ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.44150943396226416,\n \"acc_stderr\": 0.030561590426731837,\n\
\ \"acc_norm\": 0.44150943396226416,\n \"acc_norm_stderr\": 0.030561590426731837\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3819444444444444,\n\
\ \"acc_stderr\": 0.040629907841466674,\n \"acc_norm\": 0.3819444444444444,\n\
\ \"acc_norm_stderr\": 0.040629907841466674\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\
: 0.41,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.3815028901734104,\n\
\ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.3815028901734104,\n\
\ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237656,\n\
\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237656\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n\
\ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.37446808510638296,\n \"acc_stderr\": 0.03163910665367291,\n\
\ \"acc_norm\": 0.37446808510638296,\n \"acc_norm_stderr\": 0.03163910665367291\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2543859649122807,\n\
\ \"acc_stderr\": 0.040969851398436716,\n \"acc_norm\": 0.2543859649122807,\n\
\ \"acc_norm_stderr\": 0.040969851398436716\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.36551724137931035,\n \"acc_stderr\": 0.040131241954243856,\n\
\ \"acc_norm\": 0.36551724137931035,\n \"acc_norm_stderr\": 0.040131241954243856\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.28835978835978837,\n \"acc_stderr\": 0.023330654054535903,\n \"\
acc_norm\": 0.28835978835978837,\n \"acc_norm_stderr\": 0.023330654054535903\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.24603174603174602,\n\
\ \"acc_stderr\": 0.03852273364924314,\n \"acc_norm\": 0.24603174603174602,\n\
\ \"acc_norm_stderr\": 0.03852273364924314\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\"\
: 0.4290322580645161,\n \"acc_stderr\": 0.02815603653823321,\n \"\
acc_norm\": 0.4290322580645161,\n \"acc_norm_stderr\": 0.02815603653823321\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.3103448275862069,\n \"acc_stderr\": 0.03255086769970103,\n \"\
acc_norm\": 0.3103448275862069,\n \"acc_norm_stderr\": 0.03255086769970103\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.45,\n\
\ \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.5333333333333333,\n \"acc_stderr\": 0.038956580652718446,\n\
\ \"acc_norm\": 0.5333333333333333,\n \"acc_norm_stderr\": 0.038956580652718446\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.4797979797979798,\n \"acc_stderr\": 0.035594435655639196,\n \"\
acc_norm\": 0.4797979797979798,\n \"acc_norm_stderr\": 0.035594435655639196\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.6062176165803109,\n \"acc_stderr\": 0.035260770955482405,\n\
\ \"acc_norm\": 0.6062176165803109,\n \"acc_norm_stderr\": 0.035260770955482405\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.3871794871794872,\n \"acc_stderr\": 0.024697216930878948,\n\
\ \"acc_norm\": 0.3871794871794872,\n \"acc_norm_stderr\": 0.024697216930878948\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.26296296296296295,\n \"acc_stderr\": 0.02684205787383371,\n \
\ \"acc_norm\": 0.26296296296296295,\n \"acc_norm_stderr\": 0.02684205787383371\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.35294117647058826,\n \"acc_stderr\": 0.031041941304059295,\n\
\ \"acc_norm\": 0.35294117647058826,\n \"acc_norm_stderr\": 0.031041941304059295\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.31125827814569534,\n \"acc_stderr\": 0.03780445850526733,\n \"\
acc_norm\": 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526733\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.544954128440367,\n \"acc_stderr\": 0.021350503090925173,\n \"\
acc_norm\": 0.544954128440367,\n \"acc_norm_stderr\": 0.021350503090925173\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.375,\n \"acc_stderr\": 0.033016908987210894,\n \"acc_norm\": 0.375,\n\
\ \"acc_norm_stderr\": 0.033016908987210894\n },\n \"harness|hendrycksTest-high_school_us_history|5\"\
: {\n \"acc\": 0.5343137254901961,\n \"acc_stderr\": 0.03501038327635897,\n\
\ \"acc_norm\": 0.5343137254901961,\n \"acc_norm_stderr\": 0.03501038327635897\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.5654008438818565,\n \"acc_stderr\": 0.03226759995510145,\n \
\ \"acc_norm\": 0.5654008438818565,\n \"acc_norm_stderr\": 0.03226759995510145\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5022421524663677,\n\
\ \"acc_stderr\": 0.03355746535223263,\n \"acc_norm\": 0.5022421524663677,\n\
\ \"acc_norm_stderr\": 0.03355746535223263\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.4122137404580153,\n \"acc_stderr\": 0.04317171194870254,\n\
\ \"acc_norm\": 0.4122137404580153,\n \"acc_norm_stderr\": 0.04317171194870254\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.5454545454545454,\n \"acc_stderr\": 0.045454545454545484,\n \"\
acc_norm\": 0.5454545454545454,\n \"acc_norm_stderr\": 0.045454545454545484\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4444444444444444,\n\
\ \"acc_stderr\": 0.04803752235190192,\n \"acc_norm\": 0.4444444444444444,\n\
\ \"acc_norm_stderr\": 0.04803752235190192\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.3987730061349693,\n \"acc_stderr\": 0.03847021420456025,\n\
\ \"acc_norm\": 0.3987730061349693,\n \"acc_norm_stderr\": 0.03847021420456025\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\": 0.47572815533980584,\n \"acc_stderr\": 0.049449010929737795,\n\
\ \"acc_norm\": 0.47572815533980584,\n \"acc_norm_stderr\": 0.049449010929737795\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6068376068376068,\n\
\ \"acc_stderr\": 0.03199957924651047,\n \"acc_norm\": 0.6068376068376068,\n\
\ \"acc_norm_stderr\": 0.03199957924651047\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\
: 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-miscellaneous|5\"\
: {\n \"acc\": 0.5504469987228607,\n \"acc_stderr\": 0.017788725283507337,\n\
\ \"acc_norm\": 0.5504469987228607,\n \"acc_norm_stderr\": 0.017788725283507337\n\
\ },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.42485549132947975,\n\
\ \"acc_stderr\": 0.026613350840261736,\n \"acc_norm\": 0.42485549132947975,\n\
\ \"acc_norm_stderr\": 0.026613350840261736\n },\n \"harness|hendrycksTest-moral_scenarios|5\"\
: {\n \"acc\": 0.2424581005586592,\n \"acc_stderr\": 0.014333522059217889,\n\
\ \"acc_norm\": 0.2424581005586592,\n \"acc_norm_stderr\": 0.014333522059217889\n\
\ },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.4117647058823529,\n\
\ \"acc_stderr\": 0.028180596328259293,\n \"acc_norm\": 0.4117647058823529,\n\
\ \"acc_norm_stderr\": 0.028180596328259293\n },\n \"harness|hendrycksTest-philosophy|5\"\
: {\n \"acc\": 0.4662379421221865,\n \"acc_stderr\": 0.028333277109562793,\n\
\ \"acc_norm\": 0.4662379421221865,\n \"acc_norm_stderr\": 0.028333277109562793\n\
\ },\n \"harness|hendrycksTest-prehistory|5\": {\n \"acc\": 0.4722222222222222,\n\
\ \"acc_stderr\": 0.027777777777777804,\n \"acc_norm\": 0.4722222222222222,\n\
\ \"acc_norm_stderr\": 0.027777777777777804\n },\n \"harness|hendrycksTest-professional_accounting|5\"\
: {\n \"acc\": 0.30851063829787234,\n \"acc_stderr\": 0.027553366165101362,\n\
\ \"acc_norm\": 0.30851063829787234,\n \"acc_norm_stderr\": 0.027553366165101362\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3213820078226858,\n\
\ \"acc_stderr\": 0.011927581352265076,\n \"acc_norm\": 0.3213820078226858,\n\
\ \"acc_norm_stderr\": 0.011927581352265076\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.40441176470588236,\n \"acc_stderr\": 0.029812630701569743,\n\
\ \"acc_norm\": 0.40441176470588236,\n \"acc_norm_stderr\": 0.029812630701569743\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.3790849673202614,\n \"acc_stderr\": 0.019627444748412232,\n \
\ \"acc_norm\": 0.3790849673202614,\n \"acc_norm_stderr\": 0.019627444748412232\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.44545454545454544,\n\
\ \"acc_stderr\": 0.047605488214603246,\n \"acc_norm\": 0.44545454545454544,\n\
\ \"acc_norm_stderr\": 0.047605488214603246\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.40408163265306124,\n \"acc_stderr\": 0.031414708025865885,\n\
\ \"acc_norm\": 0.40408163265306124,\n \"acc_norm_stderr\": 0.031414708025865885\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.472636815920398,\n\
\ \"acc_stderr\": 0.03530235517334682,\n \"acc_norm\": 0.472636815920398,\n\
\ \"acc_norm_stderr\": 0.03530235517334682\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.4036144578313253,\n\
\ \"acc_stderr\": 0.038194861407583984,\n \"acc_norm\": 0.4036144578313253,\n\
\ \"acc_norm_stderr\": 0.038194861407583984\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.5263157894736842,\n \"acc_stderr\": 0.03829509868994727,\n\
\ \"acc_norm\": 0.5263157894736842,\n \"acc_norm_stderr\": 0.03829509868994727\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2484700122399021,\n\
\ \"mc1_stderr\": 0.015127427096520674,\n \"mc2\": 0.3759916250814691,\n\
\ \"mc2_stderr\": 0.015396201572279763\n }\n}\n```"
repo_url: https://huggingface.co/chavinlo/alpaca-native
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_21T20_23_20.255556
path:
- '**/details_harness|arc:challenge|25_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T15_14_48.848140
path:
- '**/details_harness|drop|3_2023-09-17T15-14-48.848140.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T15-14-48.848140.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T15_14_48.848140
path:
- '**/details_harness|gsm8k|5_2023-09-17T15-14-48.848140.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T15-14-48.848140.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hellaswag|10_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-21T20-23-20.255556.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_21T20_23_20.255556
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-21T20-23-20.255556.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-21T20-23-20.255556.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T15_14_48.848140
path:
- '**/details_harness|winogrande|5_2023-09-17T15-14-48.848140.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T15-14-48.848140.parquet'
- config_name: results
data_files:
- split: 2023_09_17T15_14_48.848140
path:
- results_2023-09-17T15-14-48.848140.parquet
- split: 2023_09_21T20_23_20.255556
path:
- results_2023-09-21T20-23-20.255556.parquet
- split: latest
path:
- results_2023-09-21T20-23-20.255556.parquet
---
# Dataset Card for Evaluation run of chavinlo/alpaca-native
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/chavinlo/alpaca-native
- **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 [chavinlo/alpaca-native](https://huggingface.co/chavinlo/alpaca-native) 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_chavinlo__alpaca-native",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-21T20:23:20.255556](https://huggingface.co/datasets/open-llm-leaderboard/details_chavinlo__alpaca-native/blob/main/results_2023-09-21T20-23-20.255556.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": {
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"acc_stderr": 0.035302205782678654,
"acc_norm": 0.42235476219088836,
"acc_norm_stderr": 0.035290265393035695,
"mc1": 0.2484700122399021,
"mc1_stderr": 0.015127427096520674,
"mc2": 0.3759916250814691,
"mc2_stderr": 0.015396201572279763
},
"harness|arc:challenge|25": {
"acc": 0.5127986348122867,
"acc_stderr": 0.014606603181012538,
"acc_norm": 0.5204778156996587,
"acc_norm_stderr": 0.01459913135303501
},
"harness|hellaswag|10": {
"acc": 0.5959968133837881,
"acc_stderr": 0.004896952378506926,
"acc_norm": 0.7699661422027485,
"acc_norm_stderr": 0.004199941217549452
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.28,
"acc_stderr": 0.04512608598542129,
"acc_norm": 0.28,
"acc_norm_stderr": 0.04512608598542129
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.45925925925925926,
"acc_stderr": 0.04304979692464242,
"acc_norm": 0.45925925925925926,
"acc_norm_stderr": 0.04304979692464242
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.3618421052631579,
"acc_stderr": 0.03910525752849724,
"acc_norm": 0.3618421052631579,
"acc_norm_stderr": 0.03910525752849724
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.46,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.46,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.44150943396226416,
"acc_stderr": 0.030561590426731837,
"acc_norm": 0.44150943396226416,
"acc_norm_stderr": 0.030561590426731837
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.3819444444444444,
"acc_stderr": 0.040629907841466674,
"acc_norm": 0.3819444444444444,
"acc_norm_stderr": 0.040629907841466674
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.41,
"acc_stderr": 0.04943110704237102,
"acc_norm": 0.41,
"acc_norm_stderr": 0.04943110704237102
},
"harness|hendrycksTest-college_mathematics|5": {
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"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.3815028901734104,
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"acc_norm": 0.3815028901734104,
"acc_norm_stderr": 0.03703851193099521
},
"harness|hendrycksTest-college_physics|5": {
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"acc_norm": 0.21568627450980393,
"acc_norm_stderr": 0.04092563958237656
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620332,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620332
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.37446808510638296,
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"acc_norm": 0.37446808510638296,
"acc_norm_stderr": 0.03163910665367291
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.2543859649122807,
"acc_stderr": 0.040969851398436716,
"acc_norm": 0.2543859649122807,
"acc_norm_stderr": 0.040969851398436716
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.36551724137931035,
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"acc_norm": 0.36551724137931035,
"acc_norm_stderr": 0.040131241954243856
},
"harness|hendrycksTest-elementary_mathematics|5": {
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"acc_norm": 0.28835978835978837,
"acc_norm_stderr": 0.023330654054535903
},
"harness|hendrycksTest-formal_logic|5": {
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"acc_norm": 0.24603174603174602,
"acc_norm_stderr": 0.03852273364924314
},
"harness|hendrycksTest-global_facts|5": {
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"acc_norm": 0.33,
"acc_norm_stderr": 0.047258156262526045
},
"harness|hendrycksTest-high_school_biology|5": {
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"acc_norm": 0.4290322580645161,
"acc_norm_stderr": 0.02815603653823321
},
"harness|hendrycksTest-high_school_chemistry|5": {
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"acc_stderr": 0.03255086769970103,
"acc_norm": 0.3103448275862069,
"acc_norm_stderr": 0.03255086769970103
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.45,
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"acc_norm_stderr": 0.05
},
"harness|hendrycksTest-high_school_european_history|5": {
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"acc_norm_stderr": 0.038956580652718446
},
"harness|hendrycksTest-high_school_geography|5": {
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"acc_norm_stderr": 0.035594435655639196
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.6062176165803109,
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"acc_norm": 0.6062176165803109,
"acc_norm_stderr": 0.035260770955482405
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.3871794871794872,
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"acc_norm_stderr": 0.024697216930878948
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.26296296296296295,
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"acc_norm": 0.26296296296296295,
"acc_norm_stderr": 0.02684205787383371
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.35294117647058826,
"acc_stderr": 0.031041941304059295,
"acc_norm": 0.35294117647058826,
"acc_norm_stderr": 0.031041941304059295
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.31125827814569534,
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"acc_norm": 0.31125827814569534,
"acc_norm_stderr": 0.03780445850526733
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.544954128440367,
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"acc_norm": 0.544954128440367,
"acc_norm_stderr": 0.021350503090925173
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.375,
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"acc_norm": 0.375,
"acc_norm_stderr": 0.033016908987210894
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.5343137254901961,
"acc_stderr": 0.03501038327635897,
"acc_norm": 0.5343137254901961,
"acc_norm_stderr": 0.03501038327635897
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.5654008438818565,
"acc_stderr": 0.03226759995510145,
"acc_norm": 0.5654008438818565,
"acc_norm_stderr": 0.03226759995510145
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.5022421524663677,
"acc_stderr": 0.03355746535223263,
"acc_norm": 0.5022421524663677,
"acc_norm_stderr": 0.03355746535223263
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.4122137404580153,
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"acc_norm": 0.4122137404580153,
"acc_norm_stderr": 0.04317171194870254
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.5454545454545454,
"acc_stderr": 0.045454545454545484,
"acc_norm": 0.5454545454545454,
"acc_norm_stderr": 0.045454545454545484
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.4444444444444444,
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"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.04803752235190192
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.3987730061349693,
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"acc_norm": 0.3987730061349693,
"acc_norm_stderr": 0.03847021420456025
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.36607142857142855,
"acc_stderr": 0.0457237235873743,
"acc_norm": 0.36607142857142855,
"acc_norm_stderr": 0.0457237235873743
},
"harness|hendrycksTest-management|5": {
"acc": 0.47572815533980584,
"acc_stderr": 0.049449010929737795,
"acc_norm": 0.47572815533980584,
"acc_norm_stderr": 0.049449010929737795
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.6068376068376068,
"acc_stderr": 0.03199957924651047,
"acc_norm": 0.6068376068376068,
"acc_norm_stderr": 0.03199957924651047
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.45,
"acc_stderr": 0.05,
"acc_norm": 0.45,
"acc_norm_stderr": 0.05
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.5504469987228607,
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"acc_norm": 0.5504469987228607,
"acc_norm_stderr": 0.017788725283507337
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.42485549132947975,
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"acc_norm": 0.42485549132947975,
"acc_norm_stderr": 0.026613350840261736
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.2424581005586592,
"acc_stderr": 0.014333522059217889,
"acc_norm": 0.2424581005586592,
"acc_norm_stderr": 0.014333522059217889
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.4117647058823529,
"acc_stderr": 0.028180596328259293,
"acc_norm": 0.4117647058823529,
"acc_norm_stderr": 0.028180596328259293
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.4662379421221865,
"acc_stderr": 0.028333277109562793,
"acc_norm": 0.4662379421221865,
"acc_norm_stderr": 0.028333277109562793
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.4722222222222222,
"acc_stderr": 0.027777777777777804,
"acc_norm": 0.4722222222222222,
"acc_norm_stderr": 0.027777777777777804
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.30851063829787234,
"acc_stderr": 0.027553366165101362,
"acc_norm": 0.30851063829787234,
"acc_norm_stderr": 0.027553366165101362
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.3213820078226858,
"acc_stderr": 0.011927581352265076,
"acc_norm": 0.3213820078226858,
"acc_norm_stderr": 0.011927581352265076
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.40441176470588236,
"acc_stderr": 0.029812630701569743,
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"acc_norm_stderr": 0.029812630701569743
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.3790849673202614,
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"acc_norm": 0.3790849673202614,
"acc_norm_stderr": 0.019627444748412232
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.44545454545454544,
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"acc_norm": 0.44545454545454544,
"acc_norm_stderr": 0.047605488214603246
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.40408163265306124,
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"acc_norm": 0.40408163265306124,
"acc_norm_stderr": 0.031414708025865885
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.472636815920398,
"acc_stderr": 0.03530235517334682,
"acc_norm": 0.472636815920398,
"acc_norm_stderr": 0.03530235517334682
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.59,
"acc_stderr": 0.04943110704237102,
"acc_norm": 0.59,
"acc_norm_stderr": 0.04943110704237102
},
"harness|hendrycksTest-virology|5": {
"acc": 0.4036144578313253,
"acc_stderr": 0.038194861407583984,
"acc_norm": 0.4036144578313253,
"acc_norm_stderr": 0.038194861407583984
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.5263157894736842,
"acc_stderr": 0.03829509868994727,
"acc_norm": 0.5263157894736842,
"acc_norm_stderr": 0.03829509868994727
},
"harness|truthfulqa:mc|0": {
"mc1": 0.2484700122399021,
"mc1_stderr": 0.015127427096520674,
"mc2": 0.3759916250814691,
"mc2_stderr": 0.015396201572279763
}
}
```
### 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] | [
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|
celsowm/cnn_news_ptbr | celsowm | 2023-12-01T03:13:56Z | 351 | 0 | [
"region:us"
]
| null | 2023-11-04T13:04:04Z | ---
dataset_info:
features:
- name: titulo
dtype: string
- name: texto
dtype: string
- name: link
dtype: string
- name: resumo
dtype: string
- name: categoria
dtype: string
- name: data_hora
dtype: string
splits:
- name: train
num_bytes: 9586869
num_examples: 3877
download_size: 5402043
dataset_size: 9586869
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "cnn_news_ptbr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
eli5_category | null | 2022-11-18T20:00:33Z | 350 | 4 | [
"task_categories:text2text-generation",
"task_ids:abstractive-qa",
"task_ids:open-domain-abstractive-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|eli5",
"language:en",
"license:unknown",
"region:us"
]
| [
"text2text-generation"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: ELI5-Category
size_categories:
- 100K<n<1M
source_datasets:
- extended|eli5
task_categories:
- text2text-generation
task_ids:
- abstractive-qa
- open-domain-abstractive-qa
dataset_info:
features:
- name: q_id
dtype: string
- name: title
dtype: string
- name: selftext
dtype: string
- name: category
dtype: string
- name: subreddit
dtype: string
- name: answers
struct:
- name: a_id
sequence: string
- name: text
sequence: string
- name: score
sequence: int32
- name: text_urls
sequence:
sequence: string
- name: title_urls
sequence: string
- name: selftext_urls
sequence: string
splits:
- name: train
num_bytes: 166409797
num_examples: 91772
- name: validation1
num_bytes: 13150585
num_examples: 5446
- name: validation2
num_bytes: 4737744
num_examples: 2375
- name: test
num_bytes: 10419098
num_examples: 5411
download_size: 72921829
dataset_size: 194717224
---
# Dataset Card for ELI5-Category
## 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:** [ELI5-Category homepage](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/)
- **Repository:** [ELI5-Category repository](https://github.com/rexarski/ANLY580-final-project)
- **Point of Contact:** [Jingsong Gao](mailto:[email protected])
### Dataset Summary
The ELI5-Category dataset is a smaller but newer and categorized version of the original ELI5 dataset. It's an English-language dataset of questions and answers gathered from the [r/explainlikeimfive](https://www.reddit.com/r/explainlikeimfive/) subreddit where users ask factual questions requiring paragraph-length or longer answers. After 2017, a tagging system was introduced to this subreddit so that the questions can be categorized into different topics according to their tags. Since the training and validation set is built by questions in different topics, the dataset is expected to alleviate the train/validation overlapping issue in the original [ELI5 dataset](https://huggingface.co/datasets/eli5).
### Supported Tasks and Leaderboards
- `abstractive-qa`, `open-domain-abstractive-qa`: The dataset can be used to train a model for Open Domain Long Form Question Answering. An LFQA model is presented with a non-factoid and asked to retrieve relevant information from a knowledge source (such as [Wikipedia](https://www.wikipedia.org/)), then use it to generate a multi-sentence answer.
### Languages
The text in the dataset is in English, as spoken by Reddit users on the [r/explainlikeimfive](https://www.reddit.com/r/explainlikeimfive/) subreddit. The associated BCP-47 code is `en`.
## Dataset Structure
### Data Instances
The structure of this dataset is very similar to the original [ELI5 dataset](https://huggingface.co/datasets/eli5). A typical data point comprises a question, with a `title` containing the main question and a `selftext` which sometimes elaborates on it, and a list of answers from the forum sorted by scores they obtained. Additionally, the URLs in each of the text fields have been extracted to respective lists and replaced by generic tokens in the text.
In addition to the original ELI5 dataset, the data point also has a `category` field. There are 11 common values of `category` in this dataset: `Biology`,`Chemistry`,`Culture`,`Earth Science`,`Economics`,`Engineering`,`Mathematics`,`Other`,`Physics`,`Psychology`,`Technology`, and a special `category`: `Repost` indicates the same question has been asked before.
An example from the ELI5-Category set looks as follows:
```
{'q_id': '5lcm18',
'title': 'Why do old games running on new hardware still have technical issues ?',
'selftext': 'I am playing some mega man games on my Xbox One and experience slowdown when there are a lot of enemies on screen . but the Xbox One is significantly more powerful than the NES , so why is there still slowdown on this hardware ?',
'category': 'Engineering',
'subreddit': 'explainlikeimfive',
'answers': {'a_id': ['dbuo48e', 'dbusfve'],
'text': ["The XBox is emulating NES hardware and running the emulation at a set speed . If it ran it at as fast as possible , then it would be several times faster than the original NES game and would be unplayable . I ca n't speak for Mega Man exactly , but older games tended to run on a cycle locked to the screen refresh which was a fixed 60Hz or 50Hz . There was only one piece of hardware they ran on , so there was no need to adjust for different hardware speeds .",
"In that case , it 's probably on purpose - they want to emulate the experience as closely as possible , even including the slowdown and sprite flickering . Some emulators let you turn it off , but it 's usually turned on by default . In other cases , like if you 're trying to emulate PS2 games on your PC , the game might just run really slow in general . Even though your PC is way more powerful than a PS2 , it has to \" translate \" from PS2 language to PC language in realtime , which is much more difficult than running PS2 code on the PS2 itself ."],
'score': [13, 3],
'text_urls': [[],[]]},
'title_urls': {'url': []},
'selftext_urls': {'url': []}}
```
### Data Fields
- `q_id`: a string question identifier for each example, corresponding to its ID in the [Pushshift.io](https://files.pushshift.io/reddit/submissions/) Reddit submission dumps
- `subreddit`: always `explainlikeimfive`, indicating which subreddit the question came from
- `category`: tag of the question, the possible values are listed above.
- `title`: title of the question, with URLs extracted and replaced by `URL_n` tokens
- `title_urls`: list of the extracted URLs, the `n`th element of the list was replaced by `URL_n`
- `selftext`: either an empty string or an elaboration of the question
- `selftext_urls`: similar to `title_urls` but for `self_text`
- `answers`: a list of answers, each answer has:
- `a_id`: a string answer identifier for each answer, corresponding to its ID in the [Pushshift.io](https://files.pushshift.io/reddit/comments/) Reddit comments dumps.
- `text`: the answer text with the URLs normalized
- `score`: the number of upvotes - the number of downvotes the answer had received when the dumps were created
- `text_urls`: lists of the extracted URLs for every answer
### Data Splits
In order to avoid having duplicate questions across sets, three non-overlapping subsets of `category` are used in the training, validation and test set. Also, a special validation set contains all the questions in the `Repost` category. A valid retriever-generator model should have consistent performances on both validation sets.
The final split sizes are as follows:
| | Train | Valid | Valid2 |Test |
| ----- | ------ | ----- | ---- | ---- |
| `Biology` | 32769 | | | |
| `Chemistry` | 6633 | | | |
| `Culture` | | 5446 | | |
| `Earth Science` | 677 | | | |
| `Economics` | 5901 | | | |
| `Engineering` | | | | 5411 |
| `Mathematics` | 1912 | | | |
| `Other` | 19312 | | | |
| `Physics` | 10196 | | | |
| `Psychology` | 338 | | | |
| `Technology` | 14034 | | | |
| `Repost` | | | 2375 | |
| **Total** | 91772 | 5446 | 2375 | 5411 |
## Dataset Creation
### Curation Rationale
ELI5-Category was built to provide a testbed for machines to learn how to answer more complex questions, which requires them to find and combine the information in a coherent manner. The dataset was built by gathering questions that were asked by community members of three subreddits, including [r/explainlikeimfive](https://www.reddit.com/r/explainlikeimfive/), along with the answers that were provided by other users. The [rules of the subreddit](https://www.reddit.com/r/explainlikeimfive/wiki/detailed_rules) make this data particularly well suited to training a model for abstractive question answering: the questions need to seek an objective explanation about well-established facts, and the answers provided need to be understandable to a layperson without any particular knowledge domain.
### Source Data
#### Initial Data Collection and Normalization
The data was obtained by filtering submissions and comments from the subreddits of interest from the XML dumps of the [Reddit forum](https://www.reddit.com/) hosted on [Pushshift.io](https://files.pushshift.io/reddit/).
In order to further improve the quality of the selected examples, only questions with a score of at least 2 and at least one answer with a score of at least 2 were selected for the dataset. The dataset questions and answers span a period from January 2017 to June 2021.
#### Who are the source language producers?
The language producers are users of the [r/explainlikeimfive](https://www.reddit.com/r/explainlikeimfive/) subreddit between 2017 and 2021. No further demographic information was available from the data source.
### Annotations
The dataset contains the `category` as an additional annotation for the topics of questions.
#### Annotation process
The dataset is auto-annotated by the tags of posts in the [Reddit forum](https://www.reddit.com/).
#### Who are the annotators?
The annotators are users/administrators of the [r/explainlikeimfive](https://www.reddit.com/r/explainlikeimfive/) subreddit between 2017 and 2021. No further demographic information was available from the data source.
### Personal and Sensitive Information
The authors removed the speaker IDs from the [Pushshift.io](https://files.pushshift.io/reddit/) dumps but did not otherwise anonymize the data. Some questions and answers are about contemporary public figures or individuals who appeared in the news.
## Considerations for Using the Data
### Social Impact of Dataset
The dataset has a similar social impact to the original ELI5 dataset [Social Impact of Dataset](https://huggingface.co/datasets/eli5#social-impact-of-dataset).
### Discussion of Biases
The dataset has similar considerations of biases to the original ELI5 dataset [Discussion of Biases](https://huggingface.co/datasets/eli5#discussion-of-biases).
### Other Known Limitations
The dataset has similar limitations to the original ELI5 dataset [Other Known Limitations](https://huggingface.co/datasets/eli5#other-known-limitations).
## Additional Information
### Dataset Curators
The dataset was initially created by Jingsong Gao, Qinren Zhou, Rui Qiu, during a course project of `ANLY 580`: NLP for Data Analytics at Georgetown University.
### Licensing Information
The licensing status of the dataset hinges on the legal status of the [Pushshift.io](https://files.pushshift.io/reddit/) data which is unclear.
### Citation Information
```
@inproceedings{eli5-category,
author = {Jingsong Gao and
Qingren Zhou and
Rui Qiu},
title = {{ELI5-Category:} A categorized open-domain QA dataset},
year = {2021}
}
```
### Contributions
Thanks to [@jingshenSN2](https://github.com/jingshenSN2), [@QinrenZhou](https://github.com/QinrenZhou), [@rexarski](https://github.com/rexarski) for adding this dataset. | [
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|
thaiqa_squad | null | 2022-11-03T16:15:52Z | 350 | 5 | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|other-thaiqa",
"language:th",
"license:cc-by-nc-sa-3.0",
"region:us"
]
| [
"question-answering"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- th
license:
- cc-by-nc-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|other-thaiqa
task_categories:
- question-answering
task_ids:
- extractive-qa
- open-domain-qa
paperswithcode_id: null
pretty_name: thaiqa-squad
dataset_info:
features:
- name: question_id
dtype: int32
- name: article_id
dtype: int32
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: answer
dtype: string
- name: answer_begin_position
dtype: int32
- name: answer_end_position
dtype: int32
config_name: thaiqa_squad
splits:
- name: train
num_bytes: 47905050
num_examples: 4000
- name: validation
num_bytes: 744813
num_examples: 74
download_size: 10003354
dataset_size: 48649863
---
# Dataset Card for `thaiqa-squad`
## 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:** http://github.com/pythainlp/thaiqa_squad (original `thaiqa` at https://aiforthai.in.th/)
- **Repository:** http://github.com/pythainlp/thaiqa_squad
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**http://github.com/pythainlp/ (original `thaiqa` at https://aiforthai.in.th/)
### Dataset Summary
`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, originally created by [NECTEC](https://www.nectec.or.th/en/) from Wikipedia articles and adapted to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format by [PyThaiNLP](https://github.com/PyThaiNLP/).
### Supported Tasks and Leaderboards
extractive question answering
### Languages
Thai
## Dataset Structure
### Data Instances
```
{'answers': {'answer': ['ฮิกกิ้นส์'], 'answer_begin_position': [528], 'answer_end_position': [537]}, 'article_id': 115035, 'context': '<doc id="115035" url="https://th.wikipedia.org/wiki?curid=115035" title="เบนจี้">เบนจี้ เบนจี้ () เป็นชื่อตัวละครหมาพันทางแสนรู้ ที่ปรากฏอยู่ในภาพยนตร์หลายเรื่องที่เขียนบท และกำกับโดย โจ แคมป์ ในช่วงทศวรรษ 1970 ถึง 1980 ภาพยนตร์เรื่องแรกในชุด ใช้ชื่อเรื่องว่า เบนจี้ เช่นเดียวกับตัวละคร ถ่ายทำที่เมืองดัลลัส รัฐเทกซัส ฉายครั้งแรกในปี พ.ศ. 2517 ภาพยนตร์ได้รับการเสนอชื่อเข้าชิงรางวัลออสการ์ และได้รางวัลลูกโลกทองคำ สาขาเพลงประกอบยอดเยี่ยม จากเพลง Benji\'s Theme (I Feel Love) ร้องโดย ชาร์ลี ริช หมาที่แสดงเป็นเบนจี้ตัวแรก ชื่อว่า ฮิกกิ้นส์ (พ.ศ. 2502 - พ.ศ. 2518) มีอายุถึง 15 ปีแล้วในขณะแสดง หลังจากภาพยนตร์ออกฉายได้ไม่นาน มันก็ตายในปี พ.ศ. 2518เบนจี้ในภาพยนตร์เบนจี้ในภาพยนตร์. - พ.ศ. 2517, Benji (ภาพยนตร์) - พ.ศ. 2520, For the Love of Benji (ภาพยนตร์) - พ.ศ. 2521, Benji\'s Very Own Christmas Story (ภาพยนตร์โทรทัศน์) - พ.ศ. 2523, Oh Heavenly Dog (ภาพยนตร์) - พ.ศ. 2523, Benji at Work (ภาพยนตร์โทรทัศน์) - พ.ศ. 2524, Benji Takes a Dive at Marineland (ภาพยนตร์โทรทัศน์) - พ.ศ. 2526, Benji, Zax & the Alien Prince (ภาพยนตร์ซีรีส์) - พ.ศ. 2530, Benji the Hunted (ภาพยนตร์) - พ.ศ. 2547, Benji: Off the Leash! (ภาพยนตร์) - พ.ศ. 2550, Benji: The Barkening (ภาพยนตร์)</doc>\n', 'question': 'สุนัขตัวแรกรับบทเป็นเบนจี้ในภาพยนตร์เรื่อง Benji ที่ออกฉายในปี พ.ศ. 2517 มีชื่อว่าอะไร', 'question_id': 1}
{'answers': {'answer': ['ชาร์ลี ริช'], 'answer_begin_position': [482], 'answer_end_position': [492]}, 'article_id': 115035, 'context': '<doc id="115035" url="https://th.wikipedia.org/wiki?curid=115035" title="เบนจี้">เบนจี้ เบนจี้ () เป็นชื่อตัวละครหมาพันทางแสนรู้ ที่ปรากฏอยู่ในภาพยนตร์หลายเรื่องที่เขียนบท และกำกับโดย โจ แคมป์ ในช่วงทศวรรษ 1970 ถึง 1980 ภาพยนตร์เรื่องแรกในชุด ใช้ชื่อเรื่องว่า เบนจี้ เช่นเดียวกับตัวละคร ถ่ายทำที่เมืองดัลลัส รัฐเทกซัส ฉายครั้งแรกในปี พ.ศ. 2517 ภาพยนตร์ได้รับการเสนอชื่อเข้าชิงรางวัลออสการ์ และได้รางวัลลูกโลกทองคำ สาขาเพลงประกอบยอดเยี่ยม จากเพลง Benji\'s Theme (I Feel Love) ร้องโดย ชาร์ลี ริช หมาที่แสดงเป็นเบนจี้ตัวแรก ชื่อว่า ฮิกกิ้นส์ (พ.ศ. 2502 - พ.ศ. 2518) มีอายุถึง 15 ปีแล้วในขณะแสดง หลังจากภาพยนตร์ออกฉายได้ไม่นาน มันก็ตายในปี พ.ศ. 2518เบนจี้ในภาพยนตร์เบนจี้ในภาพยนตร์. - พ.ศ. 2517, Benji (ภาพยนตร์) - พ.ศ. 2520, For the Love of Benji (ภาพยนตร์) - พ.ศ. 2521, Benji\'s Very Own Christmas Story (ภาพยนตร์โทรทัศน์) - พ.ศ. 2523, Oh Heavenly Dog (ภาพยนตร์) - พ.ศ. 2523, Benji at Work (ภาพยนตร์โทรทัศน์) - พ.ศ. 2524, Benji Takes a Dive at Marineland (ภาพยนตร์โทรทัศน์) - พ.ศ. 2526, Benji, Zax & the Alien Prince (ภาพยนตร์ซีรีส์) - พ.ศ. 2530, Benji the Hunted (ภาพยนตร์) - พ.ศ. 2547, Benji: Off the Leash! (ภาพยนตร์) - พ.ศ. 2550, Benji: The Barkening (ภาพยนตร์)</doc>\n', 'question': "เพลง Benji's Theme ใช้ประกอบภาพยนตร์เรื่อง Benji ในปีพ.ศ. 2517 ขับร้องโดยใคร", 'question_id': 2035}
```
### Data Fields
```
{
"question_id": question id
"article_id": article id
"context": article texts
"question": question
"answers":
{
"answer": answer text
"answer_begin_position": answer beginning position
"answer_end_position": answer exclusive upper bound position
}
),
}
```
### Data Splits
| | train | valid |
|-------------------------|-------------|-------------|
| # questions | 4000 | 74 |
| # avg words in context | 1186.740750 | 1016.459459 |
| # avg words in question | 14.325500 | 12.743243 |
| # avg words in answer | 3.279750 | 4.608108 |
## Dataset Creation
### Curation Rationale
[PyThaiNLP](https://github.com/PyThaiNLP/) created `thaiqa_squad` as a [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) version of [thaiqa](http://copycatch.in.th/thai-qa-task.html). [thaiqa](https://aiforthai.in.th/corpus.php) is part of [The 2nd Question answering program from Thai Wikipedia](http://copycatch.in.th/thai-qa-task.html) of [National Software Contest 2020](http://nsc.siit.tu.ac.th/GENA2/login.php).
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
Wikipedia authors for contexts and [NECTEC](https://www.nectec.or.th/en/) for questions and answer annotations
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[NECTEC](https://www.nectec.or.th/en/)
### Personal and Sensitive Information
All contents are from Wikipedia. No personal and sensitive information is expected to be included.
## Considerations for Using the Data
### Social Impact of Dataset
- open-domain, extractive question answering in Thai
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
Dataset provided for research purposes only. Please check dataset license for additional information.
The contexts include `<doc>` tags at start and at the end
## Additional Information
### Dataset Curators
[NECTEC](https://www.nectec.or.th/en/) for original [thaiqa](https://aiforthai.in.th/corpus.php). SQuAD formattting by [PyThaiNLP](https://github.com/PyThaiNLP/).
### Licensing Information
CC-BY-NC-SA 3.0
### Citation Information
No clear citation guidelines from source: https://aiforthai.in.th/corpus.php
SQuAD version: https://github.com/PyThaiNLP/thaiqa_squad
### Contributions
Thanks to [@cstorm125](https://github.com/cstorm125) for adding this dataset. | [
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|
llm-book/aio | llm-book | 2023-10-06T00:59:01Z | 350 | 1 | [
"region:us"
]
| null | 2023-07-14T11:41:32Z | ---
dataset_info:
features:
- name: qid
dtype: string
- name: competition
dtype: string
- name: timestamp
dtype: string
- name: section
dtype: string
- name: number
dtype: string
- name: original_question
dtype: string
- name: original_answer
dtype: string
- name: original_additional_info
dtype: string
- name: question
dtype: string
- name: answers
list: string
splits:
- name: train
num_bytes: 9464003
num_examples: 22335
- name: validation
num_bytes: 409779
num_examples: 1000
download_size: 2267163
dataset_size: 9873782
---
# Dataset Card for llm-book/aio
書籍『大規模言語モデル入門』で使用する、「AI王」コンペティションのQAデータセットです。
[AI王の公式ページ](https://sites.google.com/view/project-aio/dataset/)で公開されているデータセットを利用しています。
## Licence
本データセットに含まれる一部のクイズ問題の著作権は [abc/EQIDEN 実行委員会](https://abc-dive.com/portal/)に帰属するものであり、これらのクイズ問題は本書における使用許諾を得ているものです。
本データセットに含まれる一部のクイズ問題は[株式会社キュービック](http://www.qbik.co.jp/)および[株式会社カプリティオ](https://capriccio.tokyo/)に依頼し作成したものであり、これらのクイズ問題は[クリエイティブ・コモンズ表示・継承ライセンス 4.0 (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/deed.ja) ライセンスの下に提供されています。
本データセットにパッセージとして付与されている Wikipedia のコンテンツは、[クリエイティブ・コモンズ表示・継承ライセンス 3.0 (CC BY-SA 3.0)](https://creativecommons.org/licenses/by-sa/3.0/deed.ja) および [GNU 自由文書ライセンス (GFDL)](https://www.gnu.org/licenses/fdl.html) の下に配布されているものです。
クイズ問題のライセンスについて、詳細は[AI王の公式ページ](https://sites.google.com/view/project-aio/dataset/)を参照してください。
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|
open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1 | open-llm-leaderboard | 2023-12-01T14:54:18Z | 350 | 0 | [
"region:us"
]
| null | 2023-09-19T01:00:38Z | ---
pretty_name: Evaluation run of ICBU-NPU/FashionGPT-70B-V1.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [ICBU-NPU/FashionGPT-70B-V1.1](https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 3 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1_public\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-11-09T05:03:34.118440](https://huggingface.co/datasets/open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1_public/blob/main/results_2023-11-09T05-03-34.118440.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\": 0.24800755033557048,\n\
\ \"em_stderr\": 0.004422612027820539,\n \"f1\": 0.40814072986577404,\n\
\ \"f1_stderr\": 0.004137188687530774,\n \"acc\": 0.6205347980131322,\n\
\ \"acc_stderr\": 0.012108370161317753\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.24800755033557048,\n \"em_stderr\": 0.004422612027820539,\n\
\ \"f1\": 0.40814072986577404,\n \"f1_stderr\": 0.004137188687530774\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.41470811220621684,\n \
\ \"acc_stderr\": 0.013570623842304504\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8263614838200474,\n \"acc_stderr\": 0.010646116480331001\n\
\ }\n}\n```"
repo_url: https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_drop_3
data_files:
- split: 2023_11_09T05_03_34.118440
path:
- '**/details_harness|drop|3_2023-11-09T05-03-34.118440.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-11-09T05-03-34.118440.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_11_09T05_03_34.118440
path:
- '**/details_harness|gsm8k|5_2023-11-09T05-03-34.118440.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-11-09T05-03-34.118440.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_11_09T05_03_34.118440
path:
- '**/details_harness|winogrande|5_2023-11-09T05-03-34.118440.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-11-09T05-03-34.118440.parquet'
- config_name: results
data_files:
- split: 2023_11_09T05_03_34.118440
path:
- results_2023-11-09T05-03-34.118440.parquet
- split: latest
path:
- results_2023-11-09T05-03-34.118440.parquet
---
# Dataset Card for Evaluation run of ICBU-NPU/FashionGPT-70B-V1.1
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1
- **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 [ICBU-NPU/FashionGPT-70B-V1.1](https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1_public",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-11-09T05:03:34.118440](https://huggingface.co/datasets/open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1_public/blob/main/results_2023-11-09T05-03-34.118440.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": 0.24800755033557048,
"em_stderr": 0.004422612027820539,
"f1": 0.40814072986577404,
"f1_stderr": 0.004137188687530774,
"acc": 0.6205347980131322,
"acc_stderr": 0.012108370161317753
},
"harness|drop|3": {
"em": 0.24800755033557048,
"em_stderr": 0.004422612027820539,
"f1": 0.40814072986577404,
"f1_stderr": 0.004137188687530774
},
"harness|gsm8k|5": {
"acc": 0.41470811220621684,
"acc_stderr": 0.013570623842304504
},
"harness|winogrande|5": {
"acc": 0.8263614838200474,
"acc_stderr": 0.010646116480331001
}
}
```
### 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] | [
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|
species_800 | null | 2023-06-16T11:33:29Z | 349 | 2 | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
]
| [
"token-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: species800
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B
'2': I
config_name: species_800
splits:
- name: train
num_bytes: 2579096
num_examples: 5734
- name: validation
num_bytes: 385756
num_examples: 831
- name: test
num_bytes: 737760
num_examples: 1631
download_size: 18204624
dataset_size: 3702612
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [SPECIES](https://species.jensenlab.org/)
- **Repository:**
- **Paper:** https://doi.org/10.1371/journal.pone.0065390
- **Leaderboard:**
- **Point of Contact:** [Lars Juhl Jensen](mailto:[email protected])
### Dataset Summary
S800 Corpus: a novel abstract-based manually annotated corpus. S800 comprises 800 PubMed abstracts in which organism mentions were identified and mapped to the corresponding NCBI Taxonomy identifiers.
To increase the corpus taxonomic mention diversity the S800 abstracts were collected by selecting 100 abstracts from the following 8 categories: bacteriology, botany, entomology, medicine, mycology, protistology, virology and zoology. S800 has been annotated with a focus at the species level; however, higher taxa mentions (such as genera, families and orders) have also been considered.
The Species-800 dataset was pre-processed and split based on the dataset of Pyysalo (https://github.com/spyysalo/s800).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
English (`en`).
## Dataset Structure
### Data Instances
```
{'id': '0',
'tokens': ['Methanoregula',
'formicica',
'sp',
'.',
'nov',
'.',
',',
'a',
'methane',
'-',
'producing',
'archaeon',
'isolated',
'from',
'methanogenic',
'sludge',
'.'],
'ner_tags': [1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}
```
### Data Fields
- `id`: Sentence identifier.
- `tokens`: Array of tokens composing a sentence.
- `ner_tags`: Array of tags, where `0` indicates no species mentioned, `1` signals the first token of a species and `2` the subsequent tokens of the species.
### 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
The species-level S800 corpus is subject to Medline restrictions.
### Citation Information
Original data:
```
@article{pafilis2013species,
title={The SPECIES and ORGANISMS resources for fast and accurate identification of taxonomic names in text},
author={Pafilis, Evangelos and Frankild, Sune P and Fanini, Lucia and Faulwetter, Sarah and Pavloudi, Christina and Vasileiadou, Aikaterini and Arvanitidis, Christos and Jensen, Lars Juhl},
journal={PloS one},
volume={8},
number={6},
pages={e65390},
year={2013},
publisher={Public Library of Science}
}
```
Source data of this dataset:
```
@article{10.1093/bioinformatics/btz682,
author = {Lee, Jinhyuk and Yoon, Wonjin and Kim, Sungdong and Kim, Donghyeon and Kim, Sunkyu and So, Chan Ho and Kang, Jaewoo},
title = "{BioBERT: a pre-trained biomedical language representation model for biomedical text mining}",
journal = {Bioinformatics},
volume = {36},
number = {4},
pages = {1234-1240},
year = {2019},
month = {09},
issn = {1367-4803},
doi = {10.1093/bioinformatics/btz682},
url = {https://doi.org/10.1093/bioinformatics/btz682},
eprint = {https://academic.oup.com/bioinformatics/article-pdf/36/4/1234/48983216/bioinformatics\_36\_4\_1234.pdf},
}
```
and
```
https://github.com/spyysalo/s800
```
### Contributions
Thanks to [@edugp](https://github.com/edugp) for adding this dataset. | [
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|
nlpaueb/finer-139 | nlpaueb | 2022-10-23T05:05:03Z | 349 | 13 | [
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:en",
"license:cc-by-sa-4.0",
"arxiv:2203.06482",
"region:us"
]
| [
"structure-prediction",
"named-entity-recognition",
"entity-extraction"
]
| 2022-03-04T10:00:23Z | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: FiNER-139
size_categories:
- 1M<n<10M
source_datasets: []
task_categories:
- structure-prediction
- named-entity-recognition
- entity-extraction
task_ids:
- named-entity-recognition
---
# Dataset Card for FiNER-139
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [SEC-BERT](#sec-bert)
- [About Us](#about-us)
## Dataset Description
- **Homepage:** [FiNER](https://github.com/nlpaueb/finer)
- **Repository:** [FiNER](https://github.com/nlpaueb/finer)
- **Paper:** [FiNER, Loukas et al. (2022)](https://arxiv.org/abs/2203.06482)
- **Point of Contact:** [Manos Fergadiotis](mailto:[email protected])
### Dataset Summary
<div style="text-align: justify">
<strong>FiNER-139</strong> is comprised of 1.1M sentences annotated with <strong>eXtensive Business Reporting Language (XBRL)</strong> tags extracted from annual and quarterly reports of publicly-traded companies in the US.
Unlike other entity extraction tasks, like named entity recognition (NER) or contract element extraction, which typically require identifying entities of a small set of common types (e.g., persons, organizations), FiNER-139 uses a much larger label set of <strong>139 entity types</strong>.
Another important difference from typical entity extraction is that FiNER focuses on numeric tokens, with the correct tag depending mostly on context, not the token itself.
</div>
### Supported Tasks
<div style="text-align: justify">
To promote transparency among shareholders and potential investors, publicly traded companies are required to file periodic financial reports annotated with tags from the eXtensive Business Reporting Language (XBRL), an XML-based language, to facilitate the processing of financial information.
However, manually tagging reports with XBRL tags is tedious and resource-intensive.
We, therefore, introduce <strong>XBRL tagging</strong> as a <strong>new entity extraction task</strong> for the <strong>financial domain</strong> and study how financial reports can be automatically enriched with XBRL tags.
To facilitate research towards automated XBRL tagging we release FiNER-139.
</div>
### Languages
**FiNER-139** is compiled from approximately 10k annual and quarterly **English** reports
## Dataset Structure
### Data Instances
This is a "train" split example:
```json
{
'id': 40
'tokens': ['In', 'March', '2014', ',', 'the', 'Rialto', 'segment', 'issued', 'an', 'additional', '$', '100', 'million', 'of', 'the', '7.00', '%', 'Senior', 'Notes', ',', 'at', 'a', 'price', 'of', '102.25', '%', 'of', 'their', 'face', 'value', 'in', 'a', 'private', 'placement', '.']
'ner_tags': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 37, 0, 0, 0, 41, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
}
```
### Data Fields
**id**: ID of the example <br>
**tokens**: List of tokens for the specific example. <br>
**ner_tags**: List of tags for each token in the example. Tags are provided as integer classes.<br>
If you want to use the class names you can access them as follows:
```python
import datasets
finer_train = datasets.load_dataset("nlpaueb/finer-139", split="train")
finer_tag_names = finer_train.features["ner_tags"].feature.names
```
**finer_tag_names** contains a list of class names corresponding to the integer classes e.g.
```
0 -> "O"
1 -> "B-AccrualForEnvironmentalLossContingencies"
```
### Data Splits
| Training | Validation | Test
| -------- | ---------- | -------
| 900,384 | 112,494 | 108,378
## Dataset Creation
### Curation Rationale
The dataset was curated by [Loukas et al. (2022)](https://arxiv.org/abs/2203.06482) <br>
### Source Data
#### Initial Data Collection and Normalization
<div style="text-align: justify">
FiNER-139 is compiled from approximately 10k annual and quarterly English reports (filings) of publicly traded companies downloaded from the [US Securities
and Exchange Commission's (SEC)](https://www.sec.gov/) [Electronic Data Gathering, Analysis, and Retrieval (EDGAR)](https://www.sec.gov/edgar.shtml) system.
The reports span a 5-year period, from 2016 to 2020. They are annotated with XBRL tags by professional auditors and describe the performance and projections of the companies. XBRL defines approximately 6k entity types from the US-GAAP taxonomy. FiNER-139 is annotated with the 139 most frequent XBRL entity types with at least 1,000 appearances.
We used regular expressions to extract the text notes from the Financial Statements Item of each filing, which is the primary source of XBRL tags in annual and quarterly reports. We used the <strong>IOB2</strong> annotation scheme to distinguish tokens at the beginning, inside, or outside of tagged expressions, which leads to 279 possible token labels.
</div>
### Annotations
#### Annotation process
<div style="text-align: justify">
All the examples were annotated by professional auditors as required by the Securities & Exchange Commission (SEC) legislation.
Even though the gold XBRL tags come from professional auditors there are still some discrepancies. Consult [Loukas et al. (2022)](https://arxiv.org/abs/2203.06482), (Section 9.4) for more details
</div>
#### Who are the annotators?
Professional auditors
### Personal and Sensitive Information
The dataset contains publicly available annual and quarterly reports (filings)
## Additional Information
### Dataset Curators
[Loukas et al. (2022)](https://arxiv.org/abs/2203.06482)
### Licensing Information
<div style="text-align: justify">
Access to SEC's EDGAR public database is free, allowing research of public companies' financial information and operations by reviewing the filings the companies makes with the SEC.
</div>
### Citation Information
If you use this dataset cite the following
```
@inproceedings{loukas-etal-2022-finer,
title = {FiNER: Financial Numeric Entity Recognition for XBRL Tagging},
author = {Loukas, Lefteris and
Fergadiotis, Manos and
Chalkidis, Ilias and
Spyropoulou, Eirini and
Malakasiotis, Prodromos and
Androutsopoulos, Ion and
Paliouras George},
booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022)},
publisher = {Association for Computational Linguistics},
location = {Dublin, Republic of Ireland},
year = {2022},
url = {https://arxiv.org/abs/2203.06482}
}
```
## SEC-BERT
<img align="center" src="https://i.ibb.co/0yz81K9/sec-bert-logo.png" alt="SEC-BERT" width="400"/>
<div style="text-align: justify">
We also pre-train our own BERT models (<strong>SEC-BERT</strong>) for the financial domain, intended to assist financial NLP research and FinTech applications. <br>
<strong>SEC-BERT</strong> consists of the following models:
* [**SEC-BERT-BASE**](https://huggingface.co/nlpaueb/sec-bert-base): Same architecture as BERT-BASE trained on financial documents.
* [**SEC-BERT-NUM**](https://huggingface.co/nlpaueb/sec-bert-num): Same as SEC-BERT-BASE but we replace every number token with a [NUM] pseudo-token handling all numeric expressions in a uniform manner, disallowing their fragmentation
* [**SEC-BERT-SHAPE**](https://huggingface.co/nlpaueb/sec-bert-shape): Same as SEC-BERT-BASE but we replace numbers with pseudo-tokens that represent the number’s shape, so numeric expressions (of known shapes) are no longer fragmented, e.g., '53.2' becomes '[XX.X]' and '40,200.5' becomes '[XX,XXX.X]'.
These models were pre-trained on 260,773 10-K filings (annual reports) from 1993-2019, publicly available at [U.S. Securities and Exchange Commission (SEC)](https://www.sec.gov/)
</div>
## About Us
<div style="text-align: justify">
[**AUEB's Natural Language Processing Group**](http://nlp.cs.aueb.gr) develops algorithms, models, and systems that allow computers to process and generate natural language texts.
The group's current research interests include:
* question answering systems for databases, ontologies, document collections, and the Web, especially biomedical question answering,
* natural language generation from databases and ontologies, especially Semantic Web ontologies,
text classification, including filtering spam and abusive content,
* information extraction and opinion mining, including legal text analytics and sentiment analysis,
* natural language processing tools for Greek, for example parsers and named-entity recognizers,
machine learning in natural language processing, especially deep learning.
The group is part of the Information Processing Laboratory of the Department of Informatics of the Athens University of Economics and Business.
</div>
[Manos Fergadiotis](https://manosfer.github.io) on behalf of [AUEB's Natural Language Processing Group](http://nlp.cs.aueb.gr) | [
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|
ehartford/wizard_vicuna_70k_unfiltered | ehartford | 2023-05-16T00:43:23Z | 348 | 119 | [
"license:apache-2.0",
"region:us"
]
| null | 2023-05-07T05:12:54Z | ---
license: apache-2.0
---
This dataset is the wizard_vicuna dataset junelee/wizard_vicuna_70k, removing conversations with alignment.
34598 conversations remain.
inspired by https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered
All credit to anon8231489123 I basically took his scripts and applied them to this new dataset. | [
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|
open-llm-leaderboard/details_mncai__Mistral-7B-openplatypus-1k | open-llm-leaderboard | 2023-10-27T04:31:58Z | 348 | 0 | [
"region:us"
]
| null | 2023-10-10T11:26:59Z | ---
pretty_name: Evaluation run of mncai/Mistral-7B-openplatypus-1k
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [mncai/Mistral-7B-openplatypus-1k](https://huggingface.co/mncai/Mistral-7B-openplatypus-1k)\
\ 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_mncai__Mistral-7B-openplatypus-1k\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-27T04:31:44.728538](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__Mistral-7B-openplatypus-1k/blob/main/results_2023-10-27T04-31-44.728538.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\": 0.0019924496644295304,\n\
\ \"em_stderr\": 0.00045666764626669425,\n \"f1\": 0.06536912751677865,\n\
\ \"f1_stderr\": 0.001427220169024926,\n \"acc\": 0.47155979662189373,\n\
\ \"acc_stderr\": 0.01115073074341337\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0019924496644295304,\n \"em_stderr\": 0.00045666764626669425,\n\
\ \"f1\": 0.06536912751677865,\n \"f1_stderr\": 0.001427220169024926\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.17437452615617893,\n \
\ \"acc_stderr\": 0.010451421361976233\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7687450670876085,\n \"acc_stderr\": 0.01185004012485051\n\
\ }\n}\n```"
repo_url: https://huggingface.co/mncai/Mistral-7B-openplatypus-1k
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_26_36.133476
path:
- '**/details_harness|arc:challenge|25_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_27T04_31_44.728538
path:
- '**/details_harness|drop|3_2023-10-27T04-31-44.728538.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-27T04-31-44.728538.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_27T04_31_44.728538
path:
- '**/details_harness|gsm8k|5_2023-10-27T04-31-44.728538.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-27T04-31-44.728538.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hellaswag|10_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T11-26-36.133476.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T11-26-36.133476.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T11-26-36.133476.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_27T04_31_44.728538
path:
- '**/details_harness|winogrande|5_2023-10-27T04-31-44.728538.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-27T04-31-44.728538.parquet'
- config_name: results
data_files:
- split: 2023_10_10T11_26_36.133476
path:
- results_2023-10-10T11-26-36.133476.parquet
- split: 2023_10_27T04_31_44.728538
path:
- results_2023-10-27T04-31-44.728538.parquet
- split: latest
path:
- results_2023-10-27T04-31-44.728538.parquet
---
# Dataset Card for Evaluation run of mncai/Mistral-7B-openplatypus-1k
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/mncai/Mistral-7B-openplatypus-1k
- **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 [mncai/Mistral-7B-openplatypus-1k](https://huggingface.co/mncai/Mistral-7B-openplatypus-1k) 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_mncai__Mistral-7B-openplatypus-1k",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-27T04:31:44.728538](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__Mistral-7B-openplatypus-1k/blob/main/results_2023-10-27T04-31-44.728538.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": 0.0019924496644295304,
"em_stderr": 0.00045666764626669425,
"f1": 0.06536912751677865,
"f1_stderr": 0.001427220169024926,
"acc": 0.47155979662189373,
"acc_stderr": 0.01115073074341337
},
"harness|drop|3": {
"em": 0.0019924496644295304,
"em_stderr": 0.00045666764626669425,
"f1": 0.06536912751677865,
"f1_stderr": 0.001427220169024926
},
"harness|gsm8k|5": {
"acc": 0.17437452615617893,
"acc_stderr": 0.010451421361976233
},
"harness|winogrande|5": {
"acc": 0.7687450670876085,
"acc_stderr": 0.01185004012485051
}
}
```
### 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] | [
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|
yale-nlp/QTSumm | yale-nlp | 2023-11-07T05:01:32Z | 348 | 1 | [
"task_categories:text-generation",
"task_categories:summarization",
"task_categories:table-question-answering",
"license:mit",
"arxiv:2305.14303",
"region:us"
]
| [
"text-generation",
"summarization",
"table-question-answering"
]
| 2023-10-20T20:26:30Z | ---
license: mit
task_categories:
- text-generation
- summarization
- table-question-answering
---
# QTSumm Dataset
The **QTSumm** dataset is a large-scale dataset for the task of **query-focused summarization over tabular data**.
It contains 7,111 human-annotated query-summary pairs over 2,934 tables covering diverse topics.
To solve this task, a text generation system has to perform **human-like reasoning and analysis** over the given table to generate a tailored summary.
## Citation
```
@misc{zhao2023qtsumm,
title={QTSumm: Query-Focused Summarization over Tabular Data},
author={Yilun Zhao and Zhenting Qi and Linyong Nan and Boyu Mi and Yixin Liu and Weijin Zou and Simeng Han and Ruizhe Chen and Xiangru Tang and Yumo Xu and Arman Cohan and Dragomir Radev},
year={2023},
eprint={2305.14303},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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|
mteb/reddit-clustering-p2p | mteb | 2022-09-27T19:13:59Z | 347 | 0 | [
"language:en",
"region:us"
]
| null | 2022-05-11T08:52:19Z | ---
language:
- en
---
10 sets with the following stats:
1. 91 labels & 15592 samples
2. 64 labels & 79172 samples
3. 38 labels & 1942 samples
4. 11 labels & 13224 samples
5. 64 labels & 92303 samples
6. 87 labels & 28607 samples
7. 10 labels & 69146 samples
8. 48 labels & 67469 samples
9. 64 labels & 29683 samples
10. 31 labels & 62261 samples
Selected at random using the script available on the mteb github repository.
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|
result-kand2-sdxl-wuerst-karlo/57854108 | result-kand2-sdxl-wuerst-karlo | 2023-11-10T09:48:00Z | 347 | 0 | [
"region:us"
]
| null | 2023-11-10T09:47:59Z | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 167
num_examples: 10
download_size: 1318
dataset_size: 167
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "57854108"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
opus_xhosanavy | null | 2022-11-03T16:08:13Z | 346 | 3 | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"language:xh",
"license:unknown",
"region:us"
]
| [
"translation"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
- xh
license:
- unknown
multilinguality:
- translation
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: OpusXhosanavy
dataset_info:
features:
- name: translation
dtype:
translation:
languages:
- en
- xh
config_name: en-xh
splits:
- name: train
num_bytes: 9654422
num_examples: 49982
download_size: 3263865
dataset_size: 9654422
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**[XhosaNavy](http://opus.nlpl.eu/XhosaNavy-v1.php)
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This corpus is part of OPUS - the open collection of parallel corpora
OPUS Website: http://opus.nlpl.eu
### Supported Tasks and Leaderboards
The underlying task is machine translation from English to Xhosa
### 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
J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012)
### Contributions
Thanks to [@lhoestq](https://github.com/lhoestq), [@spatil6](https://github.com/spatil6) for adding this dataset. | [
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|
EleutherAI/race | EleutherAI | 2023-07-03T21:27:18Z | 346 | 1 | [
"task_categories:multiple-choice",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:other",
"arxiv:1704.04683",
"region:us"
]
| [
"multiple-choice"
]
| 2023-07-03T13:20:38Z | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- other
multilinguality:
- monolingual
pretty_name: RACE
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- multiple-choice
task_ids:
- multiple-choice-qa
paperswithcode_id: race
dataset_info:
---
# "race" Grouped by Article
This is a modified version of https://huggingface.co/datasets/race that returns documents grouped by article context instead of by question. **Note:** This dataset currently only contains that test set of the ```high``` subset of the data.
The original readme is contained below.
# Dataset Card for "race"
## 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:** [http://www.cs.cmu.edu/~glai1/data/race/](http://www.cs.cmu.edu/~glai1/data/race/)
- **Repository:** https://github.com/qizhex/RACE_AR_baselines
- **Paper:** [RACE: Large-scale ReAding Comprehension Dataset From Examinations](https://arxiv.org/abs/1704.04683)
- **Point of Contact:** [Guokun Lai](mailto:[email protected]), [Qizhe Xie](mailto:[email protected])
- **Size of downloaded dataset files:** 76.33 MB
- **Size of the generated dataset:** 349.46 MB
- **Total amount of disk used:** 425.80 MB
### Dataset Summary
RACE is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
dataset is collected from English examinations in China, which are designed for middle school and high school students.
The dataset can be served as the training and test sets for machine comprehension.
### 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
#### all
- **Size of downloaded dataset files:** 25.44 MB
- **Size of the generated dataset:** 174.73 MB
- **Total amount of disk used:** 200.17 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"answer": "A",
"article": "\"Schoolgirls have been wearing such short skirts at Paget High School in Branston that they've been ordered to wear trousers ins...",
"example_id": "high132.txt",
"options": ["short skirts give people the impression of sexualisation", "short skirts are too expensive for parents to afford", "the headmaster doesn't like girls wearing short skirts", "the girls wearing short skirts will be at the risk of being laughed at"],
"question": "The girls at Paget High School are not allowed to wear skirts in that _ ."
}
```
#### high
- **Size of downloaded dataset files:** 25.44 MB
- **Size of the generated dataset:** 140.12 MB
- **Total amount of disk used:** 165.56 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"answer": "A",
"article": "\"Schoolgirls have been wearing such short skirts at Paget High School in Branston that they've been ordered to wear trousers ins...",
"example_id": "high132.txt",
"options": ["short skirts give people the impression of sexualisation", "short skirts are too expensive for parents to afford", "the headmaster doesn't like girls wearing short skirts", "the girls wearing short skirts will be at the risk of being laughed at"],
"question": "The girls at Paget High School are not allowed to wear skirts in that _ ."
}
```
#### middle
- **Size of downloaded dataset files:** 25.44 MB
- **Size of the generated dataset:** 34.61 MB
- **Total amount of disk used:** 60.05 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"answer": "B",
"article": "\"There is not enough oil in the world now. As time goes by, it becomes less and less, so what are we going to do when it runs ou...",
"example_id": "middle3.txt",
"options": ["There is more petroleum than we can use now.", "Trees are needed for some other things besides making gas.", "We got electricity from ocean tides in the old days.", "Gas wasn't used to run cars in the Second World War."],
"question": "According to the passage, which of the following statements is TRUE?"
}
```
### Data Fields
The data fields are the same among all splits.
#### all
- `example_id`: a `string` feature.
- `article`: a `string` feature.
- `answer`: a `string` feature.
- `question`: a `string` feature.
- `options`: a `list` of `string` features.
#### high
- `example_id`: a `string` feature.
- `article`: a `string` feature.
- `answer`: a `string` feature.
- `question`: a `string` feature.
- `options`: a `list` of `string` features.
#### middle
- `example_id`: a `string` feature.
- `article`: a `string` feature.
- `answer`: a `string` feature.
- `question`: a `string` feature.
- `options`: a `list` of `string` features.
### Data Splits
| name |train|validation|test|
|------|----:|---------:|---:|
|all |87866| 4887|4934|
|high |62445| 3451|3498|
|middle|25421| 1436|1436|
## 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
http://www.cs.cmu.edu/~glai1/data/race/
1. RACE dataset is available for non-commercial research purpose only.
2. All passages are obtained from the Internet which is not property of Carnegie Mellon University. We are not responsible for the content nor the meaning of these passages.
3. You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purpose, any portion of the contexts and any portion of derived data.
4. We reserve the right to terminate your access to the RACE dataset at any time.
### Citation Information
```
@inproceedings{lai-etal-2017-race,
title = "{RACE}: Large-scale {R}e{A}ding Comprehension Dataset From Examinations",
author = "Lai, Guokun and
Xie, Qizhe and
Liu, Hanxiao and
Yang, Yiming and
Hovy, Eduard",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-1082",
doi = "10.18653/v1/D17-1082",
pages = "785--794",
}
```
### Contributions
Thanks to [@abarbosa94](https://github.com/abarbosa94), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham) for adding this dataset. | [
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|
bigIR/ar_cov19 | bigIR | 2023-09-19T06:52:17Z | 345 | 1 | [
"task_categories:other",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:ar",
"data-mining",
"arxiv:2004.05861",
"region:us"
]
| [
"other"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ar
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: arcov-19
pretty_name: ArCOV19
tags:
- data-mining
dataset_info:
config_name: ar_cov19
features:
- name: tweetID
dtype: string
splits:
- name: train
num_bytes: 72223634
num_examples: 3140158
download_size: 23678407
dataset_size: 72223634
---
# Dataset Card for ArCOV19
## 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://gitlab.com/bigirqu/ArCOV-19
- **Paper:** [ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks](https://arxiv.org/abs/2004.05861)
- **Leaderboard:** [More Information Needed]
- **Point of Contact:** [Fatima Haouari](mailto:[email protected])
### Dataset Summary
ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 5th of May 2021.
ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes about 3.2M
tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked).
The propagation networks include both retweets and conversational threads (i.e., threads of replies).
ArCOV-19 is designed to enable research under several domains including natural language processing, information
retrieval, and social computing, among others. Preliminary analysis shows that ArCOV-19 captures rising discussions
associated with the first reported cases of the disease as they appeared in the Arab world. In addition to the source
tweets and the propagation networks, we also release the search queries and the language-independent crawler used to
collect the tweets to encourage the curation of similar datasets.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Arabic
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
tweet_id: the Twitter assigned ID for the tweet object.
### Data Splits
[More Information Needed]
## Dataset Creation
The dataset collection approach is presented in the following paper: [ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks](https://arxiv.org/abs/2004.05861)
### 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
No annotation was provided with the dataset.
#### Annotation process
No annotation was provided with the dataset.
#### Who are the annotators?
No annotation was provided with the dataset.
### 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
**Team:** [bigIR](https://sites.google.com/view/bigir) from Qatar University ([@bigIR_group](https://twitter.com/bigIR_group))
- [Fatima Haouari](mailto:[email protected])
- [Maram Hasanain](mailto:[email protected])
- [Reem Suwaileh](mailto:[email protected])
- [Dr. Tamer Elsayed](mailto:[email protected])
### Licensing Information
[More Information Needed]
### Citation Information
```
@article{haouari2020arcov19,
title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
year={2021},
eprint={2004.05861},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
Thanks to [@Fatima-Haouari](https://github.com/Fatima-Haouari) for adding this dataset. | [
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|
FredZhang7/stable-diffusion-prompts-2.47M | FredZhang7 | 2023-02-11T21:59:33Z | 345 | 20 | [
"task_categories:text-generation",
"size_categories:1M<n<10M",
"language:en",
"license:creativeml-openrail-m",
"region:us"
]
| [
"text-generation"
]
| 2023-02-09T04:03:22Z | ---
license: creativeml-openrail-m
task_categories:
- text-generation
language:
- en
pretty_name: SDP-2.47M
size_categories:
- 1M<n<10M
---
## Source
Combined text-only dataset from
- poloclub/diffusiondb
- Gustavosta/Stable-Diffusion-Prompts
- bartman081523/stable-diffusion-discord-prompts
- FredZhang7/krea-ai-prompts
For preprocessing methods, please see [Fast GPT2 PromptGen](https://huggingface.co/FredZhang7/distilgpt2-stable-diffusion-v2).
## Python
Download and save the dataset to `all_prompts.txt` locally.
```bash
pip install datasets
```
```python
import datasets
dataset = datasets.load_dataset("FredZhang7/stable-diffusion-prompts-2.47M")
train = dataset["train"]
prompts = train["text"]
with open("all_prompts.txt", "w") as f:
for prompt in prompts:
f.write(prompt + "\n")
``` | [
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|
Babelscape/rebel-dataset | Babelscape | 2023-06-15T12:12:59Z | 344 | 15 | [
"task_categories:text-retrieval",
"task_categories:text-generation",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"relation-extraction",
"conditional-text-generation",
"arxiv:2005.00614",
"region:us"
]
| [
"text-retrieval",
"text-generation"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
license: cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-retrieval
- text-generation
task_ids: []
pretty_name: rebel-dataset
tags:
- relation-extraction
- conditional-text-generation
---
cc-by-nc-sa-4.0---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-retrieval
- text-generation
task_ids: []
pretty_name: rebel-dataset
tags:
- relation-extraction
- conditional-text-generation
---
# Dataset Card for REBEL dataset
## Table of Contents
- [Dataset Card for REBEL dataset](#dataset-card-for-rebel)
- [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)
- [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
- **Repository:** [https://github.com/Babelscape/rebel](https://github.com/Babelscape/rebel)
- **Paper:** [https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf)
- **Point of Contact:** [[email protected]]([email protected])
### Dataset Summary
Dataset created for [REBEL](https://huggingface.co/Babelscape/rebel-large) dataset from interlinking Wikidata and Wikipedia for Relation Extraction, filtered using NLI.
### Supported Tasks and Leaderboards
- `text-retrieval-other-relation-extraction`: The dataset can be used to train a model for Relation Extraction, which consists in extracting triplets from raw text, made of subject, object and relation type. Success on this task is typically measured by achieving a *high* [F1](https://huggingface.co/metrics/F1). The [BART](https://huggingface.co/transformers/model_doc/bart.html)) model currently achieves the following score: 74 Micro F1 and 51 Macro F1 for the 220 most frequent relation types.
### Languages
The dataset is in English, from the English Wikipedia.
## Dataset Structure
### Data Instances
REBEL
- `Size of downloaded dataset files`: 1490.02 MB
- `Size of the generated dataset`: 1199.27 MB
- `Total amount of disk used`: 2689.29 MB
```
{
'id': 'Q82442-1',
'title': 'Arsène Lupin, Gentleman Burglar',
'context': 'Arsène Lupin , Gentleman Burglar is the first collection of stories by Maurice Leblanc recounting the adventures of Arsène Lupin , released on 10 June 1907 .',
'triplets': '<triplet> Arsène Lupin, Gentleman Burglar <subj> Maurice Leblanc <obj> author <triplet> Arsène Lupin <subj> Maurice Leblanc <obj> creator'
}
```
The original data is in jsonl format and contains much more information. It is divided by Wikipedia articles instead of by sentence, and contains metadata about Wikidata entities, their boundaries in the text, how it was annotated, etc. For more information check the [paper repository](https://huggingface.co/Babelscape/rebel-large) and how it was generated using the Relation Extraction dataset pipeline, [cRocoDiLe](https://github.com/Babelscape/crocodile).
### Data Fields
List and describe the fields present in the dataset. Mention their data type, and whether they are used as input or output in any of the tasks the dataset currently supports. If the data has span indices, describe their attributes, such as whether they are at the character level or word level, whether they are contiguous or not, etc. If the datasets contains example IDs, state whether they have an inherent meaning, such as a mapping to other datasets or pointing to relationships between data points.
- `id`: ID of the instance. It contains a unique id matching to a Wikipedia page and a number separated by a hyphen indicating which sentence of the Wikipedia article it is.
- `title`: Title of the Wikipedia page the sentence comes from.
- `context`: Text from Wikipedia articles that serves as context for the Relation Extraction task.
- `triplets`: Linearized version of the triplets present in the text, split by the use of special tokens. For more info on this linearization check the [paper](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf).
### Data Splits
Test and Validation splits are each 5% of the original data.
Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length. For example:
| | Tain | Valid | Test |
| ----- | ------ | ----- | ---- |
| Input Sentences | 3,120,296 | 172,860 | 173,601 |
| Input Sentences (top 220 relation types as used in original paper) | 784,202 | 43,341 | 43,506 |
| Number of Triplets (top 220 relation types as used in original paper) | 878,555 | 48,514 | 48,852 |
## Dataset Creation
### Curation Rationale
This dataset was created to enable the training of a BART based model as pre-training phase for Relation Extraction as seen in the paper [REBEL: Relation Extraction By End-to-end Language generation](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf).
### Source Data
Data comes from Wikipedia text before the table of contents, as well as Wikidata for the triplets annotation.
#### Initial Data Collection and Normalization
For the data collection, the dataset extraction pipeline [cRocoDiLe: Automati**c** **R**elati**o**n Extra**c**ti**o**n **D**ataset w**i**th N**L**I filt**e**ring](https://github.com/Babelscape/crocodile) insipired by [T-REx Pipeline](https://github.com/hadyelsahar/RE-NLG-Dataset) more details found at: [T-REx Website](https://hadyelsahar.github.io/t-rex/). The starting point is a Wikipedia dump as well as a Wikidata one.
After the triplets are extracted, an NLI system was used to filter out those not entailed by the text.
#### Who are the source language producers?
Any Wikipedia and Wikidata contributor.
### Annotations
#### Annotation process
The dataset extraction pipeline [cRocoDiLe: Automati**c** **R**elati**o**n Extra**c**ti**o**n **D**ataset w**i**th N**L**I filt**e**ring](https://github.com/Babelscape/crocodile).
#### Who are the annotators?
Automatic annottations
### Personal and Sensitive Information
All text is from Wikipedia, any Personal or Sensitive Information there may be present in this dataset.
## Considerations for Using the Data
### Social Impact of Dataset
The dataset serves as a pre-training step for Relation Extraction models. It is distantly annotated, hence it should only be used as such. A model trained solely on this dataset may produce allucinations coming from the silver nature of the dataset.
### Discussion of Biases
Since the dataset was automatically created from Wikipedia and Wikidata, it may reflect the biases withing those sources.
For Wikipedia text, see for example [Dinan et al 2020 on biases in Wikipedia (esp. Table 1)](https://arxiv.org/abs/2005.00614), or [Blodgett et al 2020](https://www.aclweb.org/anthology/2020.acl-main.485/) for a more general discussion of the topic.
For Wikidata, there are class imbalances, also resulting from Wikipedia.
### Other Known Limitations
Not for now
## Additional Information
### Dataset Curators
Pere-Lluis Huguet Cabot - Babelscape and Sapienza University of Rome, Italy
Roberto Navigli - Sapienza University of Rome, Italy
### Licensing Information
Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
### Citation Information
Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example:
```
@inproceedings{huguet-cabot-navigli-2021-rebel,
title = "REBEL: Relation Extraction By End-to-end Language generation",
author = "Huguet Cabot, Pere-Llu{\'\i}s and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
month = nov,
year = "2021",
address = "Online and in the Barceló Bávaro Convention Centre, Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf",
}
```
### Contributions
Thanks to [@littlepea13](https://github.com/LittlePea13) for adding this dataset. | [
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|
Graphcore/wikipedia-bert-128 | Graphcore | 2022-09-07T14:42:32Z | 344 | 0 | [
"language:en",
"license:cc-by-sa-3.0",
"region:us"
]
| null | 2022-03-02T23:29:22Z | ---
language:
- en
license:
- cc-by-sa-3.0
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|
open-llm-leaderboard/details_Riiid__sheep-duck-llama-2 | open-llm-leaderboard | 2023-09-19T02:43:00Z | 344 | 0 | [
"region:us"
]
| null | 2023-09-12T04:15:36Z | ---
pretty_name: Evaluation run of Riiid/sheep-duck-llama-2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Riiid/sheep-duck-llama-2](https://huggingface.co/Riiid/sheep-duck-llama-2) 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_Riiid__sheep-duck-llama-2\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-09-19T02:41:38.567550](https://huggingface.co/datasets/open-llm-leaderboard/details_Riiid__sheep-duck-llama-2/blob/main/results_2023-09-19T02-41-38.567550.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\": 0.7074787526637408,\n\
\ \"acc_stderr\": 0.030842770794867788,\n \"acc_norm\": 0.7112713043078007,\n\
\ \"acc_norm_stderr\": 0.03081173438001915,\n \"mc1\": 0.4663402692778458,\n\
\ \"mc1_stderr\": 0.017463793867168103,\n \"mc2\": 0.6379733867215786,\n\
\ \"mc2_stderr\": 0.014804542452694204\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6851535836177475,\n \"acc_stderr\": 0.013572657703084948,\n\
\ \"acc_norm\": 0.7226962457337884,\n \"acc_norm_stderr\": 0.013082095839059376\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6915952997410875,\n\
\ \"acc_stderr\": 0.0046089078729577085,\n \"acc_norm\": 0.8778131846245768,\n\
\ \"acc_norm_stderr\": 0.003268321260913631\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n\
\ \"acc_stderr\": 0.04171654161354543,\n \"acc_norm\": 0.6296296296296297,\n\
\ \"acc_norm_stderr\": 0.04171654161354543\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.8026315789473685,\n \"acc_stderr\": 0.03238981601699397,\n\
\ \"acc_norm\": 0.8026315789473685,\n \"acc_norm_stderr\": 0.03238981601699397\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.74,\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\": 0.02674989977124121,\n\
\ \"acc_norm\": 0.7471698113207547,\n \"acc_norm_stderr\": 0.02674989977124121\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8194444444444444,\n\
\ \"acc_stderr\": 0.03216600808802267,\n \"acc_norm\": 0.8194444444444444,\n\
\ \"acc_norm_stderr\": 0.03216600808802267\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \
\ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620332\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n\
\ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.41,\n \"acc_stderr\": 0.049431107042371025,\n \
\ \"acc_norm\": 0.41,\n \"acc_norm_stderr\": 0.049431107042371025\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\
\ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\
\ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\
\ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.77,\n \"acc_stderr\": 0.04229525846816507,\n \"acc_norm\": 0.77,\n\
\ \"acc_norm_stderr\": 0.04229525846816507\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.6851063829787234,\n \"acc_stderr\": 0.03036358219723817,\n\
\ \"acc_norm\": 0.6851063829787234,\n \"acc_norm_stderr\": 0.03036358219723817\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\": 0.6413793103448275,\n \"acc_stderr\": 0.03996629574876719,\n\
\ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.03996629574876719\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.4708994708994709,\n \"acc_stderr\": 0.02570765861415495,\n \"\
acc_norm\": 0.4708994708994709,\n \"acc_norm_stderr\": 0.02570765861415495\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5238095238095238,\n\
\ \"acc_stderr\": 0.04467062628403273,\n \"acc_norm\": 0.5238095238095238,\n\
\ \"acc_norm_stderr\": 0.04467062628403273\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \
\ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8225806451612904,\n\
\ \"acc_stderr\": 0.021732540689329286,\n \"acc_norm\": 0.8225806451612904,\n\
\ \"acc_norm_stderr\": 0.021732540689329286\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5665024630541872,\n \"acc_stderr\": 0.034867317274198714,\n\
\ \"acc_norm\": 0.5665024630541872,\n \"acc_norm_stderr\": 0.034867317274198714\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.78,\n \"acc_stderr\": 0.04163331998932262,\n \"acc_norm\"\
: 0.78,\n \"acc_norm_stderr\": 0.04163331998932262\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.027998073798781678,\n\
\ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.027998073798781678\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.8888888888888888,\n \"acc_stderr\": 0.022390787638216763,\n \"\
acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.022390787638216763\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240528,\n\
\ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240528\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.7102564102564103,\n \"acc_stderr\": 0.023000628243687968,\n\
\ \"acc_norm\": 0.7102564102564103,\n \"acc_norm_stderr\": 0.023000628243687968\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32222222222222224,\n \"acc_stderr\": 0.0284934650910286,\n \
\ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.0284934650910286\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.7773109243697479,\n \"acc_stderr\": 0.027025433498882385,\n\
\ \"acc_norm\": 0.7773109243697479,\n \"acc_norm_stderr\": 0.027025433498882385\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.47019867549668876,\n \"acc_stderr\": 0.040752249922169775,\n \"\
acc_norm\": 0.47019867549668876,\n \"acc_norm_stderr\": 0.040752249922169775\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.9009174311926605,\n \"acc_stderr\": 0.01280978008187893,\n \"\
acc_norm\": 0.9009174311926605,\n \"acc_norm_stderr\": 0.01280978008187893\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5972222222222222,\n \"acc_stderr\": 0.03344887382997865,\n \"\
acc_norm\": 0.5972222222222222,\n \"acc_norm_stderr\": 0.03344887382997865\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073315,\n \"\
acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073315\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640255,\n \
\ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640255\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7982062780269058,\n\
\ \"acc_stderr\": 0.026936111912802273,\n \"acc_norm\": 0.7982062780269058,\n\
\ \"acc_norm_stderr\": 0.026936111912802273\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8549618320610687,\n \"acc_stderr\": 0.030884661089515368,\n\
\ \"acc_norm\": 0.8549618320610687,\n \"acc_norm_stderr\": 0.030884661089515368\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8760330578512396,\n \"acc_stderr\": 0.030083098716035206,\n \"\
acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.030083098716035206\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n\
\ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\
\ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.8282208588957055,\n \"acc_stderr\": 0.029634717272371037,\n\
\ \"acc_norm\": 0.8282208588957055,\n \"acc_norm_stderr\": 0.029634717272371037\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5446428571428571,\n\
\ \"acc_stderr\": 0.04726835553719098,\n \"acc_norm\": 0.5446428571428571,\n\
\ \"acc_norm_stderr\": 0.04726835553719098\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\
\ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9145299145299145,\n\
\ \"acc_stderr\": 0.01831589168562585,\n \"acc_norm\": 0.9145299145299145,\n\
\ \"acc_norm_stderr\": 0.01831589168562585\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \
\ \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.04560480215720684\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8697318007662835,\n\
\ \"acc_stderr\": 0.012036729568216055,\n \"acc_norm\": 0.8697318007662835,\n\
\ \"acc_norm_stderr\": 0.012036729568216055\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7832369942196532,\n \"acc_stderr\": 0.022183477668412856,\n\
\ \"acc_norm\": 0.7832369942196532,\n \"acc_norm_stderr\": 0.022183477668412856\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.6245810055865921,\n\
\ \"acc_stderr\": 0.01619510424846353,\n \"acc_norm\": 0.6245810055865921,\n\
\ \"acc_norm_stderr\": 0.01619510424846353\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7549019607843137,\n \"acc_stderr\": 0.02463004897982477,\n\
\ \"acc_norm\": 0.7549019607843137,\n \"acc_norm_stderr\": 0.02463004897982477\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7909967845659164,\n\
\ \"acc_stderr\": 0.02309314039837422,\n \"acc_norm\": 0.7909967845659164,\n\
\ \"acc_norm_stderr\": 0.02309314039837422\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.8425925925925926,\n \"acc_stderr\": 0.020263764996385717,\n\
\ \"acc_norm\": 0.8425925925925926,\n \"acc_norm_stderr\": 0.020263764996385717\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.5780141843971631,\n \"acc_stderr\": 0.029462189233370593,\n \
\ \"acc_norm\": 0.5780141843971631,\n \"acc_norm_stderr\": 0.029462189233370593\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5867014341590613,\n\
\ \"acc_stderr\": 0.012576779494860076,\n \"acc_norm\": 0.5867014341590613,\n\
\ \"acc_norm_stderr\": 0.012576779494860076\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.02667925227010314,\n\
\ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.02667925227010314\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.7696078431372549,\n \"acc_stderr\": 0.01703522925803403,\n \
\ \"acc_norm\": 0.7696078431372549,\n \"acc_norm_stderr\": 0.01703522925803403\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7545454545454545,\n\
\ \"acc_stderr\": 0.041220665028782855,\n \"acc_norm\": 0.7545454545454545,\n\
\ \"acc_norm_stderr\": 0.041220665028782855\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7959183673469388,\n \"acc_stderr\": 0.025801283475090496,\n\
\ \"acc_norm\": 0.7959183673469388,\n \"acc_norm_stderr\": 0.025801283475090496\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8706467661691543,\n\
\ \"acc_stderr\": 0.023729830881018533,\n \"acc_norm\": 0.8706467661691543,\n\
\ \"acc_norm_stderr\": 0.023729830881018533\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.87,\n \"acc_stderr\": 0.033799766898963086,\n \
\ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.033799766898963086\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5180722891566265,\n\
\ \"acc_stderr\": 0.03889951252827216,\n \"acc_norm\": 0.5180722891566265,\n\
\ \"acc_norm_stderr\": 0.03889951252827216\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.02517298435015575,\n\
\ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.02517298435015575\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4663402692778458,\n\
\ \"mc1_stderr\": 0.017463793867168103,\n \"mc2\": 0.6379733867215786,\n\
\ \"mc2_stderr\": 0.014804542452694204\n }\n}\n```"
repo_url: https://huggingface.co/Riiid/sheep-duck-llama-2
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_12T04_15_20.917267
path:
- '**/details_harness|arc:challenge|25_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|arc:challenge|25_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hellaswag|10_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hellaswag|10_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-12T04-15-20.917267.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-19T02-41-38.567550.parquet'
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- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-19T02-41-38.567550.parquet'
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- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-19T02-41-38.567550.parquet'
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- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-19T02-41-38.567550.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
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path:
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_human_aging_5
data_files:
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path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
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path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
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path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
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path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
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path:
- '**/details_harness|hendrycksTest-management|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
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path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
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path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
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path:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
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path:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
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path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
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path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
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path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
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path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
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path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
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path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
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path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
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path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-12T04-15-20.917267.parquet'
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-12T04-15-20.917267.parquet'
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path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
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path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-19T02-41-38.567550.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-12T04-15-20.917267.parquet'
- split: 2023_09_19T02_41_38.567550
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-19T02-41-38.567550.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-19T02-41-38.567550.parquet'
- config_name: results
data_files:
- split: 2023_09_12T04_15_20.917267
path:
- results_2023-09-12T04-15-20.917267.parquet
- split: 2023_09_19T02_41_38.567550
path:
- results_2023-09-19T02-41-38.567550.parquet
- split: latest
path:
- results_2023-09-19T02-41-38.567550.parquet
---
# Dataset Card for Evaluation run of Riiid/sheep-duck-llama-2
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Riiid/sheep-duck-llama-2
- **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 [Riiid/sheep-duck-llama-2](https://huggingface.co/Riiid/sheep-duck-llama-2) 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_Riiid__sheep-duck-llama-2",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-19T02:41:38.567550](https://huggingface.co/datasets/open-llm-leaderboard/details_Riiid__sheep-duck-llama-2/blob/main/results_2023-09-19T02-41-38.567550.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
{
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"mc1_stderr": 0.017463793867168103,
"mc2": 0.6379733867215786,
"mc2_stderr": 0.014804542452694204
},
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"acc_norm": 0.7226962457337884,
"acc_norm_stderr": 0.013082095839059376
},
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},
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}
}
```
### 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] | [
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|
imvladikon/hebrew_speech_coursera | imvladikon | 2023-05-05T09:05:00Z | 343 | 5 | [
"task_categories:automatic-speech-recognition",
"size_categories:1K<n<10K",
"language:he",
"region:us"
]
| [
"automatic-speech-recognition"
]
| 2022-03-02T23:29:22Z | ---
task_categories:
- automatic-speech-recognition
language:
- he
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 6670706136.352
num_examples: 20306
- name: validation
num_bytes: 1648062261.28
num_examples: 5076
download_size: 7726933856
dataset_size: 8318768397.632
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
```json
{'audio': {'path': '/root/.cache/huggingface/datasets/downloads/extracted/89efd3a0fa3ead3f0b8e432e8796697a738d4561b24ff91f4fb2cc25d86e9fb0/train/ccef55189b7843d49110228cb0a71bfa115.wav',
'array': array([-0.01217651, -0.04351807, -0.06278992, ..., -0.00018311,
-0.00146484, -0.00349426]),
'sampling_rate': 16000},
'sentence': 'מצד אחד ובתנועה הציונית הצעירה'}
```
### Data Fields
[More Information Needed]
### Data Splits
| | train | validation |
| ---- | ----- | ---------- |
| number of samples | 20306 | 5076 |
| hours | 28.88 | 7.23 |
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```
@misc{imvladikon2022hebrew_speech_coursera,
author = {Gurevich, Vladimir},
title = {Hebrew Speech Recognition Dataset: Coursera},
year = {2022},
howpublished = \url{https://huggingface.co/datasets/imvladikon/hebrew_speech_coursera},
}
```
### Contributions
[More Information Needed] | [
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|
imvladikon/hebrew_speech_kan | imvladikon | 2023-05-05T09:12:15Z | 343 | 3 | [
"task_categories:automatic-speech-recognition",
"size_categories:1K<n<10K",
"language:he",
"region:us"
]
| [
"automatic-speech-recognition"
]
| 2022-03-02T23:29:22Z | ---
task_categories:
- automatic-speech-recognition
language:
- he
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 1569850175.0
num_examples: 8000
- name: validation
num_bytes: 394275049.0
num_examples: 2000
download_size: 1989406585
dataset_size: 1964125224.0
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Hebrew Dataset for ASR
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
```json
{'audio': {'path': '/root/.cache/huggingface/datasets/downloads/extracted/8ce7402f6482c6053251d7f3000eec88668c994beb48b7ca7352e77ef810a0b6/train/e429593fede945c185897e378a5839f4198.wav',
'array': array([-0.00265503, -0.0018158 , -0.00149536, ..., -0.00135803,
-0.00231934, -0.00190735]),
'sampling_rate': 16000},
'sentence': 'היא מבינה אותי יותר מכל אחד אחר'}
```
### Data Fields
[More Information Needed]
### Data Splits
| | train | validation |
| ---- | ----- | ---------- |
| number of samples | 8000 | 2000 |
| hours | 6.92 | 1.73 |
## Dataset Creation
### Curation Rationale
scraped data from youtube (channel כאן) with removing outliers (by length and ratio between length of the audio and sentences)
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```
@misc{imvladikon2022hebrew_speech_kan,
author = {Gurevich, Vladimir},
title = {Hebrew Speech Recognition Dataset: Kan},
year = {2022},
howpublished = \url{https://huggingface.co/datasets/imvladikon/hebrew_speech_kan},
}
```
### Contributions
[More Information Needed] | [
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|
open-llm-leaderboard/details_huggingtweets__bladeecity-jerma985 | open-llm-leaderboard | 2023-09-16T19:05:45Z | 343 | 0 | [
"region:us"
]
| null | 2023-08-18T00:09:13Z | ---
pretty_name: Evaluation run of huggingtweets/bladeecity-jerma985
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [huggingtweets/bladeecity-jerma985](https://huggingface.co/huggingtweets/bladeecity-jerma985)\
\ 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_huggingtweets__bladeecity-jerma985\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-16T19:05:34.186179](https://huggingface.co/datasets/open-llm-leaderboard/details_huggingtweets__bladeecity-jerma985/blob/main/results_2023-09-16T19-05-34.186179.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\": 0.03125,\n \
\ \"em_stderr\": 0.0017818474501498898,\n \"f1\": 0.05531879194630876,\n\
\ \"f1_stderr\": 0.0020837697984111155,\n \"acc\": 0.2600631412786109,\n\
\ \"acc_stderr\": 0.007020548332172167\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.03125,\n \"em_stderr\": 0.0017818474501498898,\n \
\ \"f1\": 0.05531879194630876,\n \"f1_stderr\": 0.0020837697984111155\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5201262825572218,\n\
\ \"acc_stderr\": 0.014041096664344334\n }\n}\n```"
repo_url: https://huggingface.co/huggingtweets/bladeecity-jerma985
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|arc:challenge|25_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_16T19_05_34.186179
path:
- '**/details_harness|drop|3_2023-09-16T19-05-34.186179.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-16T19-05-34.186179.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_16T19_05_34.186179
path:
- '**/details_harness|gsm8k|5_2023-09-16T19-05-34.186179.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-16T19-05-34.186179.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hellaswag|10_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:07:22.226124.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
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path:
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path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
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path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:07:22.226124.parquet'
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path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
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path:
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path:
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- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
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path:
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- config_name: harness_hendrycksTest_management_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:07:22.226124.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
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path:
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path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T19:07:22.226124.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_16T19_05_34.186179
path:
- '**/details_harness|winogrande|5_2023-09-16T19-05-34.186179.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-16T19-05-34.186179.parquet'
- config_name: results
data_files:
- split: 2023_07_19T19_07_22.226124
path:
- results_2023-07-19T19:07:22.226124.parquet
- split: 2023_09_16T19_05_34.186179
path:
- results_2023-09-16T19-05-34.186179.parquet
- split: latest
path:
- results_2023-09-16T19-05-34.186179.parquet
---
# Dataset Card for Evaluation run of huggingtweets/bladeecity-jerma985
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/huggingtweets/bladeecity-jerma985
- **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 [huggingtweets/bladeecity-jerma985](https://huggingface.co/huggingtweets/bladeecity-jerma985) 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_huggingtweets__bladeecity-jerma985",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-16T19:05:34.186179](https://huggingface.co/datasets/open-llm-leaderboard/details_huggingtweets__bladeecity-jerma985/blob/main/results_2023-09-16T19-05-34.186179.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": 0.03125,
"em_stderr": 0.0017818474501498898,
"f1": 0.05531879194630876,
"f1_stderr": 0.0020837697984111155,
"acc": 0.2600631412786109,
"acc_stderr": 0.007020548332172167
},
"harness|drop|3": {
"em": 0.03125,
"em_stderr": 0.0017818474501498898,
"f1": 0.05531879194630876,
"f1_stderr": 0.0020837697984111155
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
},
"harness|winogrande|5": {
"acc": 0.5201262825572218,
"acc_stderr": 0.014041096664344334
}
}
```
### 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] | [
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|
AdvayK/SFD_7_9010_split | AdvayK | 2023-11-28T00:13:26Z | 343 | 0 | [
"region:us"
]
| null | 2023-11-28T00:04:03Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 495058139.16573346
num_examples: 803
- name: test
num_bytes: 52309573.83426652
num_examples: 90
download_size: 444464113
dataset_size: 547367713.0
---
# Dataset Card for "SFD_7_9010_split"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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0.3205512762069702,
0.181427463889122,
0.7112785577774048,
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0.2525830566883087,
0.2138182371854782,
0.22345364093780518,
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0.44631627202033997,
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]
|
open-llm-leaderboard/details_uni-tianyan__Uni-TianYan | open-llm-leaderboard | 2023-09-18T02:40:22Z | 342 | 0 | [
"region:us"
]
| null | 2023-09-03T12:28:00Z | ---
pretty_name: Evaluation run of uni-tianyan/Uni-TianYan
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [uni-tianyan/Uni-TianYan](https://huggingface.co/uni-tianyan/Uni-TianYan) 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_uni-tianyan__Uni-TianYan\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-18T02:40:09.826211](https://huggingface.co/datasets/open-llm-leaderboard/details_uni-tianyan__Uni-TianYan/blob/main/results_2023-09-18T02-40-09.826211.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\": 0.24486157718120805,\n\
\ \"em_stderr\": 0.004403654691385411,\n \"f1\": 0.39787751677852523,\n\
\ \"f1_stderr\": 0.004155160727794137,\n \"acc\": 0.5222921265482389,\n\
\ \"acc_stderr\": 0.01107896164608613\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.24486157718120805,\n \"em_stderr\": 0.004403654691385411,\n\
\ \"f1\": 0.39787751677852523,\n \"f1_stderr\": 0.004155160727794137\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.221379833206975,\n \
\ \"acc_stderr\": 0.011436000004253518\n },\n \"harness|winogrande|5\":\
\ {\n \"acc\": 0.8232044198895028,\n \"acc_stderr\": 0.010721923287918744\n\
\ }\n}\n```"
repo_url: https://huggingface.co/uni-tianyan/Uni-TianYan
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_03T12_27_36.436118
path:
- '**/details_harness|arc:challenge|25_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_18T02_40_09.826211
path:
- '**/details_harness|drop|3_2023-09-18T02-40-09.826211.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-18T02-40-09.826211.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_18T02_40_09.826211
path:
- '**/details_harness|gsm8k|5_2023-09-18T02-40-09.826211.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-18T02-40-09.826211.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hellaswag|10_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-03T12:27:36.436118.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-03T12:27:36.436118.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-03T12:27:36.436118.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_18T02_40_09.826211
path:
- '**/details_harness|winogrande|5_2023-09-18T02-40-09.826211.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-18T02-40-09.826211.parquet'
- config_name: results
data_files:
- split: 2023_09_03T12_27_36.436118
path:
- results_2023-09-03T12:27:36.436118.parquet
- split: 2023_09_18T02_40_09.826211
path:
- results_2023-09-18T02-40-09.826211.parquet
- split: latest
path:
- results_2023-09-18T02-40-09.826211.parquet
---
# Dataset Card for Evaluation run of uni-tianyan/Uni-TianYan
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/uni-tianyan/Uni-TianYan
- **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 [uni-tianyan/Uni-TianYan](https://huggingface.co/uni-tianyan/Uni-TianYan) 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_uni-tianyan__Uni-TianYan",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-18T02:40:09.826211](https://huggingface.co/datasets/open-llm-leaderboard/details_uni-tianyan__Uni-TianYan/blob/main/results_2023-09-18T02-40-09.826211.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": 0.24486157718120805,
"em_stderr": 0.004403654691385411,
"f1": 0.39787751677852523,
"f1_stderr": 0.004155160727794137,
"acc": 0.5222921265482389,
"acc_stderr": 0.01107896164608613
},
"harness|drop|3": {
"em": 0.24486157718120805,
"em_stderr": 0.004403654691385411,
"f1": 0.39787751677852523,
"f1_stderr": 0.004155160727794137
},
"harness|gsm8k|5": {
"acc": 0.221379833206975,
"acc_stderr": 0.011436000004253518
},
"harness|winogrande|5": {
"acc": 0.8232044198895028,
"acc_stderr": 0.010721923287918744
}
}
```
### 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] | [
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|
lc_quad | null | 2023-04-05T10:09:15Z | 341 | 6 | [
"task_categories:question-answering",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
"knowledge-base-qa",
"region:us"
]
| [
"question-answering"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- cc-by-3.0
multilinguality:
- monolingual
pretty_name: 'LC-QuAD 2.0: Large-scale Complex Question Answering Dataset'
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids: []
paperswithcode_id: lc-quad-2-0
tags:
- knowledge-base-qa
dataset_info:
features:
- name: NNQT_question
dtype: string
- name: uid
dtype: int32
- name: subgraph
dtype: string
- name: template_index
dtype: int32
- name: question
dtype: string
- name: sparql_wikidata
dtype: string
- name: sparql_dbpedia18
dtype: string
- name: template
dtype: string
- name: paraphrased_question
dtype: string
splits:
- name: train
num_bytes: 16637751
num_examples: 19293
- name: test
num_bytes: 4067092
num_examples: 4781
download_size: 3959901
dataset_size: 20704843
---
# Dataset Card for LC-QuAD 2.0
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [http://lc-quad.sda.tech/](http://lc-quad.sda.tech/)
- **Repository:** https://github.com/AskNowQA/LC-QuAD2.0
- **Paper:** [LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia](https://api.semanticscholar.org/CorpusID:198166992)
- **Point of Contact:** [Mohnish Dubey](mailto:[email protected]) or [Mohnish Dubey](mailto:[email protected])
- **Size of downloaded dataset files:** 3.87 MB
- **Size of the generated dataset:** 20.73 MB
- **Total amount of disk used:** 24.60 MB
### Dataset Summary
LC-QuAD 2.0 is a Large Question Answering dataset with 30,000 pairs of question and its corresponding SPARQL query. The target knowledge base is Wikidata and DBpedia, specifically the 2018 version. Please see our paper for details about the dataset creation process and framework.
### 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
#### default
- **Size of downloaded dataset files:** 3.87 MB
- **Size of the generated dataset:** 20.73 MB
- **Total amount of disk used:** 24.60 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"NNQT_question": "What is the {periodical literature} for {mouthpiece} of {Delta Air Lines}",
"paraphrased_question": "What is Delta Air Line's periodical literature mouthpiece?",
"question": "What periodical literature does Delta Air Lines use as a moutpiece?",
"sparql_dbpedia18": "\"select distinct ?obj where { ?statement <http://www.w3.org/1999/02/22-rdf-syntax-ns#subject> <http://wikidata.dbpedia.org/resou...",
"sparql_wikidata": " select distinct ?obj where { wd:Q188920 wdt:P2813 ?obj . ?obj wdt:P31 wd:Q1002697 } ",
"subgraph": "simple question right",
"template": " <S P ?O ; ?O instanceOf Type>",
"template_index": 65,
"uid": 19719
}
```
### Data Fields
The data fields are the same among all splits.
#### default
- `NNQT_question`: a `string` feature.
- `uid`: a `int32` feature.
- `subgraph`: a `string` feature.
- `template_index`: a `int32` feature.
- `question`: a `string` feature.
- `sparql_wikidata`: a `string` feature.
- `sparql_dbpedia18`: a `string` feature.
- `template`: a `string` feature.
- `paraphrased_question`: a `string` feature.
### Data Splits
| name |train|test|
|-------|----:|---:|
|default|19293|4781|
## 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
LC-QuAD 2.0 is licensed under a [Creative Commons Attribution 3.0 Unported License](http://creativecommons.org/licenses/by/3.0/deed.en_US).
### Citation Information
```
@inproceedings{dubey2017lc2,
title={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia},
author={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens},
booktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)},
year={2019},
organization={Springer}
}
```
### Contributions
Thanks to [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset. | [
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|
howard-hou/OCR-VQA | howard-hou | 2023-04-24T01:29:24Z | 341 | 7 | [
"region:us"
]
| null | 2023-04-23T17:43:27Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: image_id
dtype: string
- name: questions
sequence: string
- name: answers
sequence: string
- name: ocr_tokens
sequence: string
- name: ocr_info
list:
- name: word
dtype: string
- name: bounding_box
struct:
- name: width
dtype: float64
- name: height
dtype: float64
- name: top_left_x
dtype: float64
- name: top_left_y
dtype: float64
- name: title
dtype: string
- name: authorName
dtype: string
- name: genre
dtype: string
- name: image_width
dtype: int64
- name: image_height
dtype: int64
- name: image_url
dtype: string
- name: set_name
dtype: string
splits:
- name: train
num_bytes: 7503971854.0
num_examples: 166022
- name: test
num_bytes: 928616409.0
num_examples: 20796
- name: validation
num_bytes: 920236957.0
num_examples: 20731
download_size: 2329997099
dataset_size: 9352825220.0
---
# Dataset Card for "OCR-VQA"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
C-MTEB/QBQTC | C-MTEB | 2023-07-28T13:38:12Z | 341 | 0 | [
"region:us"
]
| null | 2023-07-28T13:38:05Z | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 524191
num_examples: 5000
download_size: 387552
dataset_size: 524191
---
# Dataset Card for "QBQTC"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
indonlp/nusaparagraph_rhetoric | indonlp | 2023-09-07T13:05:19Z | 341 | 0 | [
"license:apache-2.0",
"region:us"
]
| null | 2023-09-07T13:00:38Z | ---
license: apache-2.0
---
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|
sabilmakbar/sea_wiki | sabilmakbar | 2023-11-12T16:10:53Z | 341 | 0 | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"source_datasets:Wikipedia",
"language:ace",
"language:ban",
"language:bcl",
"language:bjn",
"language:bug",
"language:cbk",
"language:ceb",
"language:gor",
"language:id",
"language:ilo",
"language:jv",
"language:km",
"language:lo",
"language:mad",
"language:min",
"language:mnw",
"language:ms",
"language:my",
"language:nia",
"language:pag",
"language:pam",
"language:shn",
"language:su",
"language:ta",
"language:th",
"language:tl",
"language:tet",
"language:vi",
"language:war",
"license:cc-by-sa-4.0",
"Wikipedia",
"Southeast Asia (SEA)",
"Dialect",
"Banyumasan Dialect of Javanese (Ngapak)",
"SEA-related Languages",
"SEA Local Languages",
"region:us"
]
| [
"text-generation",
"fill-mask"
]
| 2023-11-03T14:44:10Z | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- ace
- ban
- bcl
- bjn
- bug
- cbk
- ceb
- gor
- id
- ilo
- jv
- km
- lo
- mad
- min
- mnw
- ms
- my
- nia
- pag
- pam
- shn
- su
- ta
- th
- tl
- tet
- vi
- war
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
source_datasets:
- Wikipedia
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
pretty_name: Wikipedia Archive for SEA Languages
tags:
- Wikipedia
- Southeast Asia (SEA)
- Dialect
- Banyumasan Dialect of Javanese (Ngapak)
- SEA-related Languages
- SEA Local Languages
dataset_info:
- config_name: seawiki_all
features:
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
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- name: vi
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- name: war
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- name: vi
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- name: war
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download_size: 1811459996
dataset_size: 10686876247
- config_name: seawiki_with_countries_all
features:
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dtype: string
- name: title
dtype: string
- name: text
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num_examples: 368628
- name: idn_ace
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- name: idn_gor
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- name: idn_id
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- name: idn_ms
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num_examples: 368628
- name: idn_nia
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- name: vnm_vi
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dataset_size: 13074580034
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dtype: string
- name: title
dtype: string
- name: text
dtype: string
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download_size: 1811459996
dataset_size: 12822599756
---
# **SEA Wikipedia Data Repository**
---
Welcome to SEA Wikipedia Data Repository. The datasets are extracted from [Wikipedia HF](https://huggingface.co/datasets/wikipedia) and processed using the scripts available in this repository for reproducibility purpose. Since Wikipedia iteslf has license [cc-by-sa 4.0](https://en.wikipedia.org/wiki/Wikipedia:Copyrights), we decided to follow this instead of Wikipedia HF data has of cc-by-sa 3.0 since it gives more rights to initial author/contributor.
# Getting Started #
### To read the datasets directly ###
Use one of the following code chunks to load it from HuggingFace Hub:
You can refer to the 2nd args of ```config name``` using the following script
```
dataset = load_dataset(
"sabilmakbar/sea_wiki",
"seawiki_dedup_all" # a config name, can be "seawiki_dedup_all" or "seawiki_with_countries_all", or "seawiki_with_countries_dedup_all" , defaults to "seawiki_dedup_all"
)
```
Or you can provide both ```lang``` and ```date_stamp``` (or just lang only by assuming the ```date_stamp``` will take the newest one)
```
dataset = load_dataset(
"sabilmakbar/sea_wiki",
lang = "id", # see README for complete lang choices
date_stamp="20230901"
)
```
Or you can provide a ```country``` params with similar fashion to ```lang``` args (providing both ```country``` and ```lang``` will prioritize the ```lang``` kwarg)
```
dataset = load_dataset(
"sabilmakbar/sea_wiki",
lang = "id", # see the splits for complete lang choices
date_stamp="20230901"
)
```
# **FAQS**
### What are the available languages provided in dataset and from which country?
You may check the following tables to understand the current coverage of this dataset (languages, countries, data size & volume). All tables are sorted by the leftmost column.
#### 1. Table of Countries and its Country Code
| Country Code | Country Name | Wiki Info |
| :---: | :---: | :---: |
| brn | Brunei | [Wiki Link](https://en.wikipedia.org/wiki/Brunei) |
| idn | Indonesia | [Wiki Link](https://en.wikipedia.org/wiki/Indonesia) |
| khm | Cambodia | [Wiki Link](https://en.wikipedia.org/wiki/Cambodia) |
| lao | Laos | [Wiki Link](https://en.wikipedia.org/wiki/Laos) |
| mmr | Myanmar | [Wiki Link](https://en.wikipedia.org/wiki/Myanmar) |
| mys | Malaysia | [Wiki Link](https://en.wikipedia.org/wiki/Malaysia) |
| phl | Philippines | [Wiki Link](https://en.wikipedia.org/wiki/Philippines) |
| sgp | Singapore | [Wiki Link](https://en.wikipedia.org/wiki/Singapore) |
| tha | Thailand | [Wiki Link](https://en.wikipedia.org/wiki/Thailand) |
| tls | East Timor | [Wiki Link](https://en.wikipedia.org/wiki/East_Timor) |
| vnm | Vietnam | [Wiki Link](https://en.wikipedia.org/wiki/Vietnam) |
#### 2. Table of Languages and Countries of its speakers
| ISO 639-3 Lang Code | Dataset Lang Code | Lang Name | Country Codes Spoken | Wiki Info | Total Data | Total Size (MiB rounded) |
| :---: | :---: | :---: | :---: | :--- | ---: | ---: |
| ace | ace | Acehnese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Acehnese_language) | 12979 | 4.72 |
| ban | ban | Balinese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Balinese_language) | 20611 | 17.19 |
| bcl | bcl | Central Bicolano | phl | [Wiki Link](https://en.wikipedia.org/wiki/Banjarese_language) | 14079 | 19.05 |
| bjn | bjn | Banjarese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Banjarese_language) | 10503 | 6.47 |
| bug | bug | Buginese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Buginese_language) | 9969 | 2.08 |
| bur | my | Burmese | mmr | [Wiki Link](https://en.wikipedia.org/wiki/Burmese_language) | 108819 | 298.49 |
| cbk | cbk_zam | Zamboanga Chavacano/Chavacano | phl | [Wiki Link](https://en.wikipedia.org/wiki/Chavacano) | 2242 | 1.51 |
| ceb | ceb | Cebuano | phl | [Wiki Link](https://en.wikipedia.org/wiki/Central_Bicolano_language) | 5815254 | 4,145.16 |
| gor | gor | Gorontalo | idn | [Wiki Link](https://en.wikipedia.org/wiki/Gorontalo_language) | 15290 | 5.93 |
| ilo | ilo | Ilokano | phl | [Wiki Link](https://en.wikipedia.org/wiki/Ilocano_language) | 15369 | 15.94 |
| ind | id | Indonesian | idn | [Wiki Link](https://en.wikipedia.org/wiki/Indonesian_language) | 662443 | 1,066.10 |
| jav | jv | Javanese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Javanese_language) | 73080 | 68.66 |
| khm | km | Khmer | khm | [Wiki Link](https://en.wikipedia.org/wiki/Khmer_language) | 11466 | 97.94 |
| lao | lo | Lao | lao | [Wiki Link](https://en.wikipedia.org/wiki/Lao_language) | 4897 | 14.22 |
| mad | mad | Madurese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Madurese_language) | 1192 | 1.54 |
| may | ms | Malay | mys, sgp, brn, idn | [Wiki Link](https://en.wikipedia.org/wiki/Malay_language) | 348045 | 395.57 |
| min | min | Minangkabau | idn | [Wiki Link](https://en.wikipedia.org/wiki/Minangkabau_language) | 225972 | 111.31 |
| mnw | mnw | Mon | mmr | [Wiki Link](https://en.wikipedia.org/wiki/Mon_language) | 3271 | 45.05 |
| nia | nia | Nias | idn | [Wiki Link](https://en.wikipedia.org/wiki/Nias_language) | 1714 | 2.05 |
| pag | pag | Pangasinan | phl | [Wiki Link](https://en.wikipedia.org/wiki/Pangasinan_language) | 1108 | 0.73 |
| pam | pam | Kapampangan | phl | [Wiki Link](https://en.wikipedia.org/wiki/Kapampangan_language) | 8932 | 7.83 |
| shn | shn | Shan | mmr | [Wiki Link](https://en.wikipedia.org/wiki/Shan_language) | 13662 | 32.06 |
| sun | su | Sundanese | idn | [Wiki Link](https://en.wikipedia.org/wiki/Sundanese_language) | 61529 | 45.31 |
| tam | ta | Tamil | mys, sgp | [Wiki Link](https://en.wikipedia.org/wiki/Tamil_language) | 160580 | 771.58 |
| tgl | tl | Tagalog | phl | [Wiki Link](https://en.wikipedia.org/wiki/Tagalog_language) | 45121 | 81.34 |
| tha | th | Thai | tha | [Wiki Link](https://en.wikipedia.org/wiki/Thai_language) | 159666 | 965.95 |
| tet | tet | Tetum | tls, idn | [Wiki Link](https://en.wikipedia.org/wiki/Tetum_language) | 1464 | 1.38 |
| vie | vi | Vietnamese | vnm | [Wiki Link](https://en.wikipedia.org/wiki/Vietnamese_language) | 1287912 | 1,528.58 |
| war | war | Waray | phl | [Wiki Link](https://en.wikipedia.org/wiki/Waray_language) | 1266204 | 433.22 |
| (dialect) | map_bms | Banyumasan <br>(Dialect of Javanese) | idn | [Wiki Link](https://en.wikipedia.org/wiki/Banyumasan_dialect) | 11839 | 4.83 |
#### 3. Table of Token Statistics for Covered Languages
The token statistics is generated using ```tiktoken``` using encoder for GPT-4.
| Dataset Lang Code | Total Token | Avg Token per Article | Min Token | Max Token | Token Deciles List |
| :---: | ---: | ---: | ---: | ---: | :--- |
| ace | 1,370,829 | 105.61899992295247 | 3 | 9,659 | [38.0, 52.0, 54.0, 69.0, 76.0, 84.0, 90.0, 123.0, 126.0] |
| ban | 5,924,610 | 287.44893503469024 | 5 | 24,364 | [97.0, 144.0, 165.0, 187.0, 209.0, 245.0, 276.0, 315.0, 421.0] |
| bcl | 6,234,838 | 442.8466510405569 | 2 | 54,049 | [55.0, 95.0, 143.0, 179.0, 226.0, 304.0, 419.0, 587.0, 917.2] |
| bjn | 1,935,505 | 184.28115776444827 | 2 | 30,170 | [36.0, 38.0, 39.0, 40.0, 42.0, 51.0, 82.0, 151.0, 367.0] |
| bug | 553,693 | 55.54147858360919 | 1 | 13,951 | [31.0, 42.0, 43.0, 46.0, 48.0, 50.0, 52.0, 55.0, 57.0] |
| cbk_zam | 402,703 | 179.6177520071365 | 2 | 6,494 | [35.0, 41.2, 56.0, 69.0, 90.0, 120.0, 138.0, 155.0, 294.9] |
| ceb | 1,319,601,771 | 226.92074516435568 | 4 | 221,802 | [93.0, 108.0, 123.0, 136.0, 163.0, 207.0, 278.0, 377.0, 426.0] |
| gor | 1,575,766 | 103.05860039241334 | 2 | 5,525 | [55.0, 58.0, 60.0, 62.0, 64.0, 66.0, 69.0, 75.0, 96.0] |
| id | 325,411,713 | 491.22975561670967 | 1 | 198,597 | [54.0, 93.0, 123.0, 145.0, 180.0, 226.0, 332.0, 543.0, 1068.0] |
| ilo | 5,593,491 | 363.94632051532307 | 17 | 18,202 | [59.0, 80.0, 91.0, 111.0, 152.0, 213.0, 303.0, 461.0, 856.0] |
| jv | 23,528,314 | 321.95284619594963 | 2 | 342,156 | [48.0, 60.0, 75.0, 88.0, 117.0, 175.0, 270.0, 420.0, 772.0] |
| km | 54,559,721 | 4,758.391854177568 | 1 | 1,110,771 | [160.0, 293.0, 452.0, 693.0, 1032.0, 1609.0, 2644.0, 4745.0, 9607.0] |
| lo | 9,395,636 | 1,918.6514192362672 | 3 | 107,154 | [134.0, 184.2, 285.0, 494.0, 658.0, 894.6, 1258.0, 1971.2, 4153.8] |
| mad | 611,736 | 513.2013422818792 | 14 | 17,093 | [80.1, 110.2, 135.0, 161.0, 194.0, 242.0, 302.7, 531.4, 1167.1] |
| map_bms | 1,307,244 | 110.41844750401216 | 1 | 20,629 | [20.0, 21.0, 22.0, 24.0, 30.0, 35.0, 36.0, 38.0, 111.0] |
| min | 33,114,184 | 146.54109358681606 | 3 | 58,387 | [81.0, 91.0, 96.0, 108.0, 119.0, 135.0, 156.0, 168.0, 170.0] |
| mnw | 31,595,647 | 9,659.3234484867 | 6 | 1,450,765 | [425.0, 601.0, 629.0, 682.0, 763.0, 2103.0, 4255.0, 7724.0, 14517.0] |
| ms | 121,343,673 | 348.64363228892813 | 1 | 68,545 | [32.0, 40.0, 49.0, 63.0, 105.0, 138.0, 216.0, 362.0, 788.0] |
| my | 189,439,447 | 1,740.8673761015998 | 10 | 1,376,658 | [164.0, 269.0, 350.0, 508.0, 559.0, 578.0, 605.0, 892.4, 3369.0] |
| nia | 795,527 | 464.134772462077 | 8 | 18,650 | [59.0, 61.0, 63.0, 65.0, 67.0, 86.0, 239.1, 623.4, 1249.7] |
| pag | 222,366 | 200.6913357400722 | 5 | 10,143 | [31.0, 51.0, 73.0, 110.0, 118.0, 120.0, 127.0, 181.0, 355.8] |
| pam | 2,269,091 | 254.04064039408868 | 1 | 14,912 | [38.0, 56.0, 78.0, 108.0, 121.0, 150.0, 193.0, 289.0, 525.8] |
| shn | 23,125,637 | 1,692.6977748499487 | 2 | 204,094 | [460.0, 480.0, 585.0, 679.0, 715.0, 740.0, 756.0, 780.0, 1580.9] |
| su | 14,710,124 | 239.07627297697022 | 1 | 99,456 | [41.0, 43.0, 45.0, 49.0, 70.0, 146.0, 216.0, 219.0, 419.0] |
| ta | 376,043,508 | 2,341.782961763607 | 15 | 177,054 | [543.0, 700.0, 824.0, 1001.0, 1153.0, 1465.0, 1992.0, 2911.0, 4652.0] |
| tet | 487,016 | 332.6612021857924 | 4 | 24,287 | [30.3, 47.0, 66.9, 101.0, 164.0, 177.0, 187.0, 248.6, 604.4] |
| th | 330,964,733 | 2,072.8566695476807 | 1 | 289,150 | [231.0, 390.0, 546.0, 727.0, 969.0, 1276.0, 1741.0, 2533.0, 4361.0] |
| tl | 27,789,730 | 615.8934864032269 | 7 | 60,728 | [73.0, 116.0, 161.0, 214.0, 281.0, 360.0, 465.0, 666.0, 1136.0] |
| vi | 546,481,913 | 424.3161900813099 | 3 | 246,463 | [46.0, 64.0, 71.0, 80.0, 86.0, 92.0, 120.0, 240.0, 824.0] |
| war | 117,438,315 | 92.74833676090108 | 1 | 25,689 | [60.0, 77.0, 81.0, 84.0, 87.0, 90.0, 94.0, 99.0, 110.0] |
Some other languages in SEA that are already exists its Wiki Index at Wikimedia might be missing from this list. Any lang update PR is greatly appreciated!
### How does the data being preprocessed? What makes it different from loading it directly from Wikipedia HF?
The data available in here are processed with following flows:
1. Raw data is being deduplicated on ```title``` and ```text``` (text-content from a given article), to remove articles containing boilerplate text (template text that are used usually for unavailable informations or asking for contributions of content in that article), which usually deemed noisy for NLP data.
2. Furthermore, the ```title``` and ```text``` data are being checked for string-matching duplication (duplication of text that are being pre-processed, i.e symbols removed, HTML tags striped, or ASCII-chars/UTF-8 chars validated).
The source code can be found on this Github Repo [SEA Wiki Github Source Code](https://github.com/sabilmakbar/sea_wiki)
### How do I extract new Wikipedia Dataset of SEA languages?
Please refer to the corresponding Github Repo for more detailed info [SEA Wiki Github Source Code](https://github.com/sabilmakbar/sea_wiki)
## Citation Info:
```
@ONLINE{wikidump,
author = "Wikimedia Foundation",
title = "Wikimedia Downloads",
url = "https://dumps.wikimedia.org"}
@ONLINE{wikipedia-hf,
title = "Huggingface Wikipedia Dataset",
url = "https://huggingface.co/datasets/wikipedia"}
```
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|
dengue_filipino | null | 2023-01-25T14:29:21Z | 340 | 1 | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:tl",
"license:unknown",
"region:us"
]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- crowdsourced
- machine-generated
language_creators:
- crowdsourced
language:
- tl
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
paperswithcode_id: dengue
pretty_name: Dengue Dataset in Filipino
dataset_info:
features:
- name: text
dtype: string
- name: absent
dtype:
class_label:
names:
'0': '0'
'1': '1'
- name: dengue
dtype:
class_label:
names:
'0': '0'
'1': '1'
- name: health
dtype:
class_label:
names:
'0': '0'
'1': '1'
- name: mosquito
dtype:
class_label:
names:
'0': '0'
'1': '1'
- name: sick
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 428553
num_examples: 4015
- name: test
num_bytes: 428553
num_examples: 4015
- name: validation
num_bytes: 54384
num_examples: 500
download_size: 156014
dataset_size: 911490
---
# Dataset Card for Dengue Dataset in Filipino
## 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:** [Dengue Dataset in Filipino homepage](https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks)
- **Repository:** [Dengue Dataset in Filipino repository](https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks)
- **Paper:** [IEEE paper](https://ieeexplore.ieee.org/document/8459963)
- **Leaderboard:**
- **Point of Contact:** [Jan Christian Cruz](mailto:[email protected])
### Dataset Summary
Benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
The dataset is primarily in Filipino, with the addition of some English words commonly used in Filipino vernacular.
## Dataset Structure
### Data Instances
Sample data:
```
{
"text": "Tapos ang dami pang lamok.",
"absent": "0",
"dengue": "0",
"health": "0",
"mosquito": "1",
"sick": "0"
}
```
### 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
[Jan Christian Cruz](mailto:[email protected])
### Licensing Information
[More Information Needed]
### Citation Information
@INPROCEEDINGS{8459963,
author={E. D. {Livelo} and C. {Cheng}},
booktitle={2018 IEEE International Conference on Agents (ICA)},
title={Intelligent Dengue Infoveillance Using Gated Recurrent Neural Learning and Cross-Label Frequencies},
year={2018},
volume={},
number={},
pages={2-7},
doi={10.1109/AGENTS.2018.8459963}}
}
### Contributions
Thanks to [@anaerobeth](https://github.com/anaerobeth) for adding this dataset. | [
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|
sent_comp | null | 2022-11-18T21:45:18Z | 340 | 1 | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:unknown",
"sentence-compression",
"region:us"
]
| [
"other"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: sentence-compression
pretty_name: Google Sentence Compression
tags:
- sentence-compression
dataset_info:
features:
- name: graph
struct:
- name: id
dtype: string
- name: sentence
dtype: string
- name: node
sequence:
- name: form
dtype: string
- name: type
dtype: string
- name: mid
dtype: string
- name: word
sequence:
- name: id
dtype: int32
- name: form
dtype: string
- name: stem
dtype: string
- name: tag
dtype: string
- name: gender
dtype: int32
- name: head_word_index
dtype: int32
- name: edge
sequence:
- name: parent_id
dtype: int32
- name: child_id
dtype: int32
- name: label
dtype: string
- name: entity_mention
sequence:
- name: start
dtype: int32
- name: end
dtype: int32
- name: head
dtype: int32
- name: name
dtype: string
- name: type
dtype: string
- name: mid
dtype: string
- name: is_proper_name_entity
dtype: bool
- name: gender
dtype: int32
- name: compression
struct:
- name: text
dtype: string
- name: edge
sequence:
- name: parent_id
dtype: int32
- name: child_id
dtype: int32
- name: headline
dtype: string
- name: compression_ratio
dtype: float32
- name: doc_id
dtype: string
- name: source_tree
struct:
- name: id
dtype: string
- name: sentence
dtype: string
- name: node
sequence:
- name: form
dtype: string
- name: type
dtype: string
- name: mid
dtype: string
- name: word
sequence:
- name: id
dtype: int32
- name: form
dtype: string
- name: stem
dtype: string
- name: tag
dtype: string
- name: gender
dtype: int32
- name: head_word_index
dtype: int32
- name: edge
sequence:
- name: parent_id
dtype: int32
- name: child_id
dtype: int32
- name: label
dtype: string
- name: entity_mention
sequence:
- name: start
dtype: int32
- name: end
dtype: int32
- name: head
dtype: int32
- name: name
dtype: string
- name: type
dtype: string
- name: mid
dtype: string
- name: is_proper_name_entity
dtype: bool
- name: gender
dtype: int32
- name: compression_untransformed
struct:
- name: text
dtype: string
- name: edge
sequence:
- name: parent_id
dtype: int32
- name: child_id
dtype: int32
splits:
- name: validation
num_bytes: 55823979
num_examples: 10000
- name: train
num_bytes: 1135684803
num_examples: 200000
download_size: 259652560
dataset_size: 1191508782
---
# Dataset Card for Google Sentence Compression
## 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/google-research-datasets/sentence-compression](https://github.com/google-research-datasets/sentence-compression)
- **Repository:** [https://github.com/google-research-datasets/sentence-compression](https://github.com/google-research-datasets/sentence-compression)
- **Paper:** [https://www.aclweb.org/anthology/D13-1155/](https://www.aclweb.org/anthology/D13-1155/)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
A major challenge in supervised sentence compression is making use of rich feature representations because of very scarce parallel data. We address this problem and present a method to automatically build a compression corpus with hundreds of thousands of instances on which deletion-based algorithms can be trained. In our corpus, the syntactic trees of the compressions are subtrees of their uncompressed counterparts, and hence supervised systems which require a structural alignment between the input and output can be successfully trained. We also extend an existing unsupervised compression method with a learning module. The new system uses structured prediction to learn from lexical, syntactic and other features. An evaluation with human raters shows that the presented data harvesting method indeed produces a parallel corpus of high quality. Also, the supervised system trained on this corpus gets high scores both from human raters and in an automatic evaluation setting, significantly outperforming a strong baseline.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
English
## Dataset Structure
### Data Instances
Each data instance should contains the information about the original sentence in `instance["graph"]["sentence"]` as well as the compressed sentence in `instance["compression"]["text"]`. As this dataset was created by pruning dependency connections, the author also includes the dependency tree and transformed graph of the original sentence and compressed sentence.
### Data Fields
Each instance should contains these information:
- `graph` (`Dict`): the transformation graph/tree for extracting compression (a modified version of a dependency tree).
- This will have features similar to a dependency tree (listed bellow)
- `compression` (`Dict`)
- `text` (`str`)
- `edge` (`List`)
- `headline` (`str`): the headline of the original news page.
- `compression_ratio` (`float`): the ratio between compressed sentence vs original sentence.
- `doc_id` (`str`): url of the original news page.
- `source_tree` (`Dict`): the original dependency tree (features listed bellow).
- `compression_untransformed` (`Dict`)
- `text` (`str`)
- `edge` (`List`)
Dependency tree features:
- `id` (`str`)
- `sentence` (`str`)
- `node` (`List`): list of nodes, each node represent a word/word phrase in the tree.
- `form` (`string`)
- `type` (`string`): the enity type of a node. Defaults to `""` if it's not an entity.
- `mid` (`string`)
- `word` (`List`): list of words the node contains.
- `id` (`int`)
- `form` (`str`): the word from the sentence.
- `stem` (`str`): the stemmed/lemmatized version of the word.
- `tag` (`str`): dependency tag of the word.
- `gender` (`int`)
- `head_word_index` (`int`)
- `edge`: list of the dependency connections between words.
- `parent_id` (`int`)
- `child_id` (`int`)
- `label` (`str`)
- `entity_mention` list of the entities in the sentence.
- `start` (`int`)
- `end` (`int`)
- `head` (`str`)
- `name` (`str`)
- `type` (`str`)
- `mid` (`str`)
- `is_proper_name_entity` (`bool`)
- `gender` (`int`)
### 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 [@mattbui](https://github.com/mattbui) for adding this dataset. | [
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|
RohanAiLab/persian_blog | RohanAiLab | 2022-10-25T09:06:36Z | 340 | 2 | [
"task_categories:text-generation",
"task_ids:language-modeling",
"source_datasets:original",
"language:fa",
"region:us"
]
| [
"text-generation"
]
| 2022-03-02T23:29:22Z | ---
language:
- fa
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: persian_blog
---
# Persian Blog
# Dataset Summary
persian_news_dataset is a collection of 400k blog posts. these posts have been gathered from more than 10 websites. This dataset can be used in different NLP tasks like language modeling and text generation tasks.
This effort is part of a bigger perspective to have several datasets in Persian language for different tasks that have two important factors: `free` and `easy-to-use`. Here is a quick HOW-TO for using this dataset in datasets library:[Demo-datasets](https://saied71.github.io/RohanAiLab/2021/09/03/Demo-datasets.html)
# Description
As discussed before, this dataset contains 5M news articles. Each article has these three attributes: text, title, category. Here is a sample of dataset:
```
text : چرا کودکان به روانشناس نیاز دارند؟ روانشناسی کودکانکودکان همچون غنچههای زیبا هستند که برای شکوفایی و به ثمر رسیدن نیاز به مراقبت و رسیدگی دارند . روانشناس کودک فردیست که از زمان بدو تولد کودک در مراحل مختلف زندگی کودک در کنار والدین وی میباشد و به چگونگی تربیت کودک کمک میکند تا به بهترین شکل رشد کند . چرا که روانشناس کودک با روحیات ، نیازها و مشکلات کودکان و همچنین چگونگی برقراری ارتباط بین کودک و والدین وی آشنایی کامل دارد .بسیاری از کودکان در سنین مختلف بخاطر شرایط زندگی ، دچار انواع ناسازگاریها و مشکلات در زندگی خود میشود از ناسازگاری کودکان میتوان به موارد زیر اشاره کرد : 1 . پرخاشگری 2 . بد دهنی 3 . اختلال در خوابیدن 4 . اختلال در غذا خوردن و کم اشتهایی 5 . حالت افسردگی و اضطراب 6 . ترس از محیط پیرامون 7 . عدم آمادگی برای ورود به جامعه 8 . وجود مشکل در محیط مدرسه 9 . عدم تمرکز 10 . جویدن ناخن ها 11 . انزوا و گوشه گیری 12 . عدم هم بازی شدن با هم سن و سال هاو .این گونه ناسازگاریها در زندگی آینده کودک نقش به سزایی دارد .روانشناس کودکیک روانشناس کودک خوب ، با دلسوزی و با تکیه بر تجربیات و تخصص خود میکوشد تا رفتارهای کودک را مورد ارزیابی و بررسی قرار دهد سپس سعی میکند تا رفتارهای بعدی کودک را پیش بینی کند و منشاء این مشکلات و سطح پیشرفت آن را بیابد. سپس او بهترین روشهای درمان برای بهبود اختلال کودک را مییابد و با کمک والدین این ناسازگاریها ، مشکلات و ناهنجاریها را حل کرده و نهایتا رابطهای دوستانه و صمیمانه بین کودک و والدین وی ایجاد مینماید تاآیندهای درخشان در انتظار کودک شما باشد .
```
# Citation
```
[email protected]
title={persian_blog},
author={Saied Alimoradi},
year={2021}
}
``` | [
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|
open-llm-leaderboard/details_EleutherAI__gpt-neo-2.7B | open-llm-leaderboard | 2023-09-16T18:17:38Z | 340 | 0 | [
"region:us"
]
| null | 2023-08-17T23:48:27Z | ---
pretty_name: Evaluation run of EleutherAI/gpt-neo-2.7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [EleutherAI/gpt-neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-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_EleutherAI__gpt-neo-2.7B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-16T18:17:27.118418](https://huggingface.co/datasets/open-llm-leaderboard/details_EleutherAI__gpt-neo-2.7B/blob/main/results_2023-09-16T18-17-27.118418.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\": 0.0003778609196460643,\n \"f1\": 0.04774853187919481,\n\
\ \"f1_stderr\": 0.0012502430800989544,\n \"acc\": 0.3067599823596958,\n\
\ \"acc_stderr\": 0.008435917406608623\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.001363255033557047,\n \"em_stderr\": 0.0003778609196460643,\n\
\ \"f1\": 0.04774853187919481,\n \"f1_stderr\": 0.0012502430800989544\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.01288855193328279,\n \
\ \"acc_stderr\": 0.003106901266499639\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6006314127861089,\n \"acc_stderr\": 0.013764933546717609\n\
\ }\n}\n```"
repo_url: https://huggingface.co/EleutherAI/gpt-neo-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_19T17_18_37.000373
path:
- '**/details_harness|arc:challenge|25_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_16T18_17_27.118418
path:
- '**/details_harness|drop|3_2023-09-16T18-17-27.118418.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-16T18-17-27.118418.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_16T18_17_27.118418
path:
- '**/details_harness|gsm8k|5_2023-09-16T18-17-27.118418.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-16T18-17-27.118418.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hellaswag|10_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:18:37.000373.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T17:18:37.000373.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T17:18:37.000373.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_16T18_17_27.118418
path:
- '**/details_harness|winogrande|5_2023-09-16T18-17-27.118418.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-16T18-17-27.118418.parquet'
- config_name: results
data_files:
- split: 2023_07_19T17_18_37.000373
path:
- results_2023-07-19T17:18:37.000373.parquet
- split: 2023_09_16T18_17_27.118418
path:
- results_2023-09-16T18-17-27.118418.parquet
- split: latest
path:
- results_2023-09-16T18-17-27.118418.parquet
---
# Dataset Card for Evaluation run of EleutherAI/gpt-neo-2.7B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/EleutherAI/gpt-neo-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 [EleutherAI/gpt-neo-2.7B](https://huggingface.co/EleutherAI/gpt-neo-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_EleutherAI__gpt-neo-2.7B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-16T18:17:27.118418](https://huggingface.co/datasets/open-llm-leaderboard/details_EleutherAI__gpt-neo-2.7B/blob/main/results_2023-09-16T18-17-27.118418.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": 0.0003778609196460643,
"f1": 0.04774853187919481,
"f1_stderr": 0.0012502430800989544,
"acc": 0.3067599823596958,
"acc_stderr": 0.008435917406608623
},
"harness|drop|3": {
"em": 0.001363255033557047,
"em_stderr": 0.0003778609196460643,
"f1": 0.04774853187919481,
"f1_stderr": 0.0012502430800989544
},
"harness|gsm8k|5": {
"acc": 0.01288855193328279,
"acc_stderr": 0.003106901266499639
},
"harness|winogrande|5": {
"acc": 0.6006314127861089,
"acc_stderr": 0.013764933546717609
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_MayaPH__GodziLLa2-70B | open-llm-leaderboard | 2023-12-01T14:52:03Z | 340 | 0 | [
"region:us"
]
| null | 2023-08-17T23:55:34Z | ---
pretty_name: Evaluation run of MayaPH/GodziLLa2-70B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [MayaPH/GodziLLa2-70B](https://huggingface.co/MayaPH/GodziLLa2-70B) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 3 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_MayaPH__GodziLLa2-70B_public\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-11-08T19:39:50.850432](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__GodziLLa2-70B_public/blob/main/results_2023-11-08T19-39-50.850432.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\": 0.40918624161073824,\n\
\ \"em_stderr\": 0.0050353012998842275,\n \"f1\": 0.523052642617452,\n\
\ \"f1_stderr\": 0.004562583016028929,\n \"acc\": 0.6320159552601676,\n\
\ \"acc_stderr\": 0.01207770454600458\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.40918624161073824,\n \"em_stderr\": 0.0050353012998842275,\n\
\ \"f1\": 0.523052642617452,\n \"f1_stderr\": 0.004562583016028929\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.43214556482183475,\n \
\ \"acc_stderr\": 0.013645072137842443\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8318863456985004,\n \"acc_stderr\": 0.010510336954166718\n\
\ }\n}\n```"
repo_url: https://huggingface.co/MayaPH/GodziLLa2-70B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_drop_3
data_files:
- split: 2023_11_08T19_39_50.850432
path:
- '**/details_harness|drop|3_2023-11-08T19-39-50.850432.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-11-08T19-39-50.850432.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_11_08T19_39_50.850432
path:
- '**/details_harness|gsm8k|5_2023-11-08T19-39-50.850432.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-11-08T19-39-50.850432.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_11_08T19_39_50.850432
path:
- '**/details_harness|winogrande|5_2023-11-08T19-39-50.850432.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-11-08T19-39-50.850432.parquet'
- config_name: results
data_files:
- split: 2023_11_08T19_39_50.850432
path:
- results_2023-11-08T19-39-50.850432.parquet
- split: latest
path:
- results_2023-11-08T19-39-50.850432.parquet
---
# Dataset Card for Evaluation run of MayaPH/GodziLLa2-70B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/MayaPH/GodziLLa2-70B
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [MayaPH/GodziLLa2-70B](https://huggingface.co/MayaPH/GodziLLa2-70B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_MayaPH__GodziLLa2-70B_public",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-11-08T19:39:50.850432](https://huggingface.co/datasets/open-llm-leaderboard/details_MayaPH__GodziLLa2-70B_public/blob/main/results_2023-11-08T19-39-50.850432.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": 0.40918624161073824,
"em_stderr": 0.0050353012998842275,
"f1": 0.523052642617452,
"f1_stderr": 0.004562583016028929,
"acc": 0.6320159552601676,
"acc_stderr": 0.01207770454600458
},
"harness|drop|3": {
"em": 0.40918624161073824,
"em_stderr": 0.0050353012998842275,
"f1": 0.523052642617452,
"f1_stderr": 0.004562583016028929
},
"harness|gsm8k|5": {
"acc": 0.43214556482183475,
"acc_stderr": 0.013645072137842443
},
"harness|winogrande|5": {
"acc": 0.8318863456985004,
"acc_stderr": 0.010510336954166718
}
}
```
### 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] | [
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|
yys/OpenOrca-Chinese | yys | 2023-09-08T08:05:47Z | 340 | 58 | [
"task_categories:conversational",
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:table-question-answering",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"task_categories:summarization",
"task_categories:feature-extraction",
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10M<n<100M",
"language:zh",
"license:mit",
"arxiv:2301.13688",
"region:us"
]
| [
"conversational",
"text-classification",
"token-classification",
"table-question-answering",
"question-answering",
"zero-shot-classification",
"summarization",
"feature-extraction",
"text-generation",
"text2text-generation"
]
| 2023-09-07T06:01:51Z | ---
license: mit
task_categories:
- conversational
- text-classification
- token-classification
- table-question-answering
- question-answering
- zero-shot-classification
- summarization
- feature-extraction
- text-generation
- text2text-generation
language:
- zh
pretty_name: OpenOrca-Chinese
size_categories:
- 10M<n<100M
---
<p><h1>🐋 OpenOrca-Chinese 数据集！🐋</h1></p>
感谢 [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) 数据集的发布，给广大NLP研究人员和开发者带来了宝贵的资源！
这是一个对 [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) 数据集中文翻译的版本，翻译引擎为 Google 翻译，希望能给中文 LLM 研究做出一点点贡献。
<br/>
# Dataset Summary
The OpenOrca dataset is a collection of augmented [FLAN Collection data](https://arxiv.org/abs/2301.13688).
Currently ~1M GPT-4 completions, and ~3.2M GPT-3.5 completions.
It is tabularized in alignment with the distributions presented in the ORCA paper and currently represents a partial completion of the full intended dataset, with ongoing generation to expand its scope.
The data is primarily used for training and evaluation in the field of natural language processing.
<a name="dataset-structure"></a>
# Dataset Structure
<a name="data-instances"></a>
## Data Instances
A data instance in this dataset represents entries from the FLAN collection which have been augmented by submitting the listed question to either GPT-4 or GPT-3.5.
The response is then entered into the response field.
<a name="data-fields"></a>
## Data Fields
The fields are:
1) 'id', a unique numbered identifier which includes one of 'niv', 't0', 'cot', or 'flan' to represent which source FLAN Collection submix the 'question' is sourced from.
2) 'system_prompt', representing the System Prompt presented to the GPT-3.5 or GPT-4 API for the datapoint
3) 'question', representing a question entry as provided by the FLAN Collection
4) 'response', a response to that question received from a query to either GPT-3.5 or GPT-4.
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|
open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Base-LLaMAfied | open-llm-leaderboard | 2023-10-26T06:44:37Z | 340 | 0 | [
"region:us"
]
| null | 2023-10-10T07:26:05Z | ---
pretty_name: Evaluation run of hiyouga/Baichuan2-7B-Base-LLaMAfied
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [hiyouga/Baichuan2-7B-Base-LLaMAfied](https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied)\
\ 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_hiyouga__Baichuan2-7B-Base-LLaMAfied\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-26T06:44:24.493952](https://huggingface.co/datasets/open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Base-LLaMAfied/blob/main/results_2023-10-26T06-44-24.493952.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\": 0.001572986577181208,\n\
\ \"em_stderr\": 0.0004058451132417743,\n \"f1\": 0.0585476090604028,\n\
\ \"f1_stderr\": 0.0013740361163735455,\n \"acc\": 0.3926358910777041,\n\
\ \"acc_stderr\": 0.010089987799825416\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.001572986577181208,\n \"em_stderr\": 0.0004058451132417743,\n\
\ \"f1\": 0.0585476090604028,\n \"f1_stderr\": 0.0013740361163735455\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.07808946171341925,\n \
\ \"acc_stderr\": 0.007390654481108214\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7071823204419889,\n \"acc_stderr\": 0.01278932111854262\n\
\ }\n}\n```"
repo_url: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
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_10T07_25_43.126145
path:
- '**/details_harness|arc:challenge|25_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_26T06_44_24.493952
path:
- '**/details_harness|drop|3_2023-10-26T06-44-24.493952.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-26T06-44-24.493952.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_26T06_44_24.493952
path:
- '**/details_harness|gsm8k|5_2023-10-26T06-44-24.493952.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-26T06-44-24.493952.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hellaswag|10_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-25-43.126145.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T07-25-43.126145.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-10T07-25-43.126145.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_26T06_44_24.493952
path:
- '**/details_harness|winogrande|5_2023-10-26T06-44-24.493952.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-26T06-44-24.493952.parquet'
- config_name: results
data_files:
- split: 2023_10_10T07_25_43.126145
path:
- results_2023-10-10T07-25-43.126145.parquet
- split: 2023_10_26T06_44_24.493952
path:
- results_2023-10-26T06-44-24.493952.parquet
- split: latest
path:
- results_2023-10-26T06-44-24.493952.parquet
---
# Dataset Card for Evaluation run of hiyouga/Baichuan2-7B-Base-LLaMAfied
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
- **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 [hiyouga/Baichuan2-7B-Base-LLaMAfied](https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied) 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_hiyouga__Baichuan2-7B-Base-LLaMAfied",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-26T06:44:24.493952](https://huggingface.co/datasets/open-llm-leaderboard/details_hiyouga__Baichuan2-7B-Base-LLaMAfied/blob/main/results_2023-10-26T06-44-24.493952.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": 0.001572986577181208,
"em_stderr": 0.0004058451132417743,
"f1": 0.0585476090604028,
"f1_stderr": 0.0013740361163735455,
"acc": 0.3926358910777041,
"acc_stderr": 0.010089987799825416
},
"harness|drop|3": {
"em": 0.001572986577181208,
"em_stderr": 0.0004058451132417743,
"f1": 0.0585476090604028,
"f1_stderr": 0.0013740361163735455
},
"harness|gsm8k|5": {
"acc": 0.07808946171341925,
"acc_stderr": 0.007390654481108214
},
"harness|winogrande|5": {
"acc": 0.7071823204419889,
"acc_stderr": 0.01278932111854262
}
}
```
### 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] | [
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|
caner | null | 2023-03-16T14:47:48Z | 339 | 1 | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar",
"license:unknown",
"region:us"
]
| [
"token-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: CANER
dataset_info:
features:
- name: token
dtype: string
- name: ner_tag
dtype:
class_label:
names:
'0': Allah
'1': Book
'2': Clan
'3': Crime
'4': Date
'5': Day
'6': Hell
'7': Loc
'8': Meas
'9': Mon
'10': Month
'11': NatOb
'12': Number
'13': O
'14': Org
'15': Para
'16': Pers
'17': Prophet
'18': Rlig
'19': Sect
'20': Time
splits:
- name: train
num_bytes: 5095721
num_examples: 258240
download_size: 17063406
dataset_size: 5095721
---
# Dataset Card for CANER
## 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:** [Classical-Arabic-Named-Entity-Recognition-Corpus](https://github.com/RamziSalah)
- **Paper:** [Researchgate](https://www.researchgate.net/publication/330075080_BUILDING_THE_CLASSICAL_ARABIC_NAMED_ENTITY_RECOGNITION_CORPUS_CANERCORPUS)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
The Classical Arabic Named Entity Recognition corpus is a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.
### Supported Tasks and Leaderboards
- Named Entity Recognition
### Languages
Classical Arabic
## Dataset Structure
### Data Instances
An example from the dataset:
```
{'ner_tag': 1, 'token': 'الجامع'}
```
Where 1 stands for "Book"
### Data Fields
- `id`: id of the sample
- `token`: the tokens of the example text
- `ner_tag`: the NER tags of each token
The NER tags correspond to this list:
```
"Allah",
"Book",
"Clan",
"Crime",
"Date",
"Day",
"Hell",
"Loc",
"Meas",
"Mon",
"Month",
"NatOb",
"Number",
"O",
"Org",
"Para",
"Pers",
"Prophet",
"Rlig",
"Sect",
"Time"
```
### Data Splits
Training splits only
## 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?
Ramzi Salah and Lailatul Qadri Zakaria
### 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
[More Information Needed]
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
@article{article,
author = {Salah, Ramzi and Zakaria, Lailatul},
year = {2018},
month = {12},
pages = {},
title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
volume = {96},
journal = {Journal of Theoretical and Applied Information Technology}
}
### Contributions
Thanks to [@KMFODA](https://github.com/KMFODA) for adding this dataset. | [
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|
GEM/squad_v2 | GEM | 2022-10-24T15:30:29Z | 339 | 0 | [
"task_categories:other",
"annotations_creators:crowd-sourced",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"question-generation",
"arxiv:1806.03822",
"region:us"
]
| [
"other"
]
| 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:
- other
task_ids: []
pretty_name: squad_v2
tags:
- question-generation
---
# Dataset Card for GEM/squad_v2
## Dataset Description
- **Homepage:** https://rajpurkar.github.io/SQuAD-explorer/
- **Repository:** https://rajpurkar.github.io/SQuAD-explorer/
- **Paper:** https://arxiv.org/abs/1806.03822v1
- **Leaderboard:** https://rajpurkar.github.io/SQuAD-explorer/
- **Point of Contact:** Robin Jia
### Link to Main Data Card
You can find the main data card on the [GEM Website](https://gem-benchmark.com/data_cards/squad_v2).
### Dataset Summary
SQuAD2.0 is a dataset that tests the ability of a system to not only answer reading comprehension questions, but also abstain when presented with a question that cannot be answered based on the provided paragraph. F1 score is used to evaluate models on the leaderboard. In GEM, we are using this dataset for the question-generation task in which a model should generate squad-like questions from an input text.
You can load the dataset via:
```
import datasets
data = datasets.load_dataset('GEM/squad_v2')
```
The data loader can be found [here](https://huggingface.co/datasets/GEM/squad_v2).
#### website
[Website](https://rajpurkar.github.io/SQuAD-explorer/)
#### paper
[Arxiv](https://arxiv.org/abs/1806.03822v1)
#### authors
Pranav Rajpurkar, Robin Jia and Percy Liang
## Dataset Overview
### Where to find the Data and its Documentation
#### Webpage
<!-- info: What is the webpage for the dataset (if it exists)? -->
<!-- scope: telescope -->
[Website](https://rajpurkar.github.io/SQuAD-explorer/)
#### Download
<!-- info: What is the link to where the original dataset is hosted? -->
<!-- scope: telescope -->
[Website](https://rajpurkar.github.io/SQuAD-explorer/)
#### Paper
<!-- info: What is the link to the paper describing the dataset (open access preferred)? -->
<!-- scope: telescope -->
[Arxiv](https://arxiv.org/abs/1806.03822v1)
#### 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{Rajpurkar2018KnowWY,
title={Know What You Don’t Know: Unanswerable Questions for SQuAD},
author={Pranav Rajpurkar and Robin Jia and Percy Liang},
booktitle={ACL},
year={2018}
}
```
#### 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 -->
Robin Jia
#### 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 -->
yes
#### Leaderboard Link
<!-- info: Provide a link to the leaderboard. -->
<!-- scope: periscope -->
[Website](https://rajpurkar.github.io/SQuAD-explorer/)
#### Leaderboard Details
<!-- info: Briefly describe how the leaderboard evaluates models. -->
<!-- scope: microscope -->
SQuAD2.0 tests the ability of a system to not only answer reading comprehension questions, but also abstain when presented with a question that cannot be answered based on the provided paragraph. F1 score is used to evaluate models on the leaderboard.
### 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`
#### 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 idea behind SQuAD2.0 dataset is to make the models understand when a question cannot be answered given a context. This will help in building models such that they know what they don't know, and therefore make the models understand language at a deeper level. The tasks that can be supported by the dataset are machine reading comprehension, extractive QA, and question generation.
#### Primary Task
<!-- info: What primary task does the dataset support? -->
<!-- scope: telescope -->
Question 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 -->
Given an input passage and an answer span, the goal is to generate a question that asks for the answer.
### Credit
#### Curation Organization Type(s)
<!-- info: In what kind of organization did the dataset curation happen? -->
<!-- scope: telescope -->
`academic`
#### Curation Organization(s)
<!-- info: Name the organization(s). -->
<!-- scope: periscope -->
Stanford University
#### Dataset Creators
<!-- info: Who created the original dataset? List the people involved in collecting the dataset and their affiliation(s). -->
<!-- scope: microscope -->
Pranav Rajpurkar, Robin Jia and Percy Liang
#### Funding
<!-- info: Who funded the data creation? -->
<!-- scope: microscope -->
Facebook and NSF Graduate Research Fellowship under Grant No. DGE-114747
#### 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 -->
(Abinaya Mahendiran)[https://github.com/AbinayaM02], Manager Data Science, NEXT Labs,
### Dataset Structure
#### Data Fields
<!-- info: List and describe the fields present in the dataset. -->
<!-- scope: telescope -->
The data fields are the same among all splits.
#### squad_v2
- `id`: a `string` feature.
- `gem_id`: a `string` feature.
- `title`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
- `text`: a `string` feature.
- `answer_start`: a `int32` feature.
#### Example Instance
<!-- info: Provide a JSON formatted example of a typical instance in the dataset. -->
<!-- scope: periscope -->
Here is an example of a validation data point. This example was too long and was cropped:
```
{
"gem_id": "gem-squad_v2-validation-1",
"id": "56ddde6b9a695914005b9629",
"answers": {
"answer_start": [94, 87, 94, 94],
"text": ["10th and 11th centuries", "in the 10th and 11th centuries", "10th and 11th centuries", "10th and 11th centuries"]
},
"context": "\"The Normans (Norman: Nourmands; French: Normands; Latin: Normanni) were the people who in the 10th and 11th centuries gave thei...",
"question": "When were the Normans in Normandy?",
"title": "Normans"
}
```
#### Data Splits
<!-- info: Describe and name the splits in the dataset if there are more than one. -->
<!-- scope: periscope -->
The original SQuAD2.0 dataset has only training and dev (validation) splits. The train split is further divided into test split and added as part of the GEM datasets.
| name | train | validation | test |
| -------------- | --------: | -------------: | -------: |
| squad_v2 | 90403 | 11873 | 39916 |
## 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 -->
SQuAD2.0 will encourage the development of new reading comprehension models
that know what they don’t know, and therefore understand language at a deeper level. It can also help in building better models for answer-aware question generation .
#### Similar Datasets
<!-- info: Do other datasets for the high level task exist? -->
<!-- scope: telescope -->
no
#### Unique Language Coverage
<!-- info: Does this dataset cover other languages than other datasets for the same task? -->
<!-- scope: periscope -->
yes
#### Ability that the Dataset measures
<!-- info: What aspect of model ability can be measured with this dataset? -->
<!-- scope: periscope -->
Reasoning capability
### 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 -->
`other`
#### 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 -->
The train(80%) and validation(10%) split of SQuAD2.0 are made available to public whereas the test(10%) split is not available.
As part of GEM, the train split, 80% of the original data is split into two train split (90%) and test split (remaining 10%). The idea is to provide all three splits for the users to use.
### Getting Started with the Task
## Previous Results
### Previous Results
#### Measured Model Abilities
<!-- info: What aspect of model ability can be measured with this dataset? -->
<!-- scope: telescope -->
Extractive QA, Question Generation
#### Metrics
<!-- info: What metrics are typically used for this task? -->
<!-- scope: periscope -->
`Other: Other Metrics`, `METEOR`, `ROUGE`, `BLEU`
#### Other Metrics
<!-- info: Definitions of other metrics -->
<!-- scope: periscope -->
- Extractive QA uses Exact Match and F1 Score
- Question generation users METEOR, ROUGE-L, BLEU-4
#### Previous results available?
<!-- info: Are previous results available? -->
<!-- scope: telescope -->
yes
#### Other Evaluation Approaches
<!-- info: What evaluation approaches have others used? -->
<!-- scope: periscope -->
Question generation users METEOR, ROUGE-L, BLEU-4
#### Relevant Previous Results
<!-- info: What are the most relevant previous results for this task/dataset? -->
<!-- scope: microscope -->
@article{Dong2019UnifiedLM,
title={Unified Language Model Pre-training for Natural Language Understanding and Generation},
author={Li Dong and Nan Yang and Wenhui Wang and Furu Wei and Xiaodong Liu and Yu Wang and Jianfeng Gao and M. Zhou and Hsiao-Wuen Hon},
journal={ArXiv},
year={2019},
volume={abs/1905.03197}
}
## Dataset Curation
### Original Curation
#### Original Curation Rationale
<!-- info: Original curation rationale -->
<!-- scope: telescope -->
The dataset is curated in three stages:
- Curating passages,
- Crowdsourcing question-answers on those passages,
- Obtaining additional answers
As part of SQuAD1.1, 10000 high-quality articles from English Wikipedia is extracted using Project Nayuki’s Wikipedia’s internal PageRanks, from which 536 articles are sampled uniformly at random. From each of these articles, individual paragraphs are extracted, stripping away images, figures, tables, and discarding paragraphs shorter than 500 characters.
SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers to look similar to answerable ones.
#### Communicative Goal
<!-- info: What was the communicative goal? -->
<!-- scope: periscope -->
To build systems that not only answer questions when possible, but also determine when no
answer is supported by the paragraph and abstain from answering.
#### Sourced from Different Sources
<!-- info: Is the dataset aggregated from different data sources? -->
<!-- scope: telescope -->
yes
#### Source Details
<!-- info: List the sources (one per line) -->
<!-- scope: periscope -->
Wikipedia
### Language Data
#### How was Language Data Obtained?
<!-- info: How was the language data obtained? -->
<!-- scope: telescope -->
`Found`
#### Where was it found?
<!-- info: If found, where from? -->
<!-- scope: telescope -->
`Single website`
#### Topics Covered
<!-- info: Does the language in the dataset focus on specific topics? How would you describe them? -->
<!-- scope: periscope -->
The dataset contains 536 articles covering a wide range of topics, from musical celebrities to abstract concepts.
#### Data Validation
<!-- info: Was the text validated by a different worker or a data curator? -->
<!-- scope: telescope -->
validated by crowdworker
#### Data Preprocessing
<!-- info: How was the text data pre-processed? (Enter N/A if the text was not pre-processed) -->
<!-- scope: microscope -->
From the sampled articles from Wikipedia, individual paragraphs are extracted, stripping
away images, figures, tables, and discarding paragraphs shorter than 500 characters and partitioned into training(80%), development set(10%) and test set(10%).
#### Was Data Filtered?
<!-- info: Were text instances selected or filtered? -->
<!-- scope: telescope -->
algorithmically
#### Filter Criteria
<!-- info: What were the selection criteria? -->
<!-- scope: microscope -->
To retrieve high-quality articles, Project Nayuki’s Wikipedia’s internal PageRanks was used to obtain the top 10000 articles of English Wikipedia, from which 536 articles are sampled uniformly at random.
### 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
#### Rater Qualifications
<!-- info: Describe the qualifications required of an annotator. -->
<!-- scope: periscope -->
Crowdworkers from the United States or Canada with a 97% HIT acceptance rate, a minimum of 1000 HITs, were employed to create questions.
#### 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 -->
yes
#### Which Annotation Service
<!-- info: Which annotation services were used? -->
<!-- scope: periscope -->
`other`, `Amazon Mechanical Turk`
#### Annotation Values
<!-- info: Purpose and values for each annotation -->
<!-- scope: microscope -->
For SQuAD 1.1 , crowdworkers were tasked with asking and answering up to 5 questions on the
content of that paragraph. The questions had to be entered in a text field, and the answers had to be
highlighted in the paragraph.
For SQuAD2.0, each task consisted of an entire article from SQuAD 1.1. For each paragraph in the article, workers were asked to pose up to five questions that were impossible to answer
based on the paragraph alone, while referencing entities in the paragraph and ensuring that a plausible answer is present.
#### Any Quality Control?
<!-- info: Quality control measures? -->
<!-- scope: telescope -->
validated by another rater
#### Quality Control Details
<!-- info: Describe the quality control measures that were taken. -->
<!-- scope: microscope -->
Questions from workers who wrote 25 or fewer questions on an article is removed; this filter
helped remove noise from workers who had trouble understanding the task, and therefore quit before completing the whole article. This filter to both SQuAD2.0 and the existing answerable questions from SQuAD 1.1.
### Consent
#### Any Consent Policy?
<!-- info: Was there a consent policy involved when gathering the data? -->
<!-- scope: telescope -->
no
### 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 -->
unlikely
#### Any PII Identification?
<!-- info: Did the curators use any automatic/manual method to identify PII in the dataset? -->
<!-- scope: periscope -->
no identification
### 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 -->
yes
## Considerations for Using the Data
### PII Risks and Liability
### Licenses
### Known Technical Limitations
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|
open-llm-leaderboard/details_microsoft__DialoGPT-medium | open-llm-leaderboard | 2023-12-03T18:16:01Z | 339 | 0 | [
"region:us"
]
| null | 2023-08-18T00:08:55Z | ---
pretty_name: Evaluation run of microsoft/DialoGPT-medium
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium)\
\ 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 aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_microsoft__DialoGPT-medium\"\
,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\
\ are the [latest results from run 2023-12-03T18:15:54.629306](https://huggingface.co/datasets/open-llm-leaderboard/details_microsoft__DialoGPT-medium/blob/main/results_2023-12-03T18-15-54.629306.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\": 0.0,\n \"\
acc_stderr\": 0.0\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \
\ \"acc_stderr\": 0.0\n }\n}\n```"
repo_url: https://huggingface.co/microsoft/DialoGPT-medium
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|arc:challenge|25_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_18T05_52_00.103585
path:
- '**/details_harness|drop|3_2023-10-18T05-52-00.103585.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-18T05-52-00.103585.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_18T05_52_00.103585
path:
- '**/details_harness|gsm8k|5_2023-10-18T05-52-00.103585.parquet'
- split: 2023_12_03T18_15_54.629306
path:
- '**/details_harness|gsm8k|5_2023-12-03T18-15-54.629306.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-03T18-15-54.629306.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hellaswag|10_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
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- split: latest
path:
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- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
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path:
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- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
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path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
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path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
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path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
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path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
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path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
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path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
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path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
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path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
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path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
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path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T19:21:27.633576.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T19:21:27.633576.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_18T05_52_00.103585
path:
- '**/details_harness|winogrande|5_2023-10-18T05-52-00.103585.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-18T05-52-00.103585.parquet'
- config_name: results
data_files:
- split: 2023_07_19T19_21_27.633576
path:
- results_2023-07-19T19:21:27.633576.parquet
- split: 2023_10_18T05_52_00.103585
path:
- results_2023-10-18T05-52-00.103585.parquet
- split: 2023_12_03T18_15_54.629306
path:
- results_2023-12-03T18-15-54.629306.parquet
- split: latest
path:
- results_2023-12-03T18-15-54.629306.parquet
---
# Dataset Card for Evaluation run of microsoft/DialoGPT-medium
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/microsoft/DialoGPT-medium
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) 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 aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_microsoft__DialoGPT-medium",
"harness_gsm8k_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-03T18:15:54.629306](https://huggingface.co/datasets/open-llm-leaderboard/details_microsoft__DialoGPT-medium/blob/main/results_2023-12-03T18-15-54.629306.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": 0.0,
"acc_stderr": 0.0
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_lizhuang144__llama_mirror_13b_v1.0 | open-llm-leaderboard | 2023-09-17T10:53:31Z | 339 | 0 | [
"region:us"
]
| null | 2023-08-18T11:48:39Z | ---
pretty_name: Evaluation run of lizhuang144/llama_mirror_13b_v1.0
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [lizhuang144/llama_mirror_13b_v1.0](https://huggingface.co/lizhuang144/llama_mirror_13b_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_lizhuang144__llama_mirror_13b_v1.0\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-17T10:53:19.904763](https://huggingface.co/datasets/open-llm-leaderboard/details_lizhuang144__llama_mirror_13b_v1.0/blob/main/results_2023-09-17T10-53-19.904763.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\": 0.002726510067114094,\n\
\ \"em_stderr\": 0.0005340111700415926,\n \"f1\": 0.06866086409395994,\n\
\ \"f1_stderr\": 0.0014864813602608763,\n \"acc\": 0.42033799014225337,\n\
\ \"acc_stderr\": 0.00955801932501455\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.002726510067114094,\n \"em_stderr\": 0.0005340111700415926,\n\
\ \"f1\": 0.06866086409395994,\n \"f1_stderr\": 0.0014864813602608763\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.07429871114480667,\n \
\ \"acc_stderr\": 0.007223844172845574\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7663772691397001,\n \"acc_stderr\": 0.011892194477183524\n\
\ }\n}\n```"
repo_url: https://huggingface.co/lizhuang144/llama_mirror_13b_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_08_09T16_49_32.921683
path:
- '**/details_harness|arc:challenge|25_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T10_53_19.904763
path:
- '**/details_harness|drop|3_2023-09-17T10-53-19.904763.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T10-53-19.904763.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T10_53_19.904763
path:
- '**/details_harness|gsm8k|5_2023-09-17T10-53-19.904763.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T10-53-19.904763.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hellaswag|10_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
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- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet'
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- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet'
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path:
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- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T16:49:32.921683.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T16:49:32.921683.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T10_53_19.904763
path:
- '**/details_harness|winogrande|5_2023-09-17T10-53-19.904763.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T10-53-19.904763.parquet'
- config_name: results
data_files:
- split: 2023_08_09T16_49_32.921683
path:
- results_2023-08-09T16:49:32.921683.parquet
- split: 2023_09_17T10_53_19.904763
path:
- results_2023-09-17T10-53-19.904763.parquet
- split: latest
path:
- results_2023-09-17T10-53-19.904763.parquet
---
# Dataset Card for Evaluation run of lizhuang144/llama_mirror_13b_v1.0
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/lizhuang144/llama_mirror_13b_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 [lizhuang144/llama_mirror_13b_v1.0](https://huggingface.co/lizhuang144/llama_mirror_13b_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_lizhuang144__llama_mirror_13b_v1.0",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-17T10:53:19.904763](https://huggingface.co/datasets/open-llm-leaderboard/details_lizhuang144__llama_mirror_13b_v1.0/blob/main/results_2023-09-17T10-53-19.904763.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": 0.002726510067114094,
"em_stderr": 0.0005340111700415926,
"f1": 0.06866086409395994,
"f1_stderr": 0.0014864813602608763,
"acc": 0.42033799014225337,
"acc_stderr": 0.00955801932501455
},
"harness|drop|3": {
"em": 0.002726510067114094,
"em_stderr": 0.0005340111700415926,
"f1": 0.06866086409395994,
"f1_stderr": 0.0014864813602608763
},
"harness|gsm8k|5": {
"acc": 0.07429871114480667,
"acc_stderr": 0.007223844172845574
},
"harness|winogrande|5": {
"acc": 0.7663772691397001,
"acc_stderr": 0.011892194477183524
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_Mikivis__xuanxuan | open-llm-leaderboard | 2023-09-16T21:42:12Z | 339 | 0 | [
"region:us"
]
| null | 2023-09-01T13:15:05Z | ---
pretty_name: Evaluation run of Mikivis/xuanxuan
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Mikivis/xuanxuan](https://huggingface.co/Mikivis/xuanxuan) 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_Mikivis__xuanxuan\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-16T21:42:00.993318](https://huggingface.co/datasets/open-llm-leaderboard/details_Mikivis__xuanxuan/blob/main/results_2023-09-16T21-42-00.993318.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\": 0.008389261744966443,\n\
\ \"em_stderr\": 0.000934054321686696,\n \"f1\": 0.05742869127516786,\n\
\ \"f1_stderr\": 0.0015884226243297857,\n \"acc\": 0.2521704814522494,\n\
\ \"acc_stderr\": 0.00702597803203845\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.008389261744966443,\n \"em_stderr\": 0.000934054321686696,\n\
\ \"f1\": 0.05742869127516786,\n \"f1_stderr\": 0.0015884226243297857\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5043409629044988,\n\
\ \"acc_stderr\": 0.0140519560640769\n }\n}\n```"
repo_url: https://huggingface.co/Mikivis/xuanxuan
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_01T13_14_51.241896
path:
- '**/details_harness|arc:challenge|25_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_16T21_42_00.993318
path:
- '**/details_harness|drop|3_2023-09-16T21-42-00.993318.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-16T21-42-00.993318.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_16T21_42_00.993318
path:
- '**/details_harness|gsm8k|5_2023-09-16T21-42-00.993318.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-16T21-42-00.993318.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hellaswag|10_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-01T13:14:51.241896.parquet'
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- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-01T13:14:51.241896.parquet'
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- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-01T13:14:51.241896.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
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path:
- '**/details_harness|truthfulqa:mc|0_2023-09-01T13:14:51.241896.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-01T13:14:51.241896.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_16T21_42_00.993318
path:
- '**/details_harness|winogrande|5_2023-09-16T21-42-00.993318.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-16T21-42-00.993318.parquet'
- config_name: results
data_files:
- split: 2023_09_01T13_14_51.241896
path:
- results_2023-09-01T13:14:51.241896.parquet
- split: 2023_09_16T21_42_00.993318
path:
- results_2023-09-16T21-42-00.993318.parquet
- split: latest
path:
- results_2023-09-16T21-42-00.993318.parquet
---
# Dataset Card for Evaluation run of Mikivis/xuanxuan
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Mikivis/xuanxuan
- **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 [Mikivis/xuanxuan](https://huggingface.co/Mikivis/xuanxuan) 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_Mikivis__xuanxuan",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-16T21:42:00.993318](https://huggingface.co/datasets/open-llm-leaderboard/details_Mikivis__xuanxuan/blob/main/results_2023-09-16T21-42-00.993318.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": 0.008389261744966443,
"em_stderr": 0.000934054321686696,
"f1": 0.05742869127516786,
"f1_stderr": 0.0015884226243297857,
"acc": 0.2521704814522494,
"acc_stderr": 0.00702597803203845
},
"harness|drop|3": {
"em": 0.008389261744966443,
"em_stderr": 0.000934054321686696,
"f1": 0.05742869127516786,
"f1_stderr": 0.0015884226243297857
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
},
"harness|winogrande|5": {
"acc": 0.5043409629044988,
"acc_stderr": 0.0140519560640769
}
}
```
### 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] | [
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|
liveqa | null | 2022-11-03T16:15:28Z | 338 | 1 | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:zh",
"license:unknown",
"region:us"
]
| [
"question-answering"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- found
language_creators:
- found
language:
- zh
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: liveqa
pretty_name: LiveQA
dataset_info:
features:
- name: id
dtype: int64
- name: passages
sequence:
- name: is_question
dtype: bool
- name: text
dtype: string
- name: candidate1
dtype: string
- name: candidate2
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 112187507
num_examples: 1670
download_size: 114704569
dataset_size: 112187507
---
# Dataset Card for LiveQA
## 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/PKU-TANGENT/LiveQA)
- **Repository:** [Github](https://github.com/PKU-TANGENT/LiveQA)
- **Paper:** [Liu et al., 2020](https://www.aclweb.org/anthology/2020.ccl-1.98.pdf)
- **Leaderboard:** N/A
- **Point of Contact:** Qianying Liu
### Dataset Summary
The LiveQA dataset is a Chinese question-answering resource constructed from playby-play live broadcasts. It contains 117k multiple-choice questions written by human commentators for over 1,670 NBA games, which are collected from the Chinese Hupu website.
### Supported Tasks and Leaderboards
Question Answering.
[More Information Needed]
### Languages
Chinese.
## Dataset Structure
### Data Instances
Each instance represents a timeline (i.e., a game) with an identifier. The passages field comprise an array of text or question segments. In the following truncated example, user comments about the game is followed by a question about which team will be the first to reach 60 points.
```python
{
'id': 1,
'passages': [
{
"is_question": False,
"text": "'我希望两位球员都能做到！！",
"candidate1": "",
"candidate2": "",
"answer": "",
},
{
"is_question": False,
"text": "新年给我们送上精彩比赛！",
"candidate1": "",
"candidate2": "",
"answer": "",
},
{
"is_question": True,
"text": "先达到60分？",
"candidate1": "火箭",
"candidate2": "勇士",
"answer": "勇士",
},
{
"is_question": False,
"text": "自己急停跳投！！！",
"candidate1": "",
"candidate2": "",
"answer": "",
}
]
}
```
### Data Fields
- id: identifier for the game
- passages: collection of text/question segments
- text: real-time text comment or binary question related to the context
- candidate1/2: one of the two answer options to the question
- answer: correct answer to the question in text
### Data Splits
There is no predefined split in this dataset.
## 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
This resource is developed by [Liu et al., 2020](https://www.aclweb.org/anthology/2020.ccl-1.98.pdf).
```
@inproceedings{qianying-etal-2020-liveqa,
title = "{L}ive{QA}: A Question Answering Dataset over Sports Live",
author = "Qianying, Liu and
Sicong, Jiang and
Yizhong, Wang and
Sujian, Li",
booktitle = "Proceedings of the 19th Chinese National Conference on Computational Linguistics",
month = oct,
year = "2020",
address = "Haikou, China",
publisher = "Chinese Information Processing Society of China",
url = "https://www.aclweb.org/anthology/2020.ccl-1.98",
pages = "1057--1067"
}
```
### Contributions
Thanks to [@j-chim](https://github.com/j-chim) for adding this dataset. | [
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|
wili_2018 | null | 2023-01-25T15:02:28Z | 338 | 3 | [
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]
| [
"text-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
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language_creators:
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license:
- odbl
multilinguality:
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size_categories:
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source_datasets:
- original
task_categories:
- text-classification
task_ids: []
paperswithcode_id: wili-2018
pretty_name: Wili2018
language_bcp47:
- be-tarask
- map-bms
- nds-nl
- roa-tara
- zh-yue
tags:
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dataset_info:
features:
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dtype: string
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dtype:
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names:
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config_name: WiLI-2018 dataset
splits:
- name: train
num_bytes: 65408201
num_examples: 117500
- name: test
num_bytes: 66491260
num_examples: 117500
download_size: 130516351
dataset_size: 131899461
---
# Dataset Card for wili_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:** https://zenodo.org/record/841984
- **Repository:** [Needs More Information]
- **Paper:** https://arxiv.org/pdf/1801.07779
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** Thoma, Martin (Email: [email protected])
### Dataset Summary
WiLI-2018, the Wikipedia language identification benchmark dataset, contains 235000 paragraphs of 235 languages. The dataset is balanced and a train-test split is provided.
### Supported Tasks and Leaderboards
[Needs More Information]
### Languages
235 Different Languages
## Dataset Structure
### Data Instances
```
{
'label': 207,
'sentence': 'Ti Turkia ket maysa a demokrata, sekular, unitario, batay-linteg a republika nga addaan ti taga-ugma a tinawtawid a kultura. Ti Turkia ket umadadu a naipatipon iti Laud babaen ti panagkameng kadagiti organisasion a kas ti Konsilo iti Europa, NATO, OECD, OSCE ken ti G-20 a dagiti kangrunaan nga ekonomia. Ti Turkia ket nangrugi a nakitulag ti napno a panagkameng iti Kappon ti Europa idi 2005, nga isu ket maysa idin a kumaduaan a kameng iti Europeano a Komunidad ti Ekonomia manipud idi 1963 ken nakadanon ti maysa a tulagan ti kappon ti aduana idi 1995. Ti Turkia ket nagtaraken iti asideg a kultural, politikal, ekonomiko ken industria a panakibiang iti Tengnga a Daya, dagiti Turko nga estado iti Tengnga nga Asia ken dagiti pagilian ti Aprika babaen ti panagkameng kadagiti organisasion a kas ti Turko a Konsilo, Nagsaupan nga Administrasion iti Turko nga Arte ken Kultura, Organisasion iti Islamiko a Panagtitinnulong ken ti Organisasion ti Ekonomiko a Panagtitinnulong.'
}
```
### Data Fields
[Needs More Information]
### Data Splits
175000 lines of text each for train and test data.
## 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
The dataset was initially created by Thomas Martin
### Licensing Information
ODC Open Database License v1.0
### Citation Information
```
@dataset{thoma_martin_2018_841984,
author = {Thoma, Martin},
title = {{WiLI-2018 - Wikipedia Language Identification database}},
month = jan,
year = 2018,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.841984},
url = {https://doi.org/10.5281/zenodo.841984}
}
```
### Contributions
Thanks to [@Shubhambindal2017](https://github.com/Shubhambindal2017) for adding this dataset. | [
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|
inkoziev/jokes_dialogues | inkoziev | 2023-02-19T07:07:16Z | 338 | 2 | [
"task_categories:conversational",
"language:ru",
"license:cc-by-nc-4.0",
"region:us"
]
| [
"conversational"
]
| 2023-02-18T11:59:12Z | ---
license: cc-by-nc-4.0
task_categories:
- conversational
language:
- ru
---
# Диалоги из анекдотов и шуток
Датасет содержит результат парсинга анекдотов, наскрапленных с разных сайтов.
## Формат
Каждый сэмпл содержит четыре поля:
"context" - контекст диалога, включая все недиалоговые вставки. Обратите внимание, что контекст содержит как предшествующие реплики, так и прочий сопутствующий текст, так
как он определяет общий сеттинг, необходимый для генерации реплики. Из реплики удалены маркеры косвенной речи.
"utterance" - диалоговая реплика.
"hash" - хэш-код исходного полного текста для связывания сэмплов.
"reply_num" - порядковый номер диалоговой реплики. Часто последняя реплика является "пайнчалайном", в ней сконцентрирована суть шутки.
Один исходный текст может дать несколько сэмплов, если в нем было много реплик. | [
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|
open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-7B | open-llm-leaderboard | 2023-09-11T14:59:23Z | 338 | 0 | [
"region:us"
]
| null | 2023-09-05T05:01:40Z | ---
pretty_name: Evaluation run of AIDC-ai-business/Marcoroni-7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [AIDC-ai-business/Marcoroni-7B](https://huggingface.co/AIDC-ai-business/Marcoroni-7B)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 61 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 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_AIDC-ai-business__Marcoroni-7B\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-09-11T14:58:05.245524](https://huggingface.co/datasets/open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-7B/blob/main/results_2023-09-11T14-58-05.245524.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\": 0.5159772470651705,\n\
\ \"acc_stderr\": 0.03490050368845693,\n \"acc_norm\": 0.5196198874675843,\n\
\ \"acc_norm_stderr\": 0.03488383911166199,\n \"mc1\": 0.3574051407588739,\n\
\ \"mc1_stderr\": 0.0167765996767294,\n \"mc2\": 0.5084843623108531,\n\
\ \"mc2_stderr\": 0.015788699144390992\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5537542662116041,\n \"acc_stderr\": 0.014526705548539982,\n\
\ \"acc_norm\": 0.5810580204778157,\n \"acc_norm_stderr\": 0.014418106953639013\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6132244572794264,\n\
\ \"acc_stderr\": 0.004860162076330978,\n \"acc_norm\": 0.8008364867556264,\n\
\ \"acc_norm_stderr\": 0.0039855506403304606\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.48148148148148145,\n\
\ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\
\ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.47368421052631576,\n \"acc_stderr\": 0.04063302731486671,\n\
\ \"acc_norm\": 0.47368421052631576,\n \"acc_norm_stderr\": 0.04063302731486671\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.5,\n\
\ \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n \
\ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6,\n \"acc_stderr\": 0.030151134457776285,\n \
\ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.030151134457776285\n \
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5625,\n\
\ \"acc_stderr\": 0.04148415739394154,\n \"acc_norm\": 0.5625,\n \
\ \"acc_norm_stderr\": 0.04148415739394154\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145632,\n \
\ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145632\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\": 0.36,\n\
\ \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4797687861271676,\n\
\ \"acc_stderr\": 0.03809342081273957,\n \"acc_norm\": 0.4797687861271676,\n\
\ \"acc_norm_stderr\": 0.03809342081273957\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.29411764705882354,\n \"acc_stderr\": 0.04533838195929775,\n\
\ \"acc_norm\": 0.29411764705882354,\n \"acc_norm_stderr\": 0.04533838195929775\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.62,\n \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n\
\ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.4851063829787234,\n \"acc_stderr\": 0.032671518489247764,\n\
\ \"acc_norm\": 0.4851063829787234,\n \"acc_norm_stderr\": 0.032671518489247764\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.32456140350877194,\n\
\ \"acc_stderr\": 0.044045561573747664,\n \"acc_norm\": 0.32456140350877194,\n\
\ \"acc_norm_stderr\": 0.044045561573747664\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.45517241379310347,\n \"acc_stderr\": 0.04149886942192117,\n\
\ \"acc_norm\": 0.45517241379310347,\n \"acc_norm_stderr\": 0.04149886942192117\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.30952380952380953,\n \"acc_stderr\": 0.023809523809523867,\n \"\
acc_norm\": 0.30952380952380953,\n \"acc_norm_stderr\": 0.023809523809523867\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2777777777777778,\n\
\ \"acc_stderr\": 0.040061680838488774,\n \"acc_norm\": 0.2777777777777778,\n\
\ \"acc_norm_stderr\": 0.040061680838488774\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.5612903225806452,\n\
\ \"acc_stderr\": 0.028229497320317216,\n \"acc_norm\": 0.5612903225806452,\n\
\ \"acc_norm_stderr\": 0.028229497320317216\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.3842364532019704,\n \"acc_stderr\": 0.0342239856565755,\n\
\ \"acc_norm\": 0.3842364532019704,\n \"acc_norm_stderr\": 0.0342239856565755\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\
: 0.41,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7090909090909091,\n \"acc_stderr\": 0.03546563019624336,\n\
\ \"acc_norm\": 0.7090909090909091,\n \"acc_norm_stderr\": 0.03546563019624336\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.6818181818181818,\n \"acc_stderr\": 0.0331847733384533,\n \"acc_norm\"\
: 0.6818181818181818,\n \"acc_norm_stderr\": 0.0331847733384533\n },\n\
\ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \
\ \"acc\": 0.7512953367875648,\n \"acc_stderr\": 0.031195840877700286,\n\
\ \"acc_norm\": 0.7512953367875648,\n \"acc_norm_stderr\": 0.031195840877700286\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.48205128205128206,\n \"acc_stderr\": 0.02533466708095495,\n\
\ \"acc_norm\": 0.48205128205128206,\n \"acc_norm_stderr\": 0.02533466708095495\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2518518518518518,\n \"acc_stderr\": 0.02646611753895991,\n \
\ \"acc_norm\": 0.2518518518518518,\n \"acc_norm_stderr\": 0.02646611753895991\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.5126050420168067,\n \"acc_stderr\": 0.03246816765752174,\n \
\ \"acc_norm\": 0.5126050420168067,\n \"acc_norm_stderr\": 0.03246816765752174\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"\
acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.7192660550458716,\n \"acc_stderr\": 0.019266055045871623,\n \"\
acc_norm\": 0.7192660550458716,\n \"acc_norm_stderr\": 0.019266055045871623\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.375,\n \"acc_stderr\": 0.033016908987210894,\n \"acc_norm\": 0.375,\n\
\ \"acc_norm_stderr\": 0.033016908987210894\n },\n \"harness|hendrycksTest-high_school_us_history|5\"\
: {\n \"acc\": 0.696078431372549,\n \"acc_stderr\": 0.03228210387037892,\n\
\ \"acc_norm\": 0.696078431372549,\n \"acc_norm_stderr\": 0.03228210387037892\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7215189873417721,\n \"acc_stderr\": 0.029178682304842548,\n \
\ \"acc_norm\": 0.7215189873417721,\n \"acc_norm_stderr\": 0.029178682304842548\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5964125560538116,\n\
\ \"acc_stderr\": 0.03292802819330314,\n \"acc_norm\": 0.5964125560538116,\n\
\ \"acc_norm_stderr\": 0.03292802819330314\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.5954198473282443,\n \"acc_stderr\": 0.043046937953806645,\n\
\ \"acc_norm\": 0.5954198473282443,\n \"acc_norm_stderr\": 0.043046937953806645\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6446280991735537,\n \"acc_stderr\": 0.0436923632657398,\n \"acc_norm\"\
: 0.6446280991735537,\n \"acc_norm_stderr\": 0.0436923632657398\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6481481481481481,\n\
\ \"acc_stderr\": 0.046166311118017125,\n \"acc_norm\": 0.6481481481481481,\n\
\ \"acc_norm_stderr\": 0.046166311118017125\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.5705521472392638,\n \"acc_stderr\": 0.03889066619112723,\n\
\ \"acc_norm\": 0.5705521472392638,\n \"acc_norm_stderr\": 0.03889066619112723\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.375,\n\
\ \"acc_stderr\": 0.04595091388086298,\n \"acc_norm\": 0.375,\n \
\ \"acc_norm_stderr\": 0.04595091388086298\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7087378640776699,\n \"acc_stderr\": 0.04498676320572924,\n\
\ \"acc_norm\": 0.7087378640776699,\n \"acc_norm_stderr\": 0.04498676320572924\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7777777777777778,\n\
\ \"acc_stderr\": 0.027236013946196704,\n \"acc_norm\": 0.7777777777777778,\n\
\ \"acc_norm_stderr\": 0.027236013946196704\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\
: 0.55,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-miscellaneous|5\"\
: {\n \"acc\": 0.7100893997445722,\n \"acc_stderr\": 0.01622501794477098,\n\
\ \"acc_norm\": 0.7100893997445722,\n \"acc_norm_stderr\": 0.01622501794477098\n\
\ },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.5809248554913294,\n\
\ \"acc_stderr\": 0.02656417811142262,\n \"acc_norm\": 0.5809248554913294,\n\
\ \"acc_norm_stderr\": 0.02656417811142262\n },\n \"harness|hendrycksTest-moral_scenarios|5\"\
: {\n \"acc\": 0.264804469273743,\n \"acc_stderr\": 0.014756906483260664,\n\
\ \"acc_norm\": 0.264804469273743,\n \"acc_norm_stderr\": 0.014756906483260664\n\
\ },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.5261437908496732,\n\
\ \"acc_stderr\": 0.028590752958852394,\n \"acc_norm\": 0.5261437908496732,\n\
\ \"acc_norm_stderr\": 0.028590752958852394\n },\n \"harness|hendrycksTest-philosophy|5\"\
: {\n \"acc\": 0.5884244372990354,\n \"acc_stderr\": 0.027950481494401266,\n\
\ \"acc_norm\": 0.5884244372990354,\n \"acc_norm_stderr\": 0.027950481494401266\n\
\ },\n \"harness|hendrycksTest-prehistory|5\": {\n \"acc\": 0.5648148148148148,\n\
\ \"acc_stderr\": 0.027586006221607708,\n \"acc_norm\": 0.5648148148148148,\n\
\ \"acc_norm_stderr\": 0.027586006221607708\n },\n \"harness|hendrycksTest-professional_accounting|5\"\
: {\n \"acc\": 0.375886524822695,\n \"acc_stderr\": 0.028893955412115882,\n\
\ \"acc_norm\": 0.375886524822695,\n \"acc_norm_stderr\": 0.028893955412115882\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.38396349413298564,\n\
\ \"acc_stderr\": 0.01242158783313423,\n \"acc_norm\": 0.38396349413298564,\n\
\ \"acc_norm_stderr\": 0.01242158783313423\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.4889705882352941,\n \"acc_stderr\": 0.03036544647727568,\n\
\ \"acc_norm\": 0.4889705882352941,\n \"acc_norm_stderr\": 0.03036544647727568\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.4869281045751634,\n \"acc_stderr\": 0.020220920829626912,\n \
\ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.020220920829626912\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5909090909090909,\n\
\ \"acc_stderr\": 0.04709306978661896,\n \"acc_norm\": 0.5909090909090909,\n\
\ \"acc_norm_stderr\": 0.04709306978661896\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.6122448979591837,\n \"acc_stderr\": 0.031192230726795656,\n\
\ \"acc_norm\": 0.6122448979591837,\n \"acc_norm_stderr\": 0.031192230726795656\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6119402985074627,\n\
\ \"acc_stderr\": 0.034457899643627506,\n \"acc_norm\": 0.6119402985074627,\n\
\ \"acc_norm_stderr\": 0.034457899643627506\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.77,\n \"acc_stderr\": 0.042295258468165065,\n \
\ \"acc_norm\": 0.77,\n \"acc_norm_stderr\": 0.042295258468165065\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.40963855421686746,\n\
\ \"acc_stderr\": 0.03828401115079022,\n \"acc_norm\": 0.40963855421686746,\n\
\ \"acc_norm_stderr\": 0.03828401115079022\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.695906432748538,\n \"acc_stderr\": 0.03528211258245229,\n\
\ \"acc_norm\": 0.695906432748538,\n \"acc_norm_stderr\": 0.03528211258245229\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3574051407588739,\n\
\ \"mc1_stderr\": 0.0167765996767294,\n \"mc2\": 0.5084843623108531,\n\
\ \"mc2_stderr\": 0.015788699144390992\n }\n}\n```"
repo_url: https://huggingface.co/AIDC-ai-business/Marcoroni-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_09_05T05_01_15.449449
path:
- '**/details_harness|arc:challenge|25_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|arc:challenge|25_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hellaswag|10_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hellaswag|10_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-05T05:01:15.449449.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T14-58-05.245524.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T14-58-05.245524.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-05T05:01:15.449449.parquet'
- split: 2023_09_11T14_58_05.245524
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-11T14-58-05.245524.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-11T14-58-05.245524.parquet'
- config_name: results
data_files:
- split: 2023_09_05T05_01_15.449449
path:
- results_2023-09-05T05:01:15.449449.parquet
- split: 2023_09_11T14_58_05.245524
path:
- results_2023-09-11T14-58-05.245524.parquet
- split: latest
path:
- results_2023-09-11T14-58-05.245524.parquet
---
# Dataset Card for Evaluation run of AIDC-ai-business/Marcoroni-7B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/AIDC-ai-business/Marcoroni-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 [AIDC-ai-business/Marcoroni-7B](https://huggingface.co/AIDC-ai-business/Marcoroni-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 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_AIDC-ai-business__Marcoroni-7B",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-11T14:58:05.245524](https://huggingface.co/datasets/open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-7B/blob/main/results_2023-09-11T14-58-05.245524.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": 0.5159772470651705,
"acc_stderr": 0.03490050368845693,
"acc_norm": 0.5196198874675843,
"acc_norm_stderr": 0.03488383911166199,
"mc1": 0.3574051407588739,
"mc1_stderr": 0.0167765996767294,
"mc2": 0.5084843623108531,
"mc2_stderr": 0.015788699144390992
},
"harness|arc:challenge|25": {
"acc": 0.5537542662116041,
"acc_stderr": 0.014526705548539982,
"acc_norm": 0.5810580204778157,
"acc_norm_stderr": 0.014418106953639013
},
"harness|hellaswag|10": {
"acc": 0.6132244572794264,
"acc_stderr": 0.004860162076330978,
"acc_norm": 0.8008364867556264,
"acc_norm_stderr": 0.0039855506403304606
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.28,
"acc_stderr": 0.04512608598542128,
"acc_norm": 0.28,
"acc_norm_stderr": 0.04512608598542128
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.48148148148148145,
"acc_stderr": 0.043163785995113245,
"acc_norm": 0.48148148148148145,
"acc_norm_stderr": 0.043163785995113245
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.47368421052631576,
"acc_stderr": 0.04063302731486671,
"acc_norm": 0.47368421052631576,
"acc_norm_stderr": 0.04063302731486671
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.5,
"acc_stderr": 0.050251890762960605,
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6,
"acc_stderr": 0.030151134457776285,
"acc_norm": 0.6,
"acc_norm_stderr": 0.030151134457776285
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.5625,
"acc_stderr": 0.04148415739394154,
"acc_norm": 0.5625,
"acc_norm_stderr": 0.04148415739394154
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.38,
"acc_stderr": 0.04878317312145632,
"acc_norm": 0.38,
"acc_norm_stderr": 0.04878317312145632
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.36,
"acc_stderr": 0.048241815132442176,
"acc_norm": 0.36,
"acc_norm_stderr": 0.048241815132442176
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.28,
"acc_stderr": 0.04512608598542128,
"acc_norm": 0.28,
"acc_norm_stderr": 0.04512608598542128
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.4797687861271676,
"acc_stderr": 0.03809342081273957,
"acc_norm": 0.4797687861271676,
"acc_norm_stderr": 0.03809342081273957
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.29411764705882354,
"acc_stderr": 0.04533838195929775,
"acc_norm": 0.29411764705882354,
"acc_norm_stderr": 0.04533838195929775
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.62,
"acc_stderr": 0.048783173121456316,
"acc_norm": 0.62,
"acc_norm_stderr": 0.048783173121456316
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.4851063829787234,
"acc_stderr": 0.032671518489247764,
"acc_norm": 0.4851063829787234,
"acc_norm_stderr": 0.032671518489247764
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.32456140350877194,
"acc_stderr": 0.044045561573747664,
"acc_norm": 0.32456140350877194,
"acc_norm_stderr": 0.044045561573747664
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.45517241379310347,
"acc_stderr": 0.04149886942192117,
"acc_norm": 0.45517241379310347,
"acc_norm_stderr": 0.04149886942192117
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.30952380952380953,
"acc_stderr": 0.023809523809523867,
"acc_norm": 0.30952380952380953,
"acc_norm_stderr": 0.023809523809523867
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.2777777777777778,
"acc_stderr": 0.040061680838488774,
"acc_norm": 0.2777777777777778,
"acc_norm_stderr": 0.040061680838488774
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.37,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.37,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-high_school_biology|5": {
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```
### 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] | [
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|
open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-13B | open-llm-leaderboard | 2023-09-18T15:06:37Z | 338 | 0 | [
"region:us"
]
| null | 2023-09-11T15:45:45Z | ---
pretty_name: Evaluation run of AIDC-ai-business/Marcoroni-13B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [AIDC-ai-business/Marcoroni-13B](https://huggingface.co/AIDC-ai-business/Marcoroni-13B)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 61 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-13B\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-09-18T15:05:14.072037](https://huggingface.co/datasets/open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-13B/blob/main/results_2023-09-18T15-05-14.072037.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\": 0.5968939242056442,\n\
\ \"acc_stderr\": 0.03397009205870784,\n \"acc_norm\": 0.6007957237246586,\n\
\ \"acc_norm_stderr\": 0.033948145854358645,\n \"mc1\": 0.4186046511627907,\n\
\ \"mc1_stderr\": 0.017270015284476855,\n \"mc2\": 0.5769635027861147,\n\
\ \"mc2_stderr\": 0.015727623906231773\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.590443686006826,\n \"acc_stderr\": 0.014370358632472447,\n\
\ \"acc_norm\": 0.6245733788395904,\n \"acc_norm_stderr\": 0.014150631435111726\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6366261700856403,\n\
\ \"acc_stderr\": 0.004799882248494813,\n \"acc_norm\": 0.8327026488747261,\n\
\ \"acc_norm_stderr\": 0.003724783389253322\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \
\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5407407407407407,\n\
\ \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.5407407407407407,\n\
\ \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.5921052631578947,\n \"acc_stderr\": 0.039993097127774734,\n\
\ \"acc_norm\": 0.5921052631578947,\n \"acc_norm_stderr\": 0.039993097127774734\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\
\ \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n \
\ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.5962264150943396,\n \"acc_stderr\": 0.030197611600197946,\n\
\ \"acc_norm\": 0.5962264150943396,\n \"acc_norm_stderr\": 0.030197611600197946\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6597222222222222,\n\
\ \"acc_stderr\": 0.039621355734862175,\n \"acc_norm\": 0.6597222222222222,\n\
\ \"acc_norm_stderr\": 0.039621355734862175\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n\
\ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6011560693641619,\n\
\ \"acc_stderr\": 0.037336266553835096,\n \"acc_norm\": 0.6011560693641619,\n\
\ \"acc_norm_stderr\": 0.037336266553835096\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.3235294117647059,\n \"acc_stderr\": 0.04655010411319616,\n\
\ \"acc_norm\": 0.3235294117647059,\n \"acc_norm_stderr\": 0.04655010411319616\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.71,\n \"acc_stderr\": 0.04560480215720685,\n \"acc_norm\": 0.71,\n\
\ \"acc_norm_stderr\": 0.04560480215720685\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5148936170212766,\n \"acc_stderr\": 0.03267151848924777,\n\
\ \"acc_norm\": 0.5148936170212766,\n \"acc_norm_stderr\": 0.03267151848924777\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.39473684210526316,\n\
\ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.39473684210526316,\n\
\ \"acc_norm_stderr\": 0.045981880578165414\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\
\ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.36243386243386244,\n \"acc_stderr\": 0.02475747390275206,\n \"\
acc_norm\": 0.36243386243386244,\n \"acc_norm_stderr\": 0.02475747390275206\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.38095238095238093,\n\
\ \"acc_stderr\": 0.043435254289490965,\n \"acc_norm\": 0.38095238095238093,\n\
\ \"acc_norm_stderr\": 0.043435254289490965\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \
\ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.6580645161290323,\n \"acc_stderr\": 0.026985289576552742,\n \"\
acc_norm\": 0.6580645161290323,\n \"acc_norm_stderr\": 0.026985289576552742\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.458128078817734,\n \"acc_stderr\": 0.03505630140785741,\n \"acc_norm\"\
: 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785741\n },\n\
\ \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\"\
: 0.59,\n \"acc_stderr\": 0.04943110704237101,\n \"acc_norm\": 0.59,\n\
\ \"acc_norm_stderr\": 0.04943110704237101\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7151515151515152,\n \"acc_stderr\": 0.035243908445117815,\n\
\ \"acc_norm\": 0.7151515151515152,\n \"acc_norm_stderr\": 0.035243908445117815\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7727272727272727,\n \"acc_stderr\": 0.029857515673386417,\n \"\
acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.029857515673386417\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015178,\n\
\ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015178\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6076923076923076,\n \"acc_stderr\": 0.02475600038213095,\n \
\ \"acc_norm\": 0.6076923076923076,\n \"acc_norm_stderr\": 0.02475600038213095\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473072,\n \
\ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473072\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.5966386554621849,\n \"acc_stderr\": 0.031866081214088314,\n\
\ \"acc_norm\": 0.5966386554621849,\n \"acc_norm_stderr\": 0.031866081214088314\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"\
acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.7908256880733945,\n \"acc_stderr\": 0.01743793717334323,\n \"\
acc_norm\": 0.7908256880733945,\n \"acc_norm_stderr\": 0.01743793717334323\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.4212962962962963,\n \"acc_stderr\": 0.03367462138896079,\n \"\
acc_norm\": 0.4212962962962963,\n \"acc_norm_stderr\": 0.03367462138896079\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8431372549019608,\n \"acc_stderr\": 0.02552472232455333,\n \"\
acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.02552472232455333\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7468354430379747,\n \"acc_stderr\": 0.0283046579430353,\n \
\ \"acc_norm\": 0.7468354430379747,\n \"acc_norm_stderr\": 0.0283046579430353\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\
\ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\
\ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.6946564885496184,\n \"acc_stderr\": 0.040393149787245605,\n\
\ \"acc_norm\": 0.6946564885496184,\n \"acc_norm_stderr\": 0.040393149787245605\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7355371900826446,\n \"acc_stderr\": 0.040261875275912073,\n \"\
acc_norm\": 0.7355371900826446,\n \"acc_norm_stderr\": 0.040261875275912073\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\
\ \"acc_stderr\": 0.03826076324884865,\n \"acc_norm\": 0.8055555555555556,\n\
\ \"acc_norm_stderr\": 0.03826076324884865\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.6932515337423313,\n \"acc_stderr\": 0.036230899157241474,\n\
\ \"acc_norm\": 0.6932515337423313,\n \"acc_norm_stderr\": 0.036230899157241474\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4017857142857143,\n\
\ \"acc_stderr\": 0.04653333146973646,\n \"acc_norm\": 0.4017857142857143,\n\
\ \"acc_norm_stderr\": 0.04653333146973646\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.04354631077260595,\n\
\ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.04354631077260595\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8205128205128205,\n\
\ \"acc_stderr\": 0.025140935950335445,\n \"acc_norm\": 0.8205128205128205,\n\
\ \"acc_norm_stderr\": 0.025140935950335445\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.7994891443167306,\n\
\ \"acc_stderr\": 0.014317653708594207,\n \"acc_norm\": 0.7994891443167306,\n\
\ \"acc_norm_stderr\": 0.014317653708594207\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.6705202312138728,\n \"acc_stderr\": 0.025305258131879716,\n\
\ \"acc_norm\": 0.6705202312138728,\n \"acc_norm_stderr\": 0.025305258131879716\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.47262569832402235,\n\
\ \"acc_stderr\": 0.016697420650642752,\n \"acc_norm\": 0.47262569832402235,\n\
\ \"acc_norm_stderr\": 0.016697420650642752\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.6633986928104575,\n \"acc_stderr\": 0.027057974624494382,\n\
\ \"acc_norm\": 0.6633986928104575,\n \"acc_norm_stderr\": 0.027057974624494382\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6752411575562701,\n\
\ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\
\ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7098765432098766,\n \"acc_stderr\": 0.025251173936495026,\n\
\ \"acc_norm\": 0.7098765432098766,\n \"acc_norm_stderr\": 0.025251173936495026\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.475177304964539,\n \"acc_stderr\": 0.02979071924382972,\n \
\ \"acc_norm\": 0.475177304964539,\n \"acc_norm_stderr\": 0.02979071924382972\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.45241199478487615,\n\
\ \"acc_stderr\": 0.012712265105889136,\n \"acc_norm\": 0.45241199478487615,\n\
\ \"acc_norm_stderr\": 0.012712265105889136\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.5882352941176471,\n \"acc_stderr\": 0.029896163033125468,\n\
\ \"acc_norm\": 0.5882352941176471,\n \"acc_norm_stderr\": 0.029896163033125468\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.5866013071895425,\n \"acc_stderr\": 0.019922115682786685,\n \
\ \"acc_norm\": 0.5866013071895425,\n \"acc_norm_stderr\": 0.019922115682786685\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\
\ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\
\ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.6816326530612244,\n \"acc_stderr\": 0.029822533793982055,\n\
\ \"acc_norm\": 0.6816326530612244,\n \"acc_norm_stderr\": 0.029822533793982055\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7562189054726368,\n\
\ \"acc_stderr\": 0.030360490154014645,\n \"acc_norm\": 0.7562189054726368,\n\
\ \"acc_norm_stderr\": 0.030360490154014645\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.4939759036144578,\n\
\ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.4939759036144578,\n\
\ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8070175438596491,\n \"acc_stderr\": 0.030267457554898458,\n\
\ \"acc_norm\": 0.8070175438596491,\n \"acc_norm_stderr\": 0.030267457554898458\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4186046511627907,\n\
\ \"mc1_stderr\": 0.017270015284476855,\n \"mc2\": 0.5769635027861147,\n\
\ \"mc2_stderr\": 0.015727623906231773\n }\n}\n```"
repo_url: https://huggingface.co/AIDC-ai-business/Marcoroni-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_09_11T15_45_30.030837
path:
- '**/details_harness|arc:challenge|25_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|arc:challenge|25_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hellaswag|10_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hellaswag|10_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T15-45-30.030837.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T15-05-14.072037.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-18T15-05-14.072037.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-11T15-45-30.030837.parquet'
- split: 2023_09_18T15_05_14.072037
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-18T15-05-14.072037.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-18T15-05-14.072037.parquet'
- config_name: results
data_files:
- split: 2023_09_11T15_45_30.030837
path:
- results_2023-09-11T15-45-30.030837.parquet
- split: 2023_09_18T15_05_14.072037
path:
- results_2023-09-18T15-05-14.072037.parquet
- split: latest
path:
- results_2023-09-18T15-05-14.072037.parquet
---
# Dataset Card for Evaluation run of AIDC-ai-business/Marcoroni-13B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/AIDC-ai-business/Marcoroni-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 [AIDC-ai-business/Marcoroni-13B](https://huggingface.co/AIDC-ai-business/Marcoroni-13B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-13B",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-18T15:05:14.072037](https://huggingface.co/datasets/open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-13B/blob/main/results_2023-09-18T15-05-14.072037.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
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},
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}
```
### 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] | [
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|
kejian/ACL-ARC | kejian | 2023-11-02T04:51:48Z | 338 | 0 | [
"region:us"
]
| null | 2023-11-02T04:51:45Z | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: text
dtype: string
- name: citing_paper_id
dtype: string
- name: cited_paper_id
dtype: string
- name: citing_paper_year
dtype: int64
- name: cited_paper_year
dtype: int64
- name: citing_paper_title
dtype: string
- name: cited_paper_title
dtype: string
- name: cited_author_ids
sequence: string
- name: citing_author_ids
dtype: 'null'
- name: extended_context
dtype: string
- name: section_number
dtype: int64
- name: section_title
dtype: 'null'
- name: intent
dtype: string
- name: cite_marker_offset
sequence: int64
- name: sents_before
list:
list:
- name: index
dtype: int64
- name: word
dtype: string
- name: lemma
dtype: string
- name: after
dtype: string
- name: pos
dtype: string
- name: characterOffsetEnd
dtype: int64
- name: segment_span
sequence: int64
- name: characterOffsetBegin
dtype: int64
- name: originalText
dtype: string
- name: ArgType
dtype: string
- name: before
dtype: string
- name: is_root
dtype: bool
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dtype: string
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num_bytes: 32094179
num_examples: 1688
- name: test
num_bytes: 2705971
num_examples: 139
- name: validation
num_bytes: 2095387
num_examples: 114
download_size: 6517047
dataset_size: 36895537
---
# Dataset Card for "ACL-ARC"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
great_code | null | 2022-11-18T20:05:00Z | 337 | 1 | [
"task_categories:table-to-text",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-sa-3.0",
"region:us"
]
| [
"table-to-text"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
paperswithcode_id: null
pretty_name: GREAT
dataset_info:
features:
- name: id
dtype: int32
- name: source_tokens
sequence: string
- name: has_bug
dtype: bool
- name: error_location
dtype: int32
- name: repair_candidates
sequence: string
- name: bug_kind
dtype: int32
- name: bug_kind_name
dtype: string
- name: repair_targets
sequence: int32
- name: edges
list:
list:
- name: before_index
dtype: int32
- name: after_index
dtype: int32
- name: edge_type
dtype: int32
- name: edge_type_name
dtype: string
- name: provenances
list:
- name: datasetProvenance
struct:
- name: datasetName
dtype: string
- name: filepath
dtype: string
- name: license
dtype: string
- name: note
dtype: string
splits:
- name: train
num_bytes: 14705534822
num_examples: 1798742
- name: validation
num_bytes: 1502956919
num_examples: 185656
- name: test
num_bytes: 7880762248
num_examples: 968592
download_size: 23310374002
dataset_size: 24089253989
---
# Dataset Card for GREAT
## 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:** None
- **Repository:** https://github.com/google-research-datasets/great
- **Paper:** https://openreview.net/forum?id=B1lnbRNtwr
- **Leaderboard:** [More Information Needed]
- **Point of Contact:** [More Information Needed]
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
Here are some examples of questions and facts:
### 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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|
ybelkada/english_quotes_copy | ybelkada | 2023-04-04T06:13:26Z | 337 | 0 | [
"region:us"
]
| null | 2023-04-04T06:13:24Z | ---
dataset_info:
features:
- name: quote
dtype: string
- name: author
dtype: string
- name: tags
sequence: string
splits:
- name: train
num_bytes: 598359
num_examples: 2508
download_size: 349107
dataset_size: 598359
---
# Dataset Card for "english_quotes_copy"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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|
open-llm-leaderboard/details_LTC-AI-Labs__Guanaco-Vicuna-7B-L2 | open-llm-leaderboard | 2023-10-29T06:29:17Z | 337 | 0 | [
"region:us"
]
| null | 2023-10-01T13:18:33Z | ---
pretty_name: Evaluation run of LTC-AI-Labs/Guanaco-Vicuna-7B-L2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [LTC-AI-Labs/Guanaco-Vicuna-7B-L2](https://huggingface.co/LTC-AI-Labs/Guanaco-Vicuna-7B-L2)\
\ 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_LTC-AI-Labs__Guanaco-Vicuna-7B-L2\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-29T06:29:02.987953](https://huggingface.co/datasets/open-llm-leaderboard/details_LTC-AI-Labs__Guanaco-Vicuna-7B-L2/blob/main/results_2023-10-29T06-29-02.987953.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\": 0.0014681208053691276,\n\
\ \"em_stderr\": 0.00039210421902985767,\n \"f1\": 0.056828859060402796,\n\
\ \"f1_stderr\": 0.0013179206618636607,\n \"acc\": 0.416677387679193,\n\
\ \"acc_stderr\": 0.0097821448230569\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0014681208053691276,\n \"em_stderr\": 0.00039210421902985767,\n\
\ \"f1\": 0.056828859060402796,\n \"f1_stderr\": 0.0013179206618636607\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.07960576194086429,\n \
\ \"acc_stderr\": 0.007455924338676278\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7537490134175217,\n \"acc_stderr\": 0.012108365307437523\n\
\ }\n}\n```"
repo_url: https://huggingface.co/LTC-AI-Labs/Guanaco-Vicuna-7B-L2
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_18_10.170951
path:
- '**/details_harness|arc:challenge|25_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_29T06_29_02.987953
path:
- '**/details_harness|drop|3_2023-10-29T06-29-02.987953.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-29T06-29-02.987953.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_29T06_29_02.987953
path:
- '**/details_harness|gsm8k|5_2023-10-29T06-29-02.987953.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-29T06-29-02.987953.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hellaswag|10_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-10-01T13-18-10.170951.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-01T13-18-10.170951.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-10-01T13-18-10.170951.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_29T06_29_02.987953
path:
- '**/details_harness|winogrande|5_2023-10-29T06-29-02.987953.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-29T06-29-02.987953.parquet'
- config_name: results
data_files:
- split: 2023_10_01T13_18_10.170951
path:
- results_2023-10-01T13-18-10.170951.parquet
- split: 2023_10_29T06_29_02.987953
path:
- results_2023-10-29T06-29-02.987953.parquet
- split: latest
path:
- results_2023-10-29T06-29-02.987953.parquet
---
# Dataset Card for Evaluation run of LTC-AI-Labs/Guanaco-Vicuna-7B-L2
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/LTC-AI-Labs/Guanaco-Vicuna-7B-L2
- **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 [LTC-AI-Labs/Guanaco-Vicuna-7B-L2](https://huggingface.co/LTC-AI-Labs/Guanaco-Vicuna-7B-L2) 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_LTC-AI-Labs__Guanaco-Vicuna-7B-L2",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-29T06:29:02.987953](https://huggingface.co/datasets/open-llm-leaderboard/details_LTC-AI-Labs__Guanaco-Vicuna-7B-L2/blob/main/results_2023-10-29T06-29-02.987953.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": 0.0014681208053691276,
"em_stderr": 0.00039210421902985767,
"f1": 0.056828859060402796,
"f1_stderr": 0.0013179206618636607,
"acc": 0.416677387679193,
"acc_stderr": 0.0097821448230569
},
"harness|drop|3": {
"em": 0.0014681208053691276,
"em_stderr": 0.00039210421902985767,
"f1": 0.056828859060402796,
"f1_stderr": 0.0013179206618636607
},
"harness|gsm8k|5": {
"acc": 0.07960576194086429,
"acc_stderr": 0.007455924338676278
},
"harness|winogrande|5": {
"acc": 0.7537490134175217,
"acc_stderr": 0.012108365307437523
}
}
```
### 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] | [
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|
gap | null | 2023-04-05T10:06:30Z | 336 | 2 | [
"task_categories:token-classification",
"task_ids:coreference-resolution",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"arxiv:1810.05201",
"region:us"
]
| [
"token-classification"
]
| 2022-03-02T23:29:22Z | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- unknown
multilinguality:
- monolingual
pretty_name: GAP Benchmark Suite
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- coreference-resolution
paperswithcode_id: gap
dataset_info:
features:
- name: ID
dtype: string
- name: Text
dtype: string
- name: Pronoun
dtype: string
- name: Pronoun-offset
dtype: int32
- name: A
dtype: string
- name: A-offset
dtype: int32
- name: A-coref
dtype: bool
- name: B
dtype: string
- name: B-offset
dtype: int32
- name: B-coref
dtype: bool
- name: URL
dtype: string
splits:
- name: train
num_bytes: 1095623
num_examples: 2000
- name: validation
num_bytes: 248329
num_examples: 454
- name: test
num_bytes: 1090462
num_examples: 2000
download_size: 2401971
dataset_size: 2434414
---
# Dataset Card for "gap"
## 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/google-research-datasets/gap-coreference](https://github.com/google-research-datasets/gap-coreference)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns](https://arxiv.org/abs/1810.05201)
- **Point of Contact:** [[email protected]](mailto:[email protected])
- **Size of downloaded dataset files:** 2.40 MB
- **Size of the generated dataset:** 2.43 MB
- **Total amount of disk used:** 4.83 MB
### Dataset Summary
GAP is a gender-balanced dataset containing 8,908 coreference-labeled pairs of
(ambiguous pronoun, antecedent name), sampled from Wikipedia and released by
Google AI Language for the evaluation of coreference resolution in practical
applications.
### 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
#### default
- **Size of downloaded dataset files:** 2.40 MB
- **Size of the generated dataset:** 2.43 MB
- **Total amount of disk used:** 4.83 MB
An example of 'validation' looks as follows.
```
{
"A": "aliquam ultrices sagittis",
"A-coref": false,
"A-offset": 208,
"B": "elementum curabitur vitae",
"B-coref": false,
"B-offset": 435,
"ID": "validation-1",
"Pronoun": "condimentum mattis pellentesque",
"Pronoun-offset": 948,
"Text": "Lorem ipsum dolor",
"URL": "sem fringilla ut"
}
```
### Data Fields
The data fields are the same among all splits.
#### default
- `ID`: a `string` feature.
- `Text`: a `string` feature.
- `Pronoun`: a `string` feature.
- `Pronoun-offset`: a `int32` feature.
- `A`: a `string` feature.
- `A-offset`: a `int32` feature.
- `A-coref`: a `bool` feature.
- `B`: a `string` feature.
- `B-offset`: a `int32` feature.
- `B-coref`: a `bool` feature.
- `URL`: a `string` feature.
### Data Splits
| name |train|validation|test|
|-------|----:|---------:|---:|
|default| 2000| 454|2000|
## 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
```
@article{webster-etal-2018-mind,
title = "Mind the {GAP}: A Balanced Corpus of Gendered Ambiguous Pronouns",
author = "Webster, Kellie and
Recasens, Marta and
Axelrod, Vera and
Baldridge, Jason",
journal = "Transactions of the Association for Computational Linguistics",
volume = "6",
year = "2018",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/Q18-1042",
doi = "10.1162/tacl_a_00240",
pages = "605--617",
}
```
### Contributions
Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten), [@otakumesi](https://github.com/otakumesi), [@lewtun](https://github.com/lewtun) for adding this dataset. | [
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|
lucadiliello/wikiqa | lucadiliello | 2022-12-05T15:09:31Z | 336 | 0 | [
"region:us"
]
| null | 2022-12-05T15:06:32Z | ---
dataset_info:
features:
- name: label
dtype: int64
- name: answer
dtype: string
- name: key
dtype: int64
- name: question
dtype: string
splits:
- name: test_clean
num_bytes: 449691
num_examples: 2341
- name: dev_clean
num_bytes: 214886
num_examples: 1126
- name: train
num_bytes: 4017460
num_examples: 20360
- name: test
num_bytes: 1208042
num_examples: 6165
- name: dev
num_bytes: 530358
num_examples: 2733
download_size: 3111254
dataset_size: 6420437
---
# Dataset Card for "wikiqa"
WikiQA dataset for Answer Sentence Selection. The dataset contains 2 additional splits which are `clean` versions of the original development and test sets. `clean` versions contain only questions which have at least a positive and a negative answer candidate. | [
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|
open-llm-leaderboard/details_bigcode__tiny_starcoder_py | open-llm-leaderboard | 2023-09-17T18:41:39Z | 336 | 0 | [
"region:us"
]
| null | 2023-08-17T23:54:15Z | ---
pretty_name: Evaluation run of bigcode/tiny_starcoder_py
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [bigcode/tiny_starcoder_py](https://huggingface.co/bigcode/tiny_starcoder_py)\
\ 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_bigcode__tiny_starcoder_py\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-17T18:41:27.030233](https://huggingface.co/datasets/open-llm-leaderboard/details_bigcode__tiny_starcoder_py/blob/main/results_2023-09-17T18-41-27.030233.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0007340604026845638,\n\
\ \"em_stderr\": 0.0002773614457335755,\n \"f1\": 0.015742449664429566,\n\
\ \"f1_stderr\": 0.0006568370194517889,\n \"acc\": 0.2610447871046265,\n\
\ \"acc_stderr\": 0.00838467769872364\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0007340604026845638,\n \"em_stderr\": 0.0002773614457335755,\n\
\ \"f1\": 0.015742449664429566,\n \"f1_stderr\": 0.0006568370194517889\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.009855951478392721,\n \
\ \"acc_stderr\": 0.00272107657704166\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.5122336227308603,\n \"acc_stderr\": 0.01404827882040562\n\
\ }\n}\n```"
repo_url: https://huggingface.co/bigcode/tiny_starcoder_py
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_19T18_53_24.895112
path:
- '**/details_harness|arc:challenge|25_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T18_41_27.030233
path:
- '**/details_harness|drop|3_2023-09-17T18-41-27.030233.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T18-41-27.030233.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T18_41_27.030233
path:
- '**/details_harness|gsm8k|5_2023-09-17T18-41-27.030233.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T18-41-27.030233.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hellaswag|10_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:53:24.895112.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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path:
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- split: latest
path:
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- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:53:24.895112.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
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path:
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- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T18:53:24.895112.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T18_41_27.030233
path:
- '**/details_harness|winogrande|5_2023-09-17T18-41-27.030233.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T18-41-27.030233.parquet'
- config_name: results
data_files:
- split: 2023_07_19T18_53_24.895112
path:
- results_2023-07-19T18:53:24.895112.parquet
- split: 2023_09_17T18_41_27.030233
path:
- results_2023-09-17T18-41-27.030233.parquet
- split: latest
path:
- results_2023-09-17T18-41-27.030233.parquet
---
# Dataset Card for Evaluation run of bigcode/tiny_starcoder_py
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/bigcode/tiny_starcoder_py
- **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 [bigcode/tiny_starcoder_py](https://huggingface.co/bigcode/tiny_starcoder_py) 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_bigcode__tiny_starcoder_py",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-17T18:41:27.030233](https://huggingface.co/datasets/open-llm-leaderboard/details_bigcode__tiny_starcoder_py/blob/main/results_2023-09-17T18-41-27.030233.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.0007340604026845638,
"em_stderr": 0.0002773614457335755,
"f1": 0.015742449664429566,
"f1_stderr": 0.0006568370194517889,
"acc": 0.2610447871046265,
"acc_stderr": 0.00838467769872364
},
"harness|drop|3": {
"em": 0.0007340604026845638,
"em_stderr": 0.0002773614457335755,
"f1": 0.015742449664429566,
"f1_stderr": 0.0006568370194517889
},
"harness|gsm8k|5": {
"acc": 0.009855951478392721,
"acc_stderr": 0.00272107657704166
},
"harness|winogrande|5": {
"acc": 0.5122336227308603,
"acc_stderr": 0.01404827882040562
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_illuin__test-custom-llama | open-llm-leaderboard | 2023-10-27T13:17:12Z | 336 | 0 | [
"region:us"
]
| null | 2023-08-17T23:56:35Z | ---
pretty_name: Evaluation run of illuin/test-custom-llama
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [illuin/test-custom-llama](https://huggingface.co/illuin/test-custom-llama) 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_illuin__test-custom-llama\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-27T13:17:00.562267](https://huggingface.co/datasets/open-llm-leaderboard/details_illuin__test-custom-llama/blob/main/results_2023-10-27T13-17-00.562267.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\": 0.004089765100671141,\n\
\ \"em_stderr\": 0.0006535802669912844,\n \"f1\": 0.06308619966442945,\n\
\ \"f1_stderr\": 0.0014549394005291911,\n \"acc\": 0.38039089908704843,\n\
\ \"acc_stderr\": 0.009010133138187597\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.004089765100671141,\n \"em_stderr\": 0.0006535802669912844,\n\
\ \"f1\": 0.06308619966442945,\n \"f1_stderr\": 0.0014549394005291911\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0401819560272934,\n \
\ \"acc_stderr\": 0.005409439736970511\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7205998421468035,\n \"acc_stderr\": 0.012610826539404684\n\
\ }\n}\n```"
repo_url: https://huggingface.co/illuin/test-custom-llama
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_19T20_12_39.825467
path:
- '**/details_harness|arc:challenge|25_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_27T13_17_00.562267
path:
- '**/details_harness|drop|3_2023-10-27T13-17-00.562267.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-27T13-17-00.562267.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_27T13_17_00.562267
path:
- '**/details_harness|gsm8k|5_2023-10-27T13-17-00.562267.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-27T13-17-00.562267.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hellaswag|10_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T20:12:39.825467.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T20:12:39.825467.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-07-19T20:12:39.825467.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_27T13_17_00.562267
path:
- '**/details_harness|winogrande|5_2023-10-27T13-17-00.562267.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-27T13-17-00.562267.parquet'
- config_name: results
data_files:
- split: 2023_07_19T20_12_39.825467
path:
- results_2023-07-19T20:12:39.825467.parquet
- split: 2023_10_27T13_17_00.562267
path:
- results_2023-10-27T13-17-00.562267.parquet
- split: latest
path:
- results_2023-10-27T13-17-00.562267.parquet
---
# Dataset Card for Evaluation run of illuin/test-custom-llama
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/illuin/test-custom-llama
- **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 [illuin/test-custom-llama](https://huggingface.co/illuin/test-custom-llama) 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_illuin__test-custom-llama",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-27T13:17:00.562267](https://huggingface.co/datasets/open-llm-leaderboard/details_illuin__test-custom-llama/blob/main/results_2023-10-27T13-17-00.562267.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": 0.004089765100671141,
"em_stderr": 0.0006535802669912844,
"f1": 0.06308619966442945,
"f1_stderr": 0.0014549394005291911,
"acc": 0.38039089908704843,
"acc_stderr": 0.009010133138187597
},
"harness|drop|3": {
"em": 0.004089765100671141,
"em_stderr": 0.0006535802669912844,
"f1": 0.06308619966442945,
"f1_stderr": 0.0014549394005291911
},
"harness|gsm8k|5": {
"acc": 0.0401819560272934,
"acc_stderr": 0.005409439736970511
},
"harness|winogrande|5": {
"acc": 0.7205998421468035,
"acc_stderr": 0.012610826539404684
}
}
```
### 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] | [
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|
open-llm-leaderboard/details_l3utterfly__llama2-7b-layla | open-llm-leaderboard | 2023-09-17T04:33:05Z | 336 | 0 | [
"region:us"
]
| null | 2023-08-18T00:12:44Z | ---
pretty_name: Evaluation run of l3utterfly/llama2-7b-layla
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [l3utterfly/llama2-7b-layla](https://huggingface.co/l3utterfly/llama2-7b-layla)\
\ 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_l3utterfly__llama2-7b-layla\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-17T04:32:53.780547](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__llama2-7b-layla/blob/main/results_2023-09-17T04-32-53.780547.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\": 0.0005131152834514622,\n \"f1\": 0.06570889261744958,\n\
\ \"f1_stderr\": 0.0014756748283544432,\n \"acc\": 0.4130167852161326,\n\
\ \"acc_stderr\": 0.009994364317722083\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.0025167785234899327,\n \"em_stderr\": 0.0005131152834514622,\n\
\ \"f1\": 0.06570889261744958,\n \"f1_stderr\": 0.0014756748283544432\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.08491281273692192,\n \
\ \"acc_stderr\": 0.007678212824450795\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7411207576953434,\n \"acc_stderr\": 0.012310515810993372\n\
\ }\n}\n```"
repo_url: https://huggingface.co/l3utterfly/llama2-7b-layla
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|arc:challenge|25_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_17T04_32_53.780547
path:
- '**/details_harness|drop|3_2023-09-17T04-32-53.780547.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-17T04-32-53.780547.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_17T04_32_53.780547
path:
- '**/details_harness|gsm8k|5_2023-09-17T04-32-53.780547.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-17T04-32-53.780547.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hellaswag|10_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T20:58:39.874596.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T20:58:39.874596.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T20:58:39.874596.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_17T04_32_53.780547
path:
- '**/details_harness|winogrande|5_2023-09-17T04-32-53.780547.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-17T04-32-53.780547.parquet'
- config_name: results
data_files:
- split: 2023_08_09T20_58_39.874596
path:
- results_2023-08-09T20:58:39.874596.parquet
- split: 2023_09_17T04_32_53.780547
path:
- results_2023-09-17T04-32-53.780547.parquet
- split: latest
path:
- results_2023-09-17T04-32-53.780547.parquet
---
# Dataset Card for Evaluation run of l3utterfly/llama2-7b-layla
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/l3utterfly/llama2-7b-layla
- **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 [l3utterfly/llama2-7b-layla](https://huggingface.co/l3utterfly/llama2-7b-layla) 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_l3utterfly__llama2-7b-layla",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-17T04:32:53.780547](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__llama2-7b-layla/blob/main/results_2023-09-17T04-32-53.780547.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": 0.0005131152834514622,
"f1": 0.06570889261744958,
"f1_stderr": 0.0014756748283544432,
"acc": 0.4130167852161326,
"acc_stderr": 0.009994364317722083
},
"harness|drop|3": {
"em": 0.0025167785234899327,
"em_stderr": 0.0005131152834514622,
"f1": 0.06570889261744958,
"f1_stderr": 0.0014756748283544432
},
"harness|gsm8k|5": {
"acc": 0.08491281273692192,
"acc_stderr": 0.007678212824450795
},
"harness|winogrande|5": {
"acc": 0.7411207576953434,
"acc_stderr": 0.012310515810993372
}
}
```
### 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] | [
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|
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