davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
joey234/mmlu-high_school_us_history-neg-prepend-fix	--- configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: ori_prompt dtype: string splits: - name: dev num_bytes: 28257 num_examples: 5 - name: test num_bytes: 1258154 num_examples: 204 download_size: 55081 dataset_size: 1286411 --- # Dataset Card for "mmlu-high_school_us_history-neg-prepend-fix" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
HamdanXI/paradetox-preprocess-editOps	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: en_toxic_comment dtype: string - name: en_neutral_comment dtype: string - name: edit_ops sequence: sequence: string splits: - name: train num_bytes: 4628797 num_examples: 19744 download_size: 1848112 dataset_size: 4628797 --- # Dataset Card for "paradetox-preprocess-editOps" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-1b5bc0-46134145181	--- type: predictions tags: - autotrain - evaluation datasets: - adversarial_qa eval_info: task: extractive_question_answering model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat metrics: [] dataset_name: adversarial_qa dataset_config: adversarialQA dataset_split: validation col_mapping: context: context question: question answers-text: answers.text answers-answer_start: answers.answer_start --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Question Answering * Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat * Dataset: adversarial_qa * Config: adversarialQA * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@nomic-ai](https://huggingface.co/nomic-ai) for evaluating this model.
huggingartists/phish	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/phish" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.372501 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/df85b83684e95f87794aa09580ee0463.919x919x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/phish"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Phish</div> <a href="https://genius.com/artists/phish"> <div style="text-align: center; font-size: 14px;">@phish</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/phish). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/phish") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|394\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/phish") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)
FINNUMBER/FINCH_TRAIN_NQA_ARI_100_NEWFORMAT	--- dataset_info: features: - name: task dtype: string - name: context dtype: string - name: question dtype: string - name: answer dtype: string - name: instruction dtype: string - name: output dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 279758 num_examples: 100 download_size: 175553 dataset_size: 279758 configs: - config_name: default data_files: - split: train path: data/train-* ---
YAGO1818/LunaVB	--- license: apache-2.0 ---
carlavic/Moedas	--- license: openrail ---
YiYiXu/yiyi_test_ds	--- dataset_info: features: - name: image dtype: image - name: condtioning_image dtype: image - name: caption dtype: string splits: - name: train num_bytes: 22659003.0 num_examples: 15 download_size: 22663578 dataset_size: 22659003.0 --- # Dataset Card for "yiyi_test_ds" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
HydraLM/partitioned_v2_standardized_07	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: dataset_id dtype: string - name: unique_conversation_id dtype: string splits: - name: train num_bytes: 33994535.7580061 num_examples: 66505 download_size: 36546793 dataset_size: 33994535.7580061 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "partitioned_v2_standardized_07" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
BangumiBase/seireinomoribito	--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Seirei No Moribito This is the image base of bangumi Seirei no Moribito, we detected 26 characters, 2981 images in total. The full dataset is [here](all.zip). Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: \| # \| Images \| Download \| Preview 1 \| Preview 2 \| Preview 3 \| Preview 4 \| Preview 5 \| Preview 6 \| Preview 7 \| Preview 8 \| \|:------\|---------:\|:---------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\| \| 0 \| 593 \| [Download](0/dataset.zip) \| ![preview 1](0/preview_1.png) \| ![preview 2](0/preview_2.png) \| ![preview 3](0/preview_3.png) \| ![preview 4](0/preview_4.png) \| ![preview 5](0/preview_5.png) \| ![preview 6](0/preview_6.png) \| ![preview 7](0/preview_7.png) \| ![preview 8](0/preview_8.png) \| \| 1 \| 73 \| [Download](1/dataset.zip) \| ![preview 1](1/preview_1.png) \| ![preview 2](1/preview_2.png) \| ![preview 3](1/preview_3.png) \| ![preview 4](1/preview_4.png) \| ![preview 5](1/preview_5.png) \| ![preview 6](1/preview_6.png) \| ![preview 7](1/preview_7.png) \| ![preview 8](1/preview_8.png) \| \| 2 \| 487 \| [Download](2/dataset.zip) \| ![preview 1](2/preview_1.png) \| ![preview 2](2/preview_2.png) \| ![preview 3](2/preview_3.png) \| ![preview 4](2/preview_4.png) \| ![preview 5](2/preview_5.png) \| ![preview 6](2/preview_6.png) \| ![preview 7](2/preview_7.png) \| ![preview 8](2/preview_8.png) \| \| 3 \| 450 \| [Download](3/dataset.zip) \| ![preview 1](3/preview_1.png) \| ![preview 2](3/preview_2.png) \| ![preview 3](3/preview_3.png) \| ![preview 4](3/preview_4.png) \| ![preview 5](3/preview_5.png) \| ![preview 6](3/preview_6.png) \| ![preview 7](3/preview_7.png) \| ![preview 8](3/preview_8.png) \| \| 4 \| 327 \| [Download](4/dataset.zip) \| ![preview 1](4/preview_1.png) \| ![preview 2](4/preview_2.png) \| ![preview 3](4/preview_3.png) \| ![preview 4](4/preview_4.png) \| ![preview 5](4/preview_5.png) \| ![preview 6](4/preview_6.png) \| ![preview 7](4/preview_7.png) \| ![preview 8](4/preview_8.png) \| \| 5 \| 79 \| [Download](5/dataset.zip) \| ![preview 1](5/preview_1.png) \| ![preview 2](5/preview_2.png) \| ![preview 3](5/preview_3.png) \| ![preview 4](5/preview_4.png) \| ![preview 5](5/preview_5.png) \| ![preview 6](5/preview_6.png) \| ![preview 7](5/preview_7.png) \| ![preview 8](5/preview_8.png) \| \| 6 \| 33 \| [Download](6/dataset.zip) \| ![preview 1](6/preview_1.png) \| ![preview 2](6/preview_2.png) \| ![preview 3](6/preview_3.png) \| ![preview 4](6/preview_4.png) \| ![preview 5](6/preview_5.png) \| ![preview 6](6/preview_6.png) \| ![preview 7](6/preview_7.png) \| ![preview 8](6/preview_8.png) \| \| 7 \| 126 \| [Download](7/dataset.zip) \| ![preview 1](7/preview_1.png) \| ![preview 2](7/preview_2.png) \| ![preview 3](7/preview_3.png) \| ![preview 4](7/preview_4.png) \| ![preview 5](7/preview_5.png) \| ![preview 6](7/preview_6.png) \| ![preview 7](7/preview_7.png) \| ![preview 8](7/preview_8.png) \| \| 8 \| 81 \| [Download](8/dataset.zip) \| ![preview 1](8/preview_1.png) \| ![preview 2](8/preview_2.png) \| ![preview 3](8/preview_3.png) \| ![preview 4](8/preview_4.png) \| ![preview 5](8/preview_5.png) \| ![preview 6](8/preview_6.png) \| ![preview 7](8/preview_7.png) \| ![preview 8](8/preview_8.png) \| \| 9 \| 46 \| [Download](9/dataset.zip) \| ![preview 1](9/preview_1.png) \| ![preview 2](9/preview_2.png) \| ![preview 3](9/preview_3.png) \| ![preview 4](9/preview_4.png) \| ![preview 5](9/preview_5.png) \| ![preview 6](9/preview_6.png) \| ![preview 7](9/preview_7.png) \| ![preview 8](9/preview_8.png) \| \| 10 \| 43 \| [Download](10/dataset.zip) \| ![preview 1](10/preview_1.png) \| ![preview 2](10/preview_2.png) \| ![preview 3](10/preview_3.png) \| ![preview 4](10/preview_4.png) \| ![preview 5](10/preview_5.png) \| ![preview 6](10/preview_6.png) \| ![preview 7](10/preview_7.png) \| ![preview 8](10/preview_8.png) \| \| 11 \| 73 \| [Download](11/dataset.zip) \| ![preview 1](11/preview_1.png) \| ![preview 2](11/preview_2.png) \| ![preview 3](11/preview_3.png) \| ![preview 4](11/preview_4.png) \| ![preview 5](11/preview_5.png) \| ![preview 6](11/preview_6.png) \| ![preview 7](11/preview_7.png) \| ![preview 8](11/preview_8.png) \| \| 12 \| 16 \| [Download](12/dataset.zip) \| ![preview 1](12/preview_1.png) \| ![preview 2](12/preview_2.png) \| ![preview 3](12/preview_3.png) \| ![preview 4](12/preview_4.png) \| ![preview 5](12/preview_5.png) \| ![preview 6](12/preview_6.png) \| ![preview 7](12/preview_7.png) \| ![preview 8](12/preview_8.png) \| \| 13 \| 172 \| [Download](13/dataset.zip) \| ![preview 1](13/preview_1.png) \| ![preview 2](13/preview_2.png) \| ![preview 3](13/preview_3.png) \| ![preview 4](13/preview_4.png) \| ![preview 5](13/preview_5.png) \| ![preview 6](13/preview_6.png) \| ![preview 7](13/preview_7.png) \| ![preview 8](13/preview_8.png) \| \| 14 \| 96 \| [Download](14/dataset.zip) \| ![preview 1](14/preview_1.png) \| ![preview 2](14/preview_2.png) \| ![preview 3](14/preview_3.png) \| ![preview 4](14/preview_4.png) \| ![preview 5](14/preview_5.png) \| ![preview 6](14/preview_6.png) \| ![preview 7](14/preview_7.png) \| ![preview 8](14/preview_8.png) \| \| 15 \| 18 \| [Download](15/dataset.zip) \| ![preview 1](15/preview_1.png) \| ![preview 2](15/preview_2.png) \| ![preview 3](15/preview_3.png) \| ![preview 4](15/preview_4.png) \| ![preview 5](15/preview_5.png) \| ![preview 6](15/preview_6.png) \| ![preview 7](15/preview_7.png) \| ![preview 8](15/preview_8.png) \| \| 16 \| 62 \| [Download](16/dataset.zip) \| ![preview 1](16/preview_1.png) \| ![preview 2](16/preview_2.png) \| ![preview 3](16/preview_3.png) \| ![preview 4](16/preview_4.png) \| ![preview 5](16/preview_5.png) \| ![preview 6](16/preview_6.png) \| ![preview 7](16/preview_7.png) \| ![preview 8](16/preview_8.png) \| \| 17 \| 18 \| [Download](17/dataset.zip) \| ![preview 1](17/preview_1.png) \| ![preview 2](17/preview_2.png) \| ![preview 3](17/preview_3.png) \| ![preview 4](17/preview_4.png) \| ![preview 5](17/preview_5.png) \| ![preview 6](17/preview_6.png) \| ![preview 7](17/preview_7.png) \| ![preview 8](17/preview_8.png) \| \| 18 \| 53 \| [Download](18/dataset.zip) \| ![preview 1](18/preview_1.png) \| ![preview 2](18/preview_2.png) \| ![preview 3](18/preview_3.png) \| ![preview 4](18/preview_4.png) \| ![preview 5](18/preview_5.png) \| ![preview 6](18/preview_6.png) \| ![preview 7](18/preview_7.png) \| ![preview 8](18/preview_8.png) \| \| 19 \| 24 \| [Download](19/dataset.zip) \| ![preview 1](19/preview_1.png) \| ![preview 2](19/preview_2.png) \| ![preview 3](19/preview_3.png) \| ![preview 4](19/preview_4.png) \| ![preview 5](19/preview_5.png) \| ![preview 6](19/preview_6.png) \| ![preview 7](19/preview_7.png) \| ![preview 8](19/preview_8.png) \| \| 20 \| 28 \| [Download](20/dataset.zip) \| ![preview 1](20/preview_1.png) \| ![preview 2](20/preview_2.png) \| ![preview 3](20/preview_3.png) \| ![preview 4](20/preview_4.png) \| ![preview 5](20/preview_5.png) \| ![preview 6](20/preview_6.png) \| ![preview 7](20/preview_7.png) \| ![preview 8](20/preview_8.png) \| \| 21 \| 11 \| [Download](21/dataset.zip) \| ![preview 1](21/preview_1.png) \| ![preview 2](21/preview_2.png) \| ![preview 3](21/preview_3.png) \| ![preview 4](21/preview_4.png) \| ![preview 5](21/preview_5.png) \| ![preview 6](21/preview_6.png) \| ![preview 7](21/preview_7.png) \| ![preview 8](21/preview_8.png) \| \| 22 \| 14 \| [Download](22/dataset.zip) \| ![preview 1](22/preview_1.png) \| ![preview 2](22/preview_2.png) \| ![preview 3](22/preview_3.png) \| ![preview 4](22/preview_4.png) \| ![preview 5](22/preview_5.png) \| ![preview 6](22/preview_6.png) \| ![preview 7](22/preview_7.png) \| ![preview 8](22/preview_8.png) \| \| 23 \| 12 \| [Download](23/dataset.zip) \| ![preview 1](23/preview_1.png) \| ![preview 2](23/preview_2.png) \| ![preview 3](23/preview_3.png) \| ![preview 4](23/preview_4.png) \| ![preview 5](23/preview_5.png) \| ![preview 6](23/preview_6.png) \| ![preview 7](23/preview_7.png) \| ![preview 8](23/preview_8.png) \| \| 24 \| 12 \| [Download](24/dataset.zip) \| ![preview 1](24/preview_1.png) \| ![preview 2](24/preview_2.png) \| ![preview 3](24/preview_3.png) \| ![preview 4](24/preview_4.png) \| ![preview 5](24/preview_5.png) \| ![preview 6](24/preview_6.png) \| ![preview 7](24/preview_7.png) \| ![preview 8](24/preview_8.png) \| \| noise \| 34 \| [Download](-1/dataset.zip) \| ![preview 1](-1/preview_1.png) \| ![preview 2](-1/preview_2.png) \| ![preview 3](-1/preview_3.png) \| ![preview 4](-1/preview_4.png) \| ![preview 5](-1/preview_5.png) \| ![preview 6](-1/preview_6.png) \| ![preview 7](-1/preview_7.png) \| ![preview 8](-1/preview_8.png) \|
piercemaloney/coqgym_coq_projects_v1	--- dataset_info: features: - name: text dtype: string splits: - name: finmap num_bytes: 745110 num_examples: 3 - name: GeometricAlgebra num_bytes: 2180457 num_examples: 8 - name: bdds num_bytes: 11537326 num_examples: 15 - name: topology num_bytes: 1998914 num_examples: 32 - name: euler_formula num_bytes: 2157257 num_examples: 3 - name: ruler_compass_geometry num_bytes: 105862 num_examples: 10 - name: twoSquare num_bytes: 219009 num_examples: 2 - name: zfc num_bytes: 605621 num_examples: 11 - name: shuffle num_bytes: 87431 num_examples: 6 - name: three_gap num_bytes: 315458 num_examples: 7 - name: regexp num_bytes: 116907 num_examples: 7 - name: automata num_bytes: 1075636 num_examples: 25 - name: izf num_bytes: 146423 num_examples: 8 - name: railroad_crossing num_bytes: 202543 num_examples: 1 - name: idxassoc num_bytes: 139339 num_examples: 2 - name: hoare_tut num_bytes: 39069 num_examples: 3 - name: lesniewski_mereology num_bytes: 123636 num_examples: 2 - name: additions num_bytes: 147048 num_examples: 20 - name: checker num_bytes: 6689 num_examples: 2 - name: domain_theory num_bytes: 67545 num_examples: 4 - name: propcalc num_bytes: 54422 num_examples: 5 - name: area_method num_bytes: 1578799 num_examples: 38 - name: ails num_bytes: 521926 num_examples: 11 - name: dep_map num_bytes: 24951 num_examples: 2 - name: markov num_bytes: 102887 num_examples: 1 - name: rsa num_bytes: 180155 num_examples: 5 - name: goedel num_bytes: 9110441 num_examples: 44 - name: bigenough num_bytes: 5031 num_examples: 1 - name: generic_environments num_bytes: 142529 num_examples: 2 - name: ctltctl num_bytes: 61038 num_examples: 3 - name: schroeder num_bytes: 24958 num_examples: 4 - name: weak_up_to num_bytes: 175365 num_examples: 10 - name: groups num_bytes: 11115 num_examples: 1 - name: pocklington num_bytes: 617483 num_examples: 13 - name: mini_compiler num_bytes: 14459 num_examples: 1 - name: StructTact num_bytes: 293887 num_examples: 17 - name: exceptions num_bytes: 8962 num_examples: 1 - name: coqrel num_bytes: 196290 num_examples: 12 - name: higman_s num_bytes: 198793 num_examples: 5 - name: rem num_bytes: 14504 num_examples: 1 - name: tree_automata num_bytes: 1972575 num_examples: 17 - name: higman_cf num_bytes: 49720 num_examples: 2 - name: coqoban num_bytes: 38285 num_examples: 1 - name: search_trees num_bytes: 59332 num_examples: 5 - name: ieee754 num_bytes: 35416 num_examples: 3 - name: jordan_curve_theorem num_bytes: 12530912 num_examples: 10 - name: hedges num_bytes: 360884 num_examples: 1 - name: zorns_lemma num_bytes: 608752 num_examples: 19 - name: tortoise_hare_algorithm num_bytes: 10084 num_examples: 1 - name: mod_red num_bytes: 636981 num_examples: 5 - name: traversable_fincontainer num_bytes: 429019 num_examples: 1 - name: buchberger num_bytes: 2422607 num_examples: 29 - name: constructive_geometry num_bytes: 80179 num_examples: 7 - name: tarski_geometry num_bytes: 112419 num_examples: 8 - name: int_map num_bytes: 817835 num_examples: 13 - name: float num_bytes: 2994074 num_examples: 31 - name: InfSeqExt num_bytes: 106656 num_examples: 5 - name: zchinese num_bytes: 62626 num_examples: 6 - name: smc num_bytes: 6045540 num_examples: 15 - name: pts num_bytes: 72482 num_examples: 8 - name: param_pi num_bytes: 2596347 num_examples: 11 - name: axiomatic_abp num_bytes: 1204713 num_examples: 7 - name: lambda num_bytes: 181085 num_examples: 10 - name: maths num_bytes: 37685 num_examples: 3 - name: quicksort_complexity num_bytes: 489164 num_examples: 28 - name: fssec_model num_bytes: 1569135 num_examples: 25 - name: ipc num_bytes: 3108901 num_examples: 31 - name: chinese num_bytes: 208365 num_examples: 13 - name: cours_de_coq num_bytes: 71295 num_examples: 11 - name: graphs num_bytes: 644609 num_examples: 2 - name: dictionaries num_bytes: 67746 num_examples: 1 - name: free_groups num_bytes: 63973 num_examples: 1 - name: ramsey num_bytes: 11734 num_examples: 1 - name: angles num_bytes: 322579 num_examples: 5 - name: orb_stab num_bytes: 204783 num_examples: 1 - name: qarith_stern_brocot num_bytes: 10873352 num_examples: 35 - name: group_theory num_bytes: 65160 num_examples: 5 - name: demos num_bytes: 62208 num_examples: 5 - name: distributed_reference_counting num_bytes: 20874 num_examples: 1 - name: subst num_bytes: 362195 num_examples: 17 - name: miniml num_bytes: 114099 num_examples: 1 - name: algebra num_bytes: 3275753 num_examples: 65 - name: fermat4 num_bytes: 172156 num_examples: 5 - name: otway_rees num_bytes: 226052 num_examples: 19 - name: PolTac num_bytes: 157370 num_examples: 13 - name: fundamental_arithmetics num_bytes: 308733 num_examples: 8 download_size: 11353498 dataset_size: 91221719 configs: - config_name: default data_files: - split: finmap path: data/finmap-* - split: GeometricAlgebra path: data/GeometricAlgebra-* - split: bdds path: data/bdds-* - split: topology path: data/topology-* - split: euler_formula path: data/euler_formula-* - split: ruler_compass_geometry path: data/ruler_compass_geometry-* - split: twoSquare path: data/twoSquare-* - split: zfc path: data/zfc-* - split: shuffle path: data/shuffle-* - split: three_gap path: data/three_gap-* - split: regexp path: data/regexp-* - split: automata path: data/automata-* - split: izf path: data/izf-* - split: railroad_crossing path: data/railroad_crossing-* - split: idxassoc path: data/idxassoc-* - split: hoare_tut path: data/hoare_tut-* - split: lesniewski_mereology path: data/lesniewski_mereology-* - split: additions path: data/additions-* - split: checker path: data/checker-* - split: domain_theory path: data/domain_theory-* - split: propcalc path: data/propcalc-* - split: area_method path: data/area_method-* - split: ails path: data/ails-* - split: dep_map path: data/dep_map-* - split: markov path: data/markov-* - split: rsa path: data/rsa-* - split: goedel path: data/goedel-* - split: bigenough path: data/bigenough-* - split: generic_environments path: data/generic_environments-* - split: ctltctl path: data/ctltctl-* - split: schroeder path: data/schroeder-* - split: weak_up_to path: data/weak_up_to-* - split: groups path: data/groups-* - split: pocklington path: data/pocklington-* - split: mini_compiler path: data/mini_compiler-* - split: StructTact path: data/StructTact-* - split: exceptions path: data/exceptions-* - split: coqrel path: data/coqrel-* - split: higman_s path: data/higman_s-* - split: rem path: data/rem-* - split: tree_automata path: data/tree_automata-* - split: higman_cf path: data/higman_cf-* - split: coqoban path: data/coqoban-* - split: search_trees path: data/search_trees-* - split: ieee754 path: data/ieee754-* - split: jordan_curve_theorem path: data/jordan_curve_theorem-* - split: hedges path: data/hedges-* - split: zorns_lemma path: data/zorns_lemma-* - split: tortoise_hare_algorithm path: data/tortoise_hare_algorithm-* - split: mod_red path: data/mod_red-* - split: traversable_fincontainer path: data/traversable_fincontainer-* - split: buchberger path: data/buchberger-* - split: constructive_geometry path: data/constructive_geometry-* - split: tarski_geometry path: data/tarski_geometry-* - split: int_map path: data/int_map-* - split: float path: data/float-* - split: InfSeqExt path: data/InfSeqExt-* - split: zchinese path: data/zchinese-* - split: smc path: data/smc-* - split: pts path: data/pts-* - split: param_pi path: data/param_pi-* - split: axiomatic_abp path: data/axiomatic_abp-* - split: lambda path: data/lambda-* - split: maths path: data/maths-* - split: quicksort_complexity path: data/quicksort_complexity-* - split: fssec_model path: data/fssec_model-* - split: ipc path: data/ipc-* - split: chinese path: data/chinese-* - split: cours_de_coq path: data/cours_de_coq-* - split: graphs path: data/graphs-* - split: dictionaries path: data/dictionaries-* - split: free_groups path: data/free_groups-* - split: ramsey path: data/ramsey-* - split: angles path: data/angles-* - split: orb_stab path: data/orb_stab-* - split: qarith_stern_brocot path: data/qarith_stern_brocot-* - split: group_theory path: data/group_theory-* - split: demos path: data/demos-* - split: distributed_reference_counting path: data/distributed_reference_counting-* - split: subst path: data/subst-* - split: miniml path: data/miniml-* - split: algebra path: data/algebra-* - split: fermat4 path: data/fermat4-* - split: otway_rees path: data/otway_rees-* - split: PolTac path: data/PolTac-* - split: fundamental_arithmetics path: data/fundamental_arithmetics-* ---
YidaM4396/Test	--- license: mit ---
Mizukico/sd-config	--- license: openrail ---
filwsyl/ascend	--- annotations_creators: - expert-generated language_creators: - crowdsourced language: - en - zh language_bcp47: - en - zh-CN license: - cc-by-sa-4.0 multilinguality: - multilingual pretty_name: 'ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation' size_categories: - 10K<n<100K source_datasets: - original task_categories: - automatic-speech-recognition task_ids: - code-switching - speech-recognition --- # Dataset Card for ASCEND ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - Homepage: [Needs More Information] - Repository: [Needs More Information] - Paper: https://arxiv.org/abs/2112.06223 - Leaderboard: [Needs More Information] - Point of Contact: [Needs More Information] ### Dataset Summary ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set. ### Supported Tasks and Leaderboards [Needs More Information] ### Languages Chinese and English ## Dataset Structure ### Data Instances [Needs More Information] ### Data Fields [Needs More Information] ### Data Splits [Needs More Information] ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information [Needs More Information] ### Citation Information [Needs More Information]
sunhaozhepy/ag_news_roberta_keywords_embeddings	--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': World '1': Sports '2': Business '3': Sci/Tech - name: keywords dtype: string - name: keywords_embeddings sequence: float32 splits: - name: train num_bytes: 401783299 num_examples: 120000 - name: test num_bytes: 25437883 num_examples: 7600 download_size: 493380668 dataset_size: 427221182 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
suchirsalhan/MAO-CHILDES	--- license: mit ---
open-llm-leaderboard/details_mosaicml__mpt-7b-instruct	--- pretty_name: Evaluation run of mosaicml/mpt-7b-instruct dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) 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_mosaicml__mpt-7b-instruct\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T07:03:23.990596](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b-instruct/blob/main/results_2023-09-23T07-03-23.990596.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\": 0.2429739932885906,\n\ \ \"em_stderr\": 0.004392127579519805,\n \"f1\": 0.2939712667785233,\n\ \ \"f1_stderr\": 0.004382684089142145,\n \"acc\": 0.3664330383509068,\n\ \ \"acc_stderr\": 0.00868382013779556\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.2429739932885906,\n \"em_stderr\": 0.004392127579519805,\n\ \ \"f1\": 0.2939712667785233,\n \"f1_stderr\": 0.004382684089142145\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.028051554207733132,\n \ \ \"acc_stderr\": 0.0045482295338363475\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7048145224940805,\n \"acc_stderr\": 0.012819410741754772\n\ \ }\n}\n```" repo_url: https://huggingface.co/mosaicml/mpt-7b-instruct leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|arc:challenge\|25_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-20T10:01:10.556120.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T07_03_23.990596 path: - '/details_harness\|drop\|3_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-23T07-03-23.990596.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T07_03_23.990596 path: - '/details_harness\|gsm8k\|5_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-23T07-03-23.990596.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hellaswag\|10_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-20T10:01:10.556120.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_20T10_01_10.556120 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-20T10:01:10.556120.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T07_03_23.990596 path: - '/details_harness\|winogrande\|5_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-23T07-03-23.990596.parquet' - config_name: results data_files: - split: 2023_07_20T10_01_10.556120 path: - results_2023-07-20T10:01:10.556120.parquet - split: 2023_09_23T07_03_23.990596 path: - results_2023-09-23T07-03-23.990596.parquet - split: latest path: - results_2023-09-23T07-03-23.990596.parquet --- # Dataset Card for Evaluation run of mosaicml/mpt-7b-instruct ## Dataset Description - Homepage: - Repository: https://huggingface.co/mosaicml/mpt-7b-instruct - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) 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_mosaicml__mpt-7b-instruct", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T07:03:23.990596](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b-instruct/blob/main/results_2023-09-23T07-03-23.990596.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": 0.2429739932885906, "em_stderr": 0.004392127579519805, "f1": 0.2939712667785233, "f1_stderr": 0.004382684089142145, "acc": 0.3664330383509068, "acc_stderr": 0.00868382013779556 }, "harness\|drop\|3": { "em": 0.2429739932885906, "em_stderr": 0.004392127579519805, "f1": 0.2939712667785233, "f1_stderr": 0.004382684089142145 }, "harness\|gsm8k\|5": { "acc": 0.028051554207733132, "acc_stderr": 0.0045482295338363475 }, "harness\|winogrande\|5": { "acc": 0.7048145224940805, "acc_stderr": 0.012819410741754772 } } ``` ### 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]
mtalrefaie/arallama-dataset-v1.0	--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string - name: meta struct: - name: warc_headers struct: - name: warc-record-id dtype: string - name: warc-date dtype: string - name: content-type dtype: string - name: content-length dtype: int32 - name: warc-type dtype: string - name: warc-identified-content-language dtype: string - name: warc-refers-to dtype: string - name: warc-target-uri dtype: string - name: warc-block-digest dtype: string - name: identification struct: - name: label dtype: string - name: prob dtype: float32 - name: harmful_pp dtype: float32 - name: tlsh dtype: string - name: quality_warnings sequence: string - name: categories sequence: string - name: sentence_identifications list: - name: label dtype: string - name: prob dtype: float32 splits: - name: train num_bytes: 63195041070 num_examples: 4975268 download_size: 29939473314 dataset_size: 63195041070 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1	--- pretty_name: Evaluation run of mistralai/Mixtral-8x7B-Instruct-v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_mistralai__Mixtral-8x7B-Instruct-v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-05T04:20:22.140239](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1/blob/main/results_2024-01-05T04-20-22.140239.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\": 0.7126033327488117,\n\ \ \"acc_stderr\": 0.030215739102142546,\n \"acc_norm\": 0.7164863994184663,\n\ \ \"acc_norm_stderr\": 0.030796061622697008,\n \"mc1\": 0.5006119951040392,\n\ \ \"mc1_stderr\": 0.01750348793889251,\n \"mc2\": 0.649788114114722,\n\ \ \"mc2_stderr\": 0.015119260704075871\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6655290102389079,\n \"acc_stderr\": 0.013787460322441377,\n\ \ \"acc_norm\": 0.7013651877133106,\n \"acc_norm_stderr\": 0.013374078615068738\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6858195578570006,\n\ \ \"acc_stderr\": 0.004632399677490809,\n \"acc_norm\": 0.8755228042222665,\n\ \ \"acc_norm_stderr\": 0.003294504807555227\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6666666666666666,\n\ \ \"acc_stderr\": 0.04072314811876837,\n \"acc_norm\": 0.6666666666666666,\n\ \ \"acc_norm_stderr\": 0.04072314811876837\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7894736842105263,\n \"acc_stderr\": 0.03317672787533157,\n\ \ \"acc_norm\": 0.7894736842105263,\n \"acc_norm_stderr\": 0.03317672787533157\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.73,\n\ \ \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n \ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7773584905660378,\n \"acc_stderr\": 0.025604233470899098,\n\ \ \"acc_norm\": 0.7773584905660378,\n \"acc_norm_stderr\": 0.025604233470899098\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8263888888888888,\n\ \ \"acc_stderr\": 0.03167473383795718,\n \"acc_norm\": 0.8263888888888888,\n\ \ \"acc_norm_stderr\": 0.03167473383795718\n },\n \"harness\|hendrycksTest-college_chemistry\|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-college_computer_science\|5\": {\n \"acc\"\ : 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\": 0.66,\n\ \ \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness\|hendrycksTest-college_mathematics\|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_medicine\|5\": {\n \"acc\": 0.7572254335260116,\n\ \ \"acc_stderr\": 0.0326926380614177,\n \"acc_norm\": 0.7572254335260116,\n\ \ \"acc_norm_stderr\": 0.0326926380614177\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287534,\n\ \ \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287534\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.81,\n \"acc_stderr\": 0.039427724440366234,\n \"acc_norm\": 0.81,\n\ \ \"acc_norm_stderr\": 0.039427724440366234\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6680851063829787,\n \"acc_stderr\": 0.03078373675774564,\n\ \ \"acc_norm\": 0.6680851063829787,\n \"acc_norm_stderr\": 0.03078373675774564\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.6140350877192983,\n\ \ \"acc_stderr\": 0.04579639422070434,\n \"acc_norm\": 0.6140350877192983,\n\ \ \"acc_norm_stderr\": 0.04579639422070434\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6482758620689655,\n \"acc_stderr\": 0.0397923663749741,\n\ \ \"acc_norm\": 0.6482758620689655,\n \"acc_norm_stderr\": 0.0397923663749741\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.47883597883597884,\n \"acc_stderr\": 0.025728230952130726,\n \"\ acc_norm\": 0.47883597883597884,\n \"acc_norm_stderr\": 0.025728230952130726\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\": 0.42,\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\"\ : 0.8516129032258064,\n \"acc_stderr\": 0.020222737554330378,\n \"\ acc_norm\": 0.8516129032258064,\n \"acc_norm_stderr\": 0.020222737554330378\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.6206896551724138,\n \"acc_stderr\": 0.034139638059062345,\n \"\ acc_norm\": 0.6206896551724138,\n \"acc_norm_stderr\": 0.034139638059062345\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.78,\n \"acc_stderr\": 0.041633319989322626,\n \"acc_norm\"\ : 0.78,\n \"acc_norm_stderr\": 0.041633319989322626\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.03123475237772117,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.03123475237772117\n },\n\ \ \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\": 0.8686868686868687,\n\ \ \"acc_stderr\": 0.024063156416822523,\n \"acc_norm\": 0.8686868686868687,\n\ \ \"acc_norm_stderr\": 0.024063156416822523\n },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\"\ : {\n \"acc\": 0.9585492227979274,\n \"acc_stderr\": 0.01438543285747646,\n\ \ \"acc_norm\": 0.9585492227979274,\n \"acc_norm_stderr\": 0.01438543285747646\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3888888888888889,\n \"acc_stderr\": 0.029723278961476664,\n \ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.029723278961476664\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.8025210084033614,\n \"acc_stderr\": 0.02585916412205145,\n \ \ \"acc_norm\": 0.8025210084033614,\n \"acc_norm_stderr\": 0.02585916412205145\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\"\ : 0.8844036697247707,\n \"acc_stderr\": 0.013708749534172636,\n \"\ acc_norm\": 0.8844036697247707,\n \"acc_norm_stderr\": 0.013708749534172636\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5972222222222222,\n \"acc_stderr\": 0.03344887382997866,\n \"\ acc_norm\": 0.5972222222222222,\n \"acc_norm_stderr\": 0.03344887382997866\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8529411764705882,\n \"acc_stderr\": 0.024857478080250447,\n \"\ acc_norm\": 0.8529411764705882,\n \"acc_norm_stderr\": 0.024857478080250447\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8481012658227848,\n \"acc_stderr\": 0.023363878096632446,\n \ \ \"acc_norm\": 0.8481012658227848,\n \"acc_norm_stderr\": 0.023363878096632446\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.757847533632287,\n\ \ \"acc_stderr\": 0.028751392398694755,\n \"acc_norm\": 0.757847533632287,\n\ \ \"acc_norm_stderr\": 0.028751392398694755\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8091603053435115,\n \"acc_stderr\": 0.034465133507525975,\n\ \ \"acc_norm\": 0.8091603053435115,\n \"acc_norm_stderr\": 0.034465133507525975\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8760330578512396,\n \"acc_stderr\": 0.030083098716035202,\n \"\ acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.030083098716035202\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8425925925925926,\n\ \ \"acc_stderr\": 0.03520703990517963,\n \"acc_norm\": 0.8425925925925926,\n\ \ \"acc_norm_stderr\": 0.03520703990517963\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8159509202453987,\n \"acc_stderr\": 0.030446777687971716,\n\ \ \"acc_norm\": 0.8159509202453987,\n \"acc_norm_stderr\": 0.030446777687971716\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5714285714285714,\n\ \ \"acc_stderr\": 0.04697113923010213,\n \"acc_norm\": 0.5714285714285714,\n\ \ \"acc_norm_stderr\": 0.04697113923010213\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.035865947385739734,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.035865947385739734\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9230769230769231,\n\ \ \"acc_stderr\": 0.017456987872436193,\n \"acc_norm\": 0.9230769230769231,\n\ \ \"acc_norm_stderr\": 0.017456987872436193\n },\n \"harness\|hendrycksTest-medical_genetics\|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-miscellaneous\|5\": {\n \"acc\": 0.879948914431673,\n\ \ \"acc_stderr\": 0.011622736692041287,\n \"acc_norm\": 0.879948914431673,\n\ \ \"acc_norm_stderr\": 0.011622736692041287\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7803468208092486,\n \"acc_stderr\": 0.022289638852617897,\n\ \ \"acc_norm\": 0.7803468208092486,\n \"acc_norm_stderr\": 0.022289638852617897\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.46033519553072627,\n\ \ \"acc_stderr\": 0.016669799592112032,\n \"acc_norm\": 0.46033519553072627,\n\ \ \"acc_norm_stderr\": 0.016669799592112032\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.8202614379084967,\n \"acc_stderr\": 0.02198603218206415,\n\ \ \"acc_norm\": 0.8202614379084967,\n \"acc_norm_stderr\": 0.02198603218206415\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.797427652733119,\n\ \ \"acc_stderr\": 0.022827317491059686,\n \"acc_norm\": 0.797427652733119,\n\ \ \"acc_norm_stderr\": 0.022827317491059686\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8333333333333334,\n \"acc_stderr\": 0.020736358408060006,\n\ \ \"acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.020736358408060006\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5531914893617021,\n \"acc_stderr\": 0.029658235097666907,\n \ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.029658235097666907\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5443285528031291,\n\ \ \"acc_stderr\": 0.012719949543032228,\n \"acc_norm\": 0.5443285528031291,\n\ \ \"acc_norm_stderr\": 0.012719949543032228\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7941176470588235,\n \"acc_stderr\": 0.02456220431414231,\n\ \ \"acc_norm\": 0.7941176470588235,\n \"acc_norm_stderr\": 0.02456220431414231\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7647058823529411,\n \"acc_stderr\": 0.01716058723504635,\n \ \ \"acc_norm\": 0.7647058823529411,\n \"acc_norm_stderr\": 0.01716058723504635\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7090909090909091,\n\ \ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.7090909090909091,\n\ \ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7714285714285715,\n \"acc_stderr\": 0.02688214492230774,\n\ \ \"acc_norm\": 0.7714285714285715,\n \"acc_norm_stderr\": 0.02688214492230774\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.02207632610182466,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.02207632610182466\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5060240963855421,\n\ \ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.5060240963855421,\n\ \ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.02517298435015577,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.02517298435015577\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.5006119951040392,\n\ \ \"mc1_stderr\": 0.01750348793889251,\n \"mc2\": 0.649788114114722,\n\ \ \"mc2_stderr\": 0.015119260704075871\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8105761641673244,\n \"acc_stderr\": 0.011012790432989247\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6110689916603488,\n \ \ \"acc_stderr\": 0.01342838248127424\n }\n}\n```" repo_url: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|arc:challenge\|25_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-05T04-20-22.140239.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|gsm8k\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hellaswag\|10_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-05T04-20-22.140239.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-05T04-20-22.140239.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '/details_harness\|winogrande\|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-05T04-20-22.140239.parquet' - config_name: results data_files: - split: 2024_01_05T04_20_22.140239 path: - results_2024-01-05T04-20-22.140239.parquet - split: latest path: - results_2024-01-05T04-20-22.140239.parquet --- # Dataset Card for Evaluation run of mistralai/Mixtral-8x7B-Instruct-v0.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_mistralai__Mixtral-8x7B-Instruct-v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-05T04:20:22.140239](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1/blob/main/results_2024-01-05T04-20-22.140239.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": 0.7126033327488117, "acc_stderr": 0.030215739102142546, "acc_norm": 0.7164863994184663, "acc_norm_stderr": 0.030796061622697008, "mc1": 0.5006119951040392, "mc1_stderr": 0.01750348793889251, "mc2": 0.649788114114722, "mc2_stderr": 0.015119260704075871 }, "harness\|arc:challenge\|25": { "acc": 0.6655290102389079, "acc_stderr": 0.013787460322441377, "acc_norm": 0.7013651877133106, "acc_norm_stderr": 0.013374078615068738 }, "harness\|hellaswag\|10": { "acc": 0.6858195578570006, "acc_stderr": 0.004632399677490809, "acc_norm": 0.8755228042222665, "acc_norm_stderr": 0.003294504807555227 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.04072314811876837, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.04072314811876837 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7894736842105263, "acc_stderr": 0.03317672787533157, "acc_norm": 0.7894736842105263, "acc_norm_stderr": 0.03317672787533157 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7773584905660378, "acc_stderr": 0.025604233470899098, "acc_norm": 0.7773584905660378, "acc_norm_stderr": 0.025604233470899098 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8263888888888888, "acc_stderr": 0.03167473383795718, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.03167473383795718 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.7572254335260116, "acc_stderr": 0.0326926380614177, "acc_norm": 0.7572254335260116, "acc_norm_stderr": 0.0326926380614177 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6680851063829787, "acc_stderr": 0.03078373675774564, "acc_norm": 0.6680851063829787, "acc_norm_stderr": 0.03078373675774564 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.6140350877192983, "acc_stderr": 0.04579639422070434, "acc_norm": 0.6140350877192983, "acc_norm_stderr": 0.04579639422070434 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6482758620689655, "acc_stderr": 0.0397923663749741, "acc_norm": 0.6482758620689655, "acc_norm_stderr": 0.0397923663749741 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.47883597883597884, "acc_stderr": 0.025728230952130726, "acc_norm": 0.47883597883597884, "acc_norm_stderr": 0.025728230952130726 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.5238095238095238, "acc_stderr": 0.04467062628403273, "acc_norm": 0.5238095238095238, "acc_norm_stderr": 0.04467062628403273 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8516129032258064, "acc_stderr": 0.020222737554330378, "acc_norm": 0.8516129032258064, "acc_norm_stderr": 0.020222737554330378 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.6206896551724138, "acc_stderr": 0.034139638059062345, "acc_norm": 0.6206896551724138, "acc_norm_stderr": 0.034139638059062345 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.78, "acc_stderr": 0.041633319989322626, "acc_norm": 0.78, "acc_norm_stderr": 0.041633319989322626 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8, "acc_stderr": 0.03123475237772117, "acc_norm": 0.8, "acc_norm_stderr": 0.03123475237772117 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8686868686868687, "acc_stderr": 0.024063156416822523, "acc_norm": 0.8686868686868687, "acc_norm_stderr": 0.024063156416822523 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9585492227979274, "acc_stderr": 0.01438543285747646, "acc_norm": 0.9585492227979274, "acc_norm_stderr": 0.01438543285747646 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.029723278961476664, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.029723278961476664 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.8025210084033614, "acc_stderr": 0.02585916412205145, "acc_norm": 0.8025210084033614, "acc_norm_stderr": 0.02585916412205145 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.47019867549668876, "acc_stderr": 0.040752249922169775, "acc_norm": 0.47019867549668876, "acc_norm_stderr": 0.040752249922169775 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8844036697247707, "acc_stderr": 0.013708749534172636, "acc_norm": 0.8844036697247707, "acc_norm_stderr": 0.013708749534172636 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5972222222222222, "acc_stderr": 0.03344887382997866, "acc_norm": 0.5972222222222222, "acc_norm_stderr": 0.03344887382997866 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8529411764705882, "acc_stderr": 0.024857478080250447, "acc_norm": 0.8529411764705882, "acc_norm_stderr": 0.024857478080250447 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8481012658227848, "acc_stderr": 0.023363878096632446, "acc_norm": 0.8481012658227848, "acc_norm_stderr": 0.023363878096632446 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.757847533632287, "acc_stderr": 0.028751392398694755, "acc_norm": 0.757847533632287, "acc_norm_stderr": 0.028751392398694755 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8091603053435115, "acc_stderr": 0.034465133507525975, "acc_norm": 0.8091603053435115, "acc_norm_stderr": 0.034465133507525975 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8760330578512396, "acc_stderr": 0.030083098716035202, "acc_norm": 0.8760330578512396, "acc_norm_stderr": 0.030083098716035202 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8425925925925926, "acc_stderr": 0.03520703990517963, "acc_norm": 0.8425925925925926, "acc_norm_stderr": 0.03520703990517963 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.8159509202453987, "acc_stderr": 0.030446777687971716, "acc_norm": 0.8159509202453987, "acc_norm_stderr": 0.030446777687971716 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.5714285714285714, "acc_stderr": 0.04697113923010213, "acc_norm": 0.5714285714285714, "acc_norm_stderr": 0.04697113923010213 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8446601941747572, "acc_stderr": 0.035865947385739734, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.035865947385739734 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9230769230769231, "acc_stderr": 0.017456987872436193, "acc_norm": 0.9230769230769231, "acc_norm_stderr": 0.017456987872436193 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.77, "acc_stderr": 0.042295258468165065, "acc_norm": 0.77, "acc_norm_stderr": 0.042295258468165065 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.879948914431673, "acc_stderr": 0.011622736692041287, "acc_norm": 0.879948914431673, "acc_norm_stderr": 0.011622736692041287 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7803468208092486, "acc_stderr": 0.022289638852617897, "acc_norm": 0.7803468208092486, "acc_norm_stderr": 0.022289638852617897 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.46033519553072627, "acc_stderr": 0.016669799592112032, "acc_norm": 0.46033519553072627, "acc_norm_stderr": 0.016669799592112032 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.8202614379084967, "acc_stderr": 0.02198603218206415, "acc_norm": 0.8202614379084967, "acc_norm_stderr": 0.02198603218206415 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.797427652733119, "acc_stderr": 0.022827317491059686, "acc_norm": 0.797427652733119, "acc_norm_stderr": 0.022827317491059686 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.020736358408060006, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.020736358408060006 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5531914893617021, "acc_stderr": 0.029658235097666907, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.029658235097666907 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.5443285528031291, "acc_stderr": 0.012719949543032228, "acc_norm": 0.5443285528031291, "acc_norm_stderr": 0.012719949543032228 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7941176470588235, "acc_stderr": 0.02456220431414231, "acc_norm": 0.7941176470588235, "acc_norm_stderr": 0.02456220431414231 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.7647058823529411, "acc_stderr": 0.01716058723504635, "acc_norm": 0.7647058823529411, "acc_norm_stderr": 0.01716058723504635 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7090909090909091, "acc_stderr": 0.04350271442923243, "acc_norm": 0.7090909090909091, "acc_norm_stderr": 0.04350271442923243 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7714285714285715, "acc_stderr": 0.02688214492230774, "acc_norm": 0.7714285714285715, "acc_norm_stderr": 0.02688214492230774 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8905472636815921, "acc_stderr": 0.02207632610182466, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.02207632610182466 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5060240963855421, "acc_stderr": 0.03892212195333045, "acc_norm": 0.5060240963855421, "acc_norm_stderr": 0.03892212195333045 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8771929824561403, "acc_stderr": 0.02517298435015577, "acc_norm": 0.8771929824561403, "acc_norm_stderr": 0.02517298435015577 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.5006119951040392, "mc1_stderr": 0.01750348793889251, "mc2": 0.649788114114722, "mc2_stderr": 0.015119260704075871 }, "harness\|winogrande\|5": { "acc": 0.8105761641673244, "acc_stderr": 0.011012790432989247 }, "harness\|gsm8k\|5": { "acc": 0.6110689916603488, "acc_stderr": 0.01342838248127424 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address 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open-llm-leaderboard/details_01-ai__Yi-9B	--- pretty_name: Evaluation run of 01-ai/Yi-9B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [01-ai/Yi-9B](https://huggingface.co/01-ai/Yi-9B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_01-ai__Yi-9B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-07T00:53:16.402231](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-9B/blob/main/results_2024-03-07T00-53-16.402231.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\": 0.6944616852197417,\n\ \ \"acc_stderr\": 0.030657841258996534,\n \"acc_norm\": 0.7006110175468258,\n\ \ \"acc_norm_stderr\": 0.031247040652107712,\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.42448173501507824,\n\ \ \"mc2_stderr\": 0.014715889893086314\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5725255972696246,\n \"acc_stderr\": 0.01445686294465065,\n\ \ \"acc_norm\": 0.6117747440273038,\n \"acc_norm_stderr\": 0.014241614207414044\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5887273451503684,\n\ \ \"acc_stderr\": 0.004910588449330019,\n \"acc_norm\": 0.7881896036646087,\n\ \ \"acc_norm_stderr\": 0.00407756134927239\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695236\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5777777777777777,\n\ \ \"acc_stderr\": 0.042667634040995814,\n \"acc_norm\": 0.5777777777777777,\n\ \ \"acc_norm_stderr\": 0.042667634040995814\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.756578947368421,\n \"acc_stderr\": 0.034923496688842384,\n\ \ \"acc_norm\": 0.756578947368421,\n \"acc_norm_stderr\": 0.034923496688842384\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.8,\n\ \ \"acc_stderr\": 0.04020151261036844,\n \"acc_norm\": 0.8,\n \ \ \"acc_norm_stderr\": 0.04020151261036844\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7320754716981132,\n \"acc_stderr\": 0.027257260322494845,\n\ \ \"acc_norm\": 0.7320754716981132,\n \"acc_norm_stderr\": 0.027257260322494845\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8263888888888888,\n\ \ \"acc_stderr\": 0.03167473383795718,\n \"acc_norm\": 0.8263888888888888,\n\ \ \"acc_norm_stderr\": 0.03167473383795718\n },\n \"harness\|hendrycksTest-college_chemistry\|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-college_computer_science\|5\": {\n \"acc\"\ : 0.62,\n \"acc_stderr\": 0.04878317312145633,\n \"acc_norm\": 0.62,\n\ \ \"acc_norm_stderr\": 0.04878317312145633\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.7456647398843931,\n\ \ \"acc_stderr\": 0.0332055644308557,\n \"acc_norm\": 0.7456647398843931,\n\ \ \"acc_norm_stderr\": 0.0332055644308557\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4215686274509804,\n \"acc_stderr\": 0.04913595201274498,\n\ \ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.04913595201274498\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\ \ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.7191489361702128,\n \"acc_stderr\": 0.029379170464124818,\n\ \ \"acc_norm\": 0.7191489361702128,\n \"acc_norm_stderr\": 0.029379170464124818\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5263157894736842,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.5263157894736842,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.7241379310344828,\n \"acc_stderr\": 0.037245636197746325,\n\ \ \"acc_norm\": 0.7241379310344828,\n \"acc_norm_stderr\": 0.037245636197746325\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.6005291005291006,\n \"acc_stderr\": 0.02522545028406793,\n \"\ acc_norm\": 0.6005291005291006,\n \"acc_norm_stderr\": 0.02522545028406793\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.5873015873015873,\n\ \ \"acc_stderr\": 0.04403438954768177,\n \"acc_norm\": 0.5873015873015873,\n\ \ \"acc_norm_stderr\": 0.04403438954768177\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.8451612903225807,\n\ \ \"acc_stderr\": 0.020579287326583227,\n \"acc_norm\": 0.8451612903225807,\n\ \ \"acc_norm_stderr\": 0.020579287326583227\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5812807881773399,\n \"acc_stderr\": 0.034711928605184676,\n\ \ \"acc_norm\": 0.5812807881773399,\n \"acc_norm_stderr\": 0.034711928605184676\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.032250781083062896,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.032250781083062896\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8535353535353535,\n \"acc_stderr\": 0.02519092111460391,\n \"\ acc_norm\": 0.8535353535353535,\n \"acc_norm_stderr\": 0.02519092111460391\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240514,\n\ \ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240514\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.7589743589743589,\n \"acc_stderr\": 0.02168554666533319,\n \ \ \"acc_norm\": 0.7589743589743589,\n \"acc_norm_stderr\": 0.02168554666533319\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.4,\n \"acc_stderr\": 0.02986960509531691,\n \"acc_norm\"\ : 0.4,\n \"acc_norm_stderr\": 0.02986960509531691\n },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\"\ : {\n \"acc\": 0.8235294117647058,\n \"acc_stderr\": 0.024762902678057922,\n\ \ \"acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.024762902678057922\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.4105960264900662,\n \"acc_stderr\": 0.04016689594849927,\n \"\ acc_norm\": 0.4105960264900662,\n \"acc_norm_stderr\": 0.04016689594849927\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8678899082568807,\n \"acc_stderr\": 0.014517801914598238,\n \"\ acc_norm\": 0.8678899082568807,\n \"acc_norm_stderr\": 0.014517801914598238\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.6851851851851852,\n \"acc_stderr\": 0.03167468706828978,\n \"\ acc_norm\": 0.6851851851851852,\n \"acc_norm_stderr\": 0.03167468706828978\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8627450980392157,\n \"acc_stderr\": 0.024152225962801598,\n \"\ acc_norm\": 0.8627450980392157,\n \"acc_norm_stderr\": 0.024152225962801598\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579654,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579654\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7443946188340808,\n\ \ \"acc_stderr\": 0.029275891003969923,\n \"acc_norm\": 0.7443946188340808,\n\ \ \"acc_norm_stderr\": 0.029275891003969923\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8347107438016529,\n \"acc_stderr\": 0.03390780612972776,\n \"\ acc_norm\": 0.8347107438016529,\n \"acc_norm_stderr\": 0.03390780612972776\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.0335195387952127,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.0335195387952127\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5803571428571429,\n\ \ \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.5803571428571429,\n\ \ \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\ \ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9102564102564102,\n\ \ \"acc_stderr\": 0.01872430174194166,\n \"acc_norm\": 0.9102564102564102,\n\ \ \"acc_norm_stderr\": 0.01872430174194166\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8390804597701149,\n\ \ \"acc_stderr\": 0.013140225515611724,\n \"acc_norm\": 0.8390804597701149,\n\ \ \"acc_norm_stderr\": 0.013140225515611724\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071124,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071124\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4,\n\ \ \"acc_stderr\": 0.01638463841038082,\n \"acc_norm\": 0.4,\n \ \ \"acc_norm_stderr\": 0.01638463841038082\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7549019607843137,\n \"acc_stderr\": 0.024630048979824775,\n\ \ \"acc_norm\": 0.7549019607843137,\n \"acc_norm_stderr\": 0.024630048979824775\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.77491961414791,\n\ \ \"acc_stderr\": 0.023720088516179027,\n \"acc_norm\": 0.77491961414791,\n\ \ \"acc_norm_stderr\": 0.023720088516179027\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7685185185185185,\n \"acc_stderr\": 0.023468429832451163,\n\ \ \"acc_norm\": 0.7685185185185185,\n \"acc_norm_stderr\": 0.023468429832451163\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5638297872340425,\n \"acc_stderr\": 0.029583452036284066,\n \ \ \"acc_norm\": 0.5638297872340425,\n \"acc_norm_stderr\": 0.029583452036284066\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.49478487614080835,\n\ \ \"acc_stderr\": 0.012769541449652547,\n \"acc_norm\": 0.49478487614080835,\n\ \ \"acc_norm_stderr\": 0.012769541449652547\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7095588235294118,\n \"acc_stderr\": 0.02757646862274053,\n\ \ \"acc_norm\": 0.7095588235294118,\n \"acc_norm_stderr\": 0.02757646862274053\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.704248366013072,\n \"acc_stderr\": 0.01846315413263281,\n \ \ \"acc_norm\": 0.704248366013072,\n \"acc_norm_stderr\": 0.01846315413263281\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.041723430387053825,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.041723430387053825\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7591836734693878,\n \"acc_stderr\": 0.02737294220178816,\n\ \ \"acc_norm\": 0.7591836734693878,\n \"acc_norm_stderr\": 0.02737294220178816\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8606965174129353,\n\ \ \"acc_stderr\": 0.02448448716291397,\n \"acc_norm\": 0.8606965174129353,\n\ \ \"acc_norm_stderr\": 0.02448448716291397\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.028782108105401705,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.028782108105401705\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.42448173501507824,\n\ \ \"mc2_stderr\": 0.014715889893086314\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7750591949486977,\n \"acc_stderr\": 0.01173504356412674\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.489764973464746,\n \ \ \"acc_stderr\": 0.013769598923012397\n }\n}\n```" repo_url: https://huggingface.co/01-ai/Yi-9B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|arc:challenge\|25_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-07T00-53-16.402231.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|gsm8k\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hellaswag\|10_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-07T00-53-16.402231.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-07T00-53-16.402231.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '/details_harness\|winogrande\|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-07T00-53-16.402231.parquet' - config_name: results data_files: - split: 2024_03_07T00_53_16.402231 path: - results_2024-03-07T00-53-16.402231.parquet - split: latest path: - results_2024-03-07T00-53-16.402231.parquet --- # Dataset Card for Evaluation run of 01-ai/Yi-9B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [01-ai/Yi-9B](https://huggingface.co/01-ai/Yi-9B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_01-ai__Yi-9B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-07T00:53:16.402231](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-9B/blob/main/results_2024-03-07T00-53-16.402231.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": 0.6944616852197417, "acc_stderr": 0.030657841258996534, "acc_norm": 0.7006110175468258, "acc_norm_stderr": 0.031247040652107712, "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.42448173501507824, "mc2_stderr": 0.014715889893086314 }, "harness\|arc:challenge\|25": { "acc": 0.5725255972696246, "acc_stderr": 0.01445686294465065, "acc_norm": 0.6117747440273038, "acc_norm_stderr": 0.014241614207414044 }, "harness\|hellaswag\|10": { "acc": 0.5887273451503684, "acc_stderr": 0.004910588449330019, "acc_norm": 0.7881896036646087, "acc_norm_stderr": 0.00407756134927239 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5777777777777777, "acc_stderr": 0.042667634040995814, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.042667634040995814 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.756578947368421, "acc_stderr": 0.034923496688842384, "acc_norm": 0.756578947368421, "acc_norm_stderr": 0.034923496688842384 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036844, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036844 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7320754716981132, "acc_stderr": 0.027257260322494845, "acc_norm": 0.7320754716981132, "acc_norm_stderr": 0.027257260322494845 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8263888888888888, "acc_stderr": 0.03167473383795718, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.03167473383795718 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4215686274509804, "acc_stderr": 0.04913595201274498, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.04913595201274498 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.7191489361702128, "acc_stderr": 0.029379170464124818, "acc_norm": 0.7191489361702128, "acc_norm_stderr": 0.029379170464124818 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5263157894736842, "acc_stderr": 0.046970851366478626, "acc_norm": 0.5263157894736842, "acc_norm_stderr": 0.046970851366478626 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.7241379310344828, "acc_stderr": 0.037245636197746325, "acc_norm": 0.7241379310344828, "acc_norm_stderr": 0.037245636197746325 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.6005291005291006, "acc_stderr": 0.02522545028406793, "acc_norm": 0.6005291005291006, "acc_norm_stderr": 0.02522545028406793 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.5873015873015873, "acc_stderr": 0.04403438954768177, "acc_norm": 0.5873015873015873, "acc_norm_stderr": 0.04403438954768177 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8451612903225807, "acc_stderr": 0.020579287326583227, "acc_norm": 0.8451612903225807, "acc_norm_stderr": 0.020579287326583227 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5812807881773399, "acc_stderr": 0.034711928605184676, "acc_norm": 0.5812807881773399, "acc_norm_stderr": 0.034711928605184676 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7818181818181819, "acc_stderr": 0.032250781083062896, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.032250781083062896 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8535353535353535, "acc_stderr": 0.02519092111460391, "acc_norm": 0.8535353535353535, "acc_norm_stderr": 0.02519092111460391 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240514, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240514 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.7589743589743589, "acc_stderr": 0.02168554666533319, "acc_norm": 0.7589743589743589, "acc_norm_stderr": 0.02168554666533319 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.4, "acc_stderr": 0.02986960509531691, "acc_norm": 0.4, "acc_norm_stderr": 0.02986960509531691 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.8235294117647058, "acc_stderr": 0.024762902678057922, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.024762902678057922 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.4105960264900662, "acc_stderr": 0.04016689594849927, "acc_norm": 0.4105960264900662, "acc_norm_stderr": 0.04016689594849927 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8678899082568807, "acc_stderr": 0.014517801914598238, "acc_norm": 0.8678899082568807, "acc_norm_stderr": 0.014517801914598238 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.6851851851851852, "acc_stderr": 0.03167468706828978, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.03167468706828978 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8627450980392157, "acc_stderr": 0.024152225962801598, "acc_norm": 0.8627450980392157, "acc_norm_stderr": 0.024152225962801598 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579654, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579654 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7443946188340808, "acc_stderr": 0.029275891003969923, "acc_norm": 0.7443946188340808, "acc_norm_stderr": 0.029275891003969923 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8347107438016529, "acc_stderr": 0.03390780612972776, "acc_norm": 0.8347107438016529, "acc_norm_stderr": 0.03390780612972776 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7607361963190185, "acc_stderr": 0.0335195387952127, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.0335195387952127 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.5803571428571429, "acc_stderr": 0.04684099321077106, "acc_norm": 0.5803571428571429, "acc_norm_stderr": 0.04684099321077106 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8349514563106796, "acc_stderr": 0.03675668832233188, "acc_norm": 0.8349514563106796, "acc_norm_stderr": 0.03675668832233188 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9102564102564102, "acc_stderr": 0.01872430174194166, "acc_norm": 0.9102564102564102, "acc_norm_stderr": 0.01872430174194166 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8390804597701149, "acc_stderr": 0.013140225515611724, "acc_norm": 0.8390804597701149, "acc_norm_stderr": 0.013140225515611724 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071124, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071124 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4, "acc_stderr": 0.01638463841038082, "acc_norm": 0.4, "acc_norm_stderr": 0.01638463841038082 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7549019607843137, "acc_stderr": 0.024630048979824775, "acc_norm": 0.7549019607843137, "acc_norm_stderr": 0.024630048979824775 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.77491961414791, "acc_stderr": 0.023720088516179027, "acc_norm": 0.77491961414791, "acc_norm_stderr": 0.023720088516179027 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7685185185185185, "acc_stderr": 0.023468429832451163, "acc_norm": 0.7685185185185185, "acc_norm_stderr": 0.023468429832451163 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5638297872340425, "acc_stderr": 0.029583452036284066, "acc_norm": 0.5638297872340425, "acc_norm_stderr": 0.029583452036284066 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.49478487614080835, "acc_stderr": 0.012769541449652547, "acc_norm": 0.49478487614080835, "acc_norm_stderr": 0.012769541449652547 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7095588235294118, "acc_stderr": 0.02757646862274053, "acc_norm": 0.7095588235294118, "acc_norm_stderr": 0.02757646862274053 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.704248366013072, "acc_stderr": 0.01846315413263281, "acc_norm": 0.704248366013072, "acc_norm_stderr": 0.01846315413263281 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7454545454545455, "acc_stderr": 0.041723430387053825, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.041723430387053825 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7591836734693878, "acc_stderr": 0.02737294220178816, "acc_norm": 0.7591836734693878, "acc_norm_stderr": 0.02737294220178816 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8606965174129353, "acc_stderr": 0.02448448716291397, "acc_norm": 0.8606965174129353, "acc_norm_stderr": 0.02448448716291397 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8304093567251462, "acc_stderr": 0.028782108105401705, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.028782108105401705 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.42448173501507824, "mc2_stderr": 0.014715889893086314 }, "harness\|winogrande\|5": { "acc": 0.7750591949486977, "acc_stderr": 0.01173504356412674 }, "harness\|gsm8k\|5": { "acc": 0.489764973464746, "acc_stderr": 0.013769598923012397 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
mboth/kaelteErzeugen-50-undersampled	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* dataset_info: features: - name: Datatype dtype: string - name: Beschreibung dtype: string - name: Name dtype: string - name: Unit dtype: string - name: Grundfunktion dtype: string - name: ScoreGrundfunktion dtype: float64 - name: ZweiteGrundfunktion dtype: string - name: ScoreZweiteGrundfunktion dtype: float64 - name: label dtype: class_label: names: '0': Kaelteanlage '1': KaeltekreisAllgemein '2': Kaeltemaschine '3': Kaeltemengenzaehler '4': Klappe '5': Pumpe '6': RKW '7': Regler '8': Ruecklauf '9': Ventil '10': Vorlauf '11': Waermemengenzaehler - name: ScoreKomponente dtype: float64 - name: Datenpunkt dtype: string - name: ScoreDatenpunkt dtype: float64 - name: text dtype: string splits: - name: train num_bytes: 72126.24090121317 num_examples: 293 - name: test num_bytes: 18282 num_examples: 73 - name: valid num_bytes: 18282 num_examples: 73 download_size: 54220 dataset_size: 108690.24090121317 --- # Dataset Card for "kaelteErzeugen-50-undersampled" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
baptistecolle/sam-controlnet-2	--- dataset_info: features: - name: image dtype: image - name: filepath dtype: string - name: sentids list: int32 - name: filename dtype: string - name: imgid dtype: int32 - name: split dtype: string - name: sentences struct: - name: tokens list: string - name: raw dtype: string - name: imgid dtype: int32 - name: sentid dtype: int32 - name: cocoid dtype: int32 splits: - name: original num_bytes: 160172316.0 num_examples: 1000 download_size: 0 dataset_size: 160172316.0 --- # Dataset Card for "sam-controlnet-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
dura-garage/nep-spell-eval-dataset-6200	--- license: mit ---
tr416/_dataset_20231007_153958	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 762696.0 num_examples: 297 - name: test num_bytes: 7704.0 num_examples: 3 download_size: 73889 dataset_size: 770400.0 --- # Dataset Card for "_dataset_20231007_153958" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mukayese/truthful_qa-tr	--- license: apache-2.0 ---
Sleoruiz/disc_cla_primera-2	--- dataset_info: features: - name: text dtype: 'null' - name: inputs struct: - name: comision dtype: string - name: fecha_gaceta dtype: string - name: gaceta_numero dtype: string - name: name dtype: string - 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: 32328969 num_examples: 11713 download_size: 16700030 dataset_size: 32328969 --- # Dataset Card for "disc_cla_primera-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Pablao0948/Marina_Sena	--- license: openrail ---
arbml/TinyCalliFont	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 489803410.8 num_examples: 1600 - name: test num_bytes: 61689478.0 num_examples: 200 - name: validation num_bytes: 62852027.0 num_examples: 200 download_size: 617998205 dataset_size: 614344915.8 --- # Dataset Card for "TinyCalliFont" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ovior/twitter_dataset_1713002663	--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 2460067 num_examples: 7251 download_size: 1409617 dataset_size: 2460067 configs: - config_name: default data_files: - split: train path: data/train-* ---
lightblue/gpt4_conversations_multilingual	--- dataset_info: features: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: language dtype: string splits: - name: train num_bytes: 97523643.84159379 num_examples: 9217 download_size: 43657898 dataset_size: 97523643.84159379 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp	--- pretty_name: Evaluation run of RatanRohith/NeuralPizza-Valor-7B-Merge-slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [RatanRohith/NeuralPizza-Valor-7B-Merge-slerp](https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-22T23:00:14.356889](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp/blob/main/results_2024-01-22T23-00-14.356889.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\": 0.23196194129343728,\n\ \ \"acc_stderr\": 0.029934654752561563,\n \"acc_norm\": 0.2314240573187148,\n\ \ \"acc_norm_stderr\": 0.03071122006512167,\n \"mc1\": 1.0,\n \ \ \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n \"mc2_stderr\": NaN\n\ \ },\n \"harness\|arc:challenge\|25\": {\n \"acc\": 0.22696245733788395,\n\ \ \"acc_stderr\": 0.012240491536132861,\n \"acc_norm\": 0.22696245733788395,\n\ \ \"acc_norm_stderr\": 0.012240491536132861\n },\n \"harness\|hellaswag\|10\"\ : {\n \"acc\": 0.2504481179047998,\n \"acc_stderr\": 0.004323856300539177,\n\ \ \"acc_norm\": 0.2504481179047998,\n \"acc_norm_stderr\": 0.004323856300539177\n\ \ },\n \"harness\|hendrycksTest-abstract_algebra\|5\": {\n \"acc\": 0.22,\n\ \ \"acc_stderr\": 0.04163331998932268,\n \"acc_norm\": 0.22,\n \ \ \"acc_norm_stderr\": 0.04163331998932268\n },\n \"harness\|hendrycksTest-anatomy\|5\"\ : {\n \"acc\": 0.18518518518518517,\n \"acc_stderr\": 0.03355677216313142,\n\ \ \"acc_norm\": 0.18518518518518517,\n \"acc_norm_stderr\": 0.03355677216313142\n\ \ },\n \"harness\|hendrycksTest-astronomy\|5\": {\n \"acc\": 0.17763157894736842,\n\ \ \"acc_stderr\": 0.031103182383123398,\n \"acc_norm\": 0.17763157894736842,\n\ \ \"acc_norm_stderr\": 0.031103182383123398\n },\n \"harness\|hendrycksTest-business_ethics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-clinical_knowledge\|5\": {\n \"acc\": 0.21509433962264152,\n\ \ \"acc_stderr\": 0.02528839450289137,\n \"acc_norm\": 0.21509433962264152,\n\ \ \"acc_norm_stderr\": 0.02528839450289137\n },\n \"harness\|hendrycksTest-college_biology\|5\"\ : {\n \"acc\": 0.2569444444444444,\n \"acc_stderr\": 0.03653946969442099,\n\ \ \"acc_norm\": 0.2569444444444444,\n \"acc_norm_stderr\": 0.03653946969442099\n\ \ },\n \"harness\|hendrycksTest-college_chemistry\|5\": {\n \"acc\":\ \ 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.2,\n\ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\": 0.21,\n\ \ \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n \ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.20809248554913296,\n \"acc_stderr\": 0.030952890217749874,\n\ \ \"acc_norm\": 0.20809248554913296,\n \"acc_norm_stderr\": 0.030952890217749874\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.21568627450980393,\n\ \ \"acc_stderr\": 0.04092563958237654,\n \"acc_norm\": 0.21568627450980393,\n\ \ \"acc_norm_stderr\": 0.04092563958237654\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\":\ \ 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n \"\ acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\ \ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\ acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2857142857142857,\n\ \ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\ \ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \ \ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\ acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\ acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\ acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\ \ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\ \ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \ \ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\ \ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\ acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\ acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\ acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.31390134529147984,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25925925925925924,\n\ \ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\ \ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\ \ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2905982905982906,\n\ \ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\ \ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.23754789272030652,\n\ \ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\ \ \"acc_norm_stderr\": 0.015218733046150193\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\ \ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.1864951768488746,\n\ \ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\ \ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\ \ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \ \ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness\|hendrycksTest-public_relations\|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\ \ },\n \"harness\|hendrycksTest-security_studies\|5\": {\n \"acc\": 0.18775510204081633,\n\ \ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\ \ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness\|hendrycksTest-sociology\|5\"\ : {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\ \ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\ \ },\n \"harness\|hendrycksTest-us_foreign_policy\|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-virology\|5\"\ : {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\ \ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\ \ },\n \"harness\|hendrycksTest-world_religions\|5\": {\n \"acc\": 0.3216374269005848,\n\ \ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\ \ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness\|truthfulqa:mc\|0\"\ : {\n \"mc1\": 1.0,\n \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n\ \ \"mc2_stderr\": NaN\n },\n \"harness\|winogrande\|5\": {\n \"\ acc\": 0.4956590370955012,\n \"acc_stderr\": 0.014051956064076911\n },\n\ \ \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\": 0.0\n\ \ }\n}\n```" repo_url: https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|arc:challenge\|25_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-22T23-00-14.356889.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|gsm8k\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hellaswag\|10_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T23-00-14.356889.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-22T23-00-14.356889.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '/details_harness\|winogrande\|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-22T23-00-14.356889.parquet' - config_name: results data_files: - split: 2024_01_22T23_00_14.356889 path: - results_2024-01-22T23-00-14.356889.parquet - split: latest path: - results_2024-01-22T23-00-14.356889.parquet --- # Dataset Card for Evaluation run of RatanRohith/NeuralPizza-Valor-7B-Merge-slerp <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [RatanRohith/NeuralPizza-Valor-7B-Merge-slerp](https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-22T23:00:14.356889](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp/blob/main/results_2024-01-22T23-00-14.356889.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": 0.23196194129343728, "acc_stderr": 0.029934654752561563, "acc_norm": 0.2314240573187148, "acc_norm_stderr": 0.03071122006512167, "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN }, "harness\|arc:challenge\|25": { "acc": 0.22696245733788395, "acc_stderr": 0.012240491536132861, "acc_norm": 0.22696245733788395, "acc_norm_stderr": 0.012240491536132861 }, "harness\|hellaswag\|10": { "acc": 0.2504481179047998, "acc_stderr": 0.004323856300539177, "acc_norm": 0.2504481179047998, "acc_norm_stderr": 0.004323856300539177 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.18518518518518517, "acc_stderr": 0.03355677216313142, "acc_norm": 0.18518518518518517, "acc_norm_stderr": 0.03355677216313142 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.21509433962264152, "acc_stderr": 0.02528839450289137, "acc_norm": 0.21509433962264152, "acc_norm_stderr": 0.02528839450289137 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.2, "acc_stderr": 0.04020151261036845, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036845 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749874, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749874 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102973, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102973 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813365, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813365 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2413793103448276, "acc_stderr": 0.03565998174135302, "acc_norm": 0.2413793103448276, "acc_norm_stderr": 0.03565998174135302 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.20899470899470898, "acc_stderr": 0.02094048156533486, "acc_norm": 0.20899470899470898, "acc_norm_stderr": 0.02094048156533486 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.04040610178208841, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.04040610178208841 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.1774193548387097, "acc_stderr": 0.02173254068932927, "acc_norm": 0.1774193548387097, "acc_norm_stderr": 0.02173254068932927 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.15270935960591134, "acc_stderr": 0.02530890453938063, "acc_norm": 0.15270935960591134, "acc_norm_stderr": 0.02530890453938063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.17676767676767677, "acc_stderr": 0.027178752639044915, "acc_norm": 0.17676767676767677, "acc_norm_stderr": 0.027178752639044915 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860664, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860664 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.20256410256410257, "acc_stderr": 0.020377660970371372, "acc_norm": 0.20256410256410257, "acc_norm_stderr": 0.020377660970371372 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2111111111111111, "acc_stderr": 0.024882116857655075, "acc_norm": 0.2111111111111111, "acc_norm_stderr": 0.024882116857655075 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.21008403361344538, "acc_stderr": 0.026461398717471874, "acc_norm": 0.21008403361344538, "acc_norm_stderr": 0.026461398717471874 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.1986754966887417, "acc_stderr": 0.03257847384436776, "acc_norm": 0.1986754966887417, "acc_norm_stderr": 0.03257847384436776 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.1926605504587156, "acc_stderr": 0.016909276884936094, "acc_norm": 0.1926605504587156, "acc_norm_stderr": 0.016909276884936094 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.1527777777777778, "acc_stderr": 0.024536326026134224, "acc_norm": 0.1527777777777778, "acc_norm_stderr": 0.024536326026134224 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.31390134529147984, "acc_stderr": 0.031146796482972465, "acc_norm": 0.31390134529147984, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2595419847328244, "acc_stderr": 0.03844876139785271, "acc_norm": 0.2595419847328244, "acc_norm_stderr": 0.03844876139785271 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.2396694214876033, "acc_stderr": 0.03896878985070417, "acc_norm": 0.2396694214876033, "acc_norm_stderr": 0.03896878985070417 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25925925925925924, "acc_stderr": 0.042365112580946336, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.042365112580946336 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.22085889570552147, "acc_stderr": 0.032591773927421776, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.032591773927421776 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness\|hendrycksTest-management\|5": { "acc": 0.17475728155339806, "acc_stderr": 0.037601780060266224, "acc_norm": 0.17475728155339806, "acc_norm_stderr": 0.037601780060266224 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2905982905982906, "acc_stderr": 0.02974504857267404, "acc_norm": 0.2905982905982906, "acc_norm_stderr": 0.02974504857267404 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.23754789272030652, "acc_stderr": 0.015218733046150193, "acc_norm": 0.23754789272030652, "acc_norm_stderr": 0.015218733046150193 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.24855491329479767, "acc_stderr": 0.023267528432100174, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.023267528432100174 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.22549019607843138, "acc_stderr": 0.023929155517351284, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.023929155517351284 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.1864951768488746, "acc_stderr": 0.02212243977248077, "acc_norm": 0.1864951768488746, "acc_norm_stderr": 0.02212243977248077 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.21604938271604937, "acc_stderr": 0.022899162918445806, "acc_norm": 0.21604938271604937, "acc_norm_stderr": 0.022899162918445806 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.23404255319148937, "acc_stderr": 0.025257861359432417, "acc_norm": 0.23404255319148937, "acc_norm_stderr": 0.025257861359432417 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.25, "acc_stderr": 0.01751781884501444, "acc_norm": 0.25, "acc_norm_stderr": 0.01751781884501444 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03955932861795833, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03955932861795833 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370518, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370518 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness\|truthfulqa:mc\|0": { "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN }, "harness\|winogrande\|5": { "acc": 0.4956590370955012, "acc_stderr": 0.014051956064076911 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section 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open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1	--- pretty_name: Evaluation run of zyh3826/llama2-13b-ft-openllm-leaderboard-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [zyh3826/llama2-13b-ft-openllm-leaderboard-v1](https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_zyh3826__llama2-13b-ft-openllm-leaderboard-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-09T15:33:42.644192](https://huggingface.co/datasets/open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1/blob/main/results_2023-12-09T15-33-42.644192.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\": 0.6016495918139398,\n\ \ \"acc_stderr\": 0.03270798736533002,\n \"acc_norm\": 0.612894192678486,\n\ \ \"acc_norm_stderr\": 0.033541474205616734,\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.40723683293857477,\n\ \ \"mc2_stderr\": 0.01336809717170015\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.552901023890785,\n \"acc_stderr\": 0.014529380160526842,\n\ \ \"acc_norm\": 0.5964163822525598,\n \"acc_norm_stderr\": 0.01433715891426844\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6276638119896435,\n\ \ \"acc_stderr\": 0.004824393076826628,\n \"acc_norm\": 0.8314080860386377,\n\ \ \"acc_norm_stderr\": 0.0037362592995204874\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952365,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952365\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5259259259259259,\n\ \ \"acc_stderr\": 0.04313531696750575,\n \"acc_norm\": 0.5259259259259259,\n\ \ \"acc_norm_stderr\": 0.04313531696750575\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.631578947368421,\n \"acc_stderr\": 0.03925523381052932,\n\ \ \"acc_norm\": 0.631578947368421,\n \"acc_norm_stderr\": 0.03925523381052932\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.55,\n\ \ \"acc_stderr\": 0.04999999999999999,\n \"acc_norm\": 0.55,\n \ \ \"acc_norm_stderr\": 0.04999999999999999\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6377358490566037,\n \"acc_stderr\": 0.029582245128384303,\n\ \ \"acc_norm\": 0.6377358490566037,\n \"acc_norm_stderr\": 0.029582245128384303\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6944444444444444,\n\ \ \"acc_stderr\": 0.03852084696008534,\n \"acc_norm\": 0.6944444444444444,\n\ \ \"acc_norm_stderr\": 0.03852084696008534\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\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6069364161849711,\n\ \ \"acc_stderr\": 0.03724249595817731,\n \"acc_norm\": 0.6069364161849711,\n\ \ \"acc_norm_stderr\": 0.03724249595817731\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105653,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105653\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768079\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.4765957446808511,\n \"acc_stderr\": 0.03265019475033582,\n\ \ \"acc_norm\": 0.4765957446808511,\n \"acc_norm_stderr\": 0.03265019475033582\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3386243386243386,\n \"acc_stderr\": 0.024373197867983056,\n \"\ acc_norm\": 0.3386243386243386,\n \"acc_norm_stderr\": 0.024373197867983056\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.043758884927270605,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.043758884927270605\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7193548387096774,\n\ \ \"acc_stderr\": 0.02556060472102288,\n \"acc_norm\": 0.7193548387096774,\n\ \ \"acc_norm_stderr\": 0.02556060472102288\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4975369458128079,\n \"acc_stderr\": 0.03517945038691063,\n\ \ \"acc_norm\": 0.4975369458128079,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness\|hendrycksTest-high_school_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-high_school_european_history\|5\"\ : {\n \"acc\": 0.7272727272727273,\n \"acc_stderr\": 0.03477691162163659,\n\ \ \"acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.03477691162163659\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8131313131313131,\n \"acc_stderr\": 0.027772533334218957,\n \"\ acc_norm\": 0.8131313131313131,\n \"acc_norm_stderr\": 0.027772533334218957\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.025787723180723875,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.025787723180723875\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5948717948717949,\n \"acc_stderr\": 0.024890471769938145,\n\ \ \"acc_norm\": 0.5948717948717949,\n \"acc_norm_stderr\": 0.024890471769938145\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3333333333333333,\n \"acc_stderr\": 0.02874204090394849,\n \ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.02874204090394849\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6092436974789915,\n \"acc_stderr\": 0.03169380235712996,\n \ \ \"acc_norm\": 0.6092436974789915,\n \"acc_norm_stderr\": 0.03169380235712996\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"\ acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7944954128440367,\n \"acc_stderr\": 0.017324352325016015,\n \"\ acc_norm\": 0.7944954128440367,\n \"acc_norm_stderr\": 0.017324352325016015\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.49074074074074076,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.49074074074074076,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.02584501798692692,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.02584501798692692\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8016877637130801,\n \"acc_stderr\": 0.02595502084162111,\n \ \ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.02595502084162111\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6591928251121076,\n\ \ \"acc_stderr\": 0.03181149747055359,\n \"acc_norm\": 0.6591928251121076,\n\ \ \"acc_norm_stderr\": 0.03181149747055359\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.03915345408847836,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.03915345408847836\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.03826076324884866,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.03826076324884866\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7177914110429447,\n \"acc_stderr\": 0.03536117886664742,\n\ \ \"acc_norm\": 0.7177914110429447,\n \"acc_norm_stderr\": 0.03536117886664742\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\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8717948717948718,\n\ \ \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n\ \ \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8135376756066411,\n\ \ \"acc_stderr\": 0.013927751372001505,\n \"acc_norm\": 0.8135376756066411,\n\ \ \"acc_norm_stderr\": 0.013927751372001505\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6647398843930635,\n \"acc_stderr\": 0.025416003773165538,\n\ \ \"acc_norm\": 0.6647398843930635,\n \"acc_norm_stderr\": 0.025416003773165538\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.41675977653631285,\n\ \ \"acc_stderr\": 0.016489134962438954,\n \"acc_norm\": 0.41675977653631285,\n\ \ \"acc_norm_stderr\": 0.016489134962438954\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.673202614379085,\n \"acc_stderr\": 0.026857294663281413,\n\ \ \"acc_norm\": 0.673202614379085,\n \"acc_norm_stderr\": 0.026857294663281413\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6591639871382636,\n\ \ \"acc_stderr\": 0.026920841260776165,\n \"acc_norm\": 0.6591639871382636,\n\ \ \"acc_norm_stderr\": 0.026920841260776165\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7345679012345679,\n \"acc_stderr\": 0.024569223600460845,\n\ \ \"acc_norm\": 0.7345679012345679,\n \"acc_norm_stderr\": 0.024569223600460845\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.49645390070921985,\n \"acc_stderr\": 0.02982674915328092,\n \ \ \"acc_norm\": 0.49645390070921985,\n \"acc_norm_stderr\": 0.02982674915328092\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4589308996088657,\n\ \ \"acc_stderr\": 0.012727084826799798,\n \"acc_norm\": 0.4589308996088657,\n\ \ \"acc_norm_stderr\": 0.012727084826799798\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6029411764705882,\n \"acc_stderr\": 0.029722152099280065,\n\ \ \"acc_norm\": 0.6029411764705882,\n \"acc_norm_stderr\": 0.029722152099280065\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6062091503267973,\n \"acc_stderr\": 0.019766211991073063,\n \ \ \"acc_norm\": 0.6062091503267973,\n \"acc_norm_stderr\": 0.019766211991073063\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6775510204081633,\n \"acc_stderr\": 0.02992310056368391,\n\ \ \"acc_norm\": 0.6775510204081633,\n \"acc_norm_stderr\": 0.02992310056368391\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8059701492537313,\n\ \ \"acc_stderr\": 0.027962677604768907,\n \"acc_norm\": 0.8059701492537313,\n\ \ \"acc_norm_stderr\": 0.027962677604768907\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896308,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896308\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4819277108433735,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.4819277108433735,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.783625730994152,\n \"acc_stderr\": 0.031581495393387324,\n\ \ \"acc_norm\": 0.783625730994152,\n \"acc_norm_stderr\": 0.031581495393387324\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.40723683293857477,\n\ \ \"mc2_stderr\": 0.01336809717170015\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7734806629834254,\n \"acc_stderr\": 0.011764149054698329\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.013646702047005308,\n \ \ \"acc_stderr\": 0.0031957470754808027\n }\n}\n```" repo_url: https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|arc:challenge\|25_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-09T15-33-42.644192.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|gsm8k\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hellaswag\|10_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T15-33-42.644192.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-09T15-33-42.644192.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '/details_harness\|winogrande\|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-09T15-33-42.644192.parquet' - config_name: results data_files: - split: 2023_12_09T15_33_42.644192 path: - results_2023-12-09T15-33-42.644192.parquet - split: latest path: - results_2023-12-09T15-33-42.644192.parquet --- # Dataset Card for Evaluation run of zyh3826/llama2-13b-ft-openllm-leaderboard-v1 ## Dataset Description - Homepage: - Repository: https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1 - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [zyh3826/llama2-13b-ft-openllm-leaderboard-v1](https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_zyh3826__llama2-13b-ft-openllm-leaderboard-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-09T15:33:42.644192](https://huggingface.co/datasets/open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1/blob/main/results_2023-12-09T15-33-42.644192.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": 0.6016495918139398, "acc_stderr": 0.03270798736533002, "acc_norm": 0.612894192678486, "acc_norm_stderr": 0.033541474205616734, "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.40723683293857477, "mc2_stderr": 0.01336809717170015 }, "harness\|arc:challenge\|25": { "acc": 0.552901023890785, "acc_stderr": 0.014529380160526842, "acc_norm": 0.5964163822525598, "acc_norm_stderr": 0.01433715891426844 }, "harness\|hellaswag\|10": { "acc": 0.6276638119896435, "acc_stderr": 0.004824393076826628, "acc_norm": 0.8314080860386377, "acc_norm_stderr": 0.0037362592995204874 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5259259259259259, "acc_stderr": 0.04313531696750575, "acc_norm": 0.5259259259259259, "acc_norm_stderr": 0.04313531696750575 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.631578947368421, "acc_stderr": 0.03925523381052932, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.03925523381052932 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6377358490566037, "acc_stderr": 0.029582245128384303, "acc_norm": 0.6377358490566037, "acc_norm_stderr": 0.029582245128384303 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6944444444444444, "acc_stderr": 0.03852084696008534, "acc_norm": 0.6944444444444444, "acc_norm_stderr": 0.03852084696008534 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105653, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105653 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.4765957446808511, "acc_stderr": 0.03265019475033582, "acc_norm": 0.4765957446808511, "acc_norm_stderr": 0.03265019475033582 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3386243386243386, "acc_stderr": 0.024373197867983056, "acc_norm": 0.3386243386243386, "acc_norm_stderr": 0.024373197867983056 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3968253968253968, "acc_stderr": 0.043758884927270605, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.043758884927270605 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7193548387096774, "acc_stderr": 0.02556060472102288, "acc_norm": 0.7193548387096774, "acc_norm_stderr": 0.02556060472102288 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7272727272727273, "acc_stderr": 0.03477691162163659, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.03477691162163659 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8131313131313131, "acc_stderr": 0.027772533334218957, "acc_norm": 0.8131313131313131, "acc_norm_stderr": 0.027772533334218957 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8497409326424871, "acc_stderr": 0.025787723180723875, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.025787723180723875 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5948717948717949, "acc_stderr": 0.024890471769938145, "acc_norm": 0.5948717948717949, "acc_norm_stderr": 0.024890471769938145 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.02874204090394849, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.02874204090394849 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6092436974789915, "acc_stderr": 0.03169380235712996, "acc_norm": 0.6092436974789915, "acc_norm_stderr": 0.03169380235712996 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3841059602649007, "acc_stderr": 0.03971301814719197, "acc_norm": 0.3841059602649007, "acc_norm_stderr": 0.03971301814719197 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7944954128440367, "acc_stderr": 0.017324352325016015, "acc_norm": 0.7944954128440367, "acc_norm_stderr": 0.017324352325016015 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.49074074074074076, "acc_stderr": 0.034093869469927006, "acc_norm": 0.49074074074074076, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8382352941176471, "acc_stderr": 0.02584501798692692, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.02584501798692692 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8016877637130801, "acc_stderr": 0.02595502084162111, "acc_norm": 0.8016877637130801, "acc_norm_stderr": 0.02595502084162111 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6591928251121076, "acc_stderr": 0.03181149747055359, "acc_norm": 0.6591928251121076, "acc_norm_stderr": 0.03181149747055359 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7251908396946565, "acc_stderr": 0.03915345408847836, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.03915345408847836 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8055555555555556, "acc_stderr": 0.03826076324884866, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.03826076324884866 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7177914110429447, "acc_stderr": 0.03536117886664742, "acc_norm": 0.7177914110429447, "acc_norm_stderr": 0.03536117886664742 }, "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": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8717948717948718, "acc_stderr": 0.02190190511507333, "acc_norm": 0.8717948717948718, "acc_norm_stderr": 0.02190190511507333 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8135376756066411, "acc_stderr": 0.013927751372001505, "acc_norm": 0.8135376756066411, "acc_norm_stderr": 0.013927751372001505 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6647398843930635, "acc_stderr": 0.025416003773165538, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.025416003773165538 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.41675977653631285, "acc_stderr": 0.016489134962438954, "acc_norm": 0.41675977653631285, "acc_norm_stderr": 0.016489134962438954 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.673202614379085, "acc_stderr": 0.026857294663281413, "acc_norm": 0.673202614379085, "acc_norm_stderr": 0.026857294663281413 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6591639871382636, "acc_stderr": 0.026920841260776165, "acc_norm": 0.6591639871382636, "acc_norm_stderr": 0.026920841260776165 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7345679012345679, "acc_stderr": 0.024569223600460845, "acc_norm": 0.7345679012345679, "acc_norm_stderr": 0.024569223600460845 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.49645390070921985, "acc_stderr": 0.02982674915328092, "acc_norm": 0.49645390070921985, "acc_norm_stderr": 0.02982674915328092 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4589308996088657, "acc_stderr": 0.012727084826799798, "acc_norm": 0.4589308996088657, "acc_norm_stderr": 0.012727084826799798 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6029411764705882, "acc_stderr": 0.029722152099280065, "acc_norm": 0.6029411764705882, "acc_norm_stderr": 0.029722152099280065 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6062091503267973, "acc_stderr": 0.019766211991073063, "acc_norm": 0.6062091503267973, "acc_norm_stderr": 0.019766211991073063 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6775510204081633, "acc_stderr": 0.02992310056368391, "acc_norm": 0.6775510204081633, "acc_norm_stderr": 0.02992310056368391 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8059701492537313, "acc_stderr": 0.027962677604768907, "acc_norm": 0.8059701492537313, "acc_norm_stderr": 0.027962677604768907 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.87, "acc_stderr": 0.03379976689896308, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896308 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4819277108433735, "acc_stderr": 0.038899512528272166, "acc_norm": 0.4819277108433735, "acc_norm_stderr": 0.038899512528272166 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.783625730994152, "acc_stderr": 0.031581495393387324, "acc_norm": 0.783625730994152, "acc_norm_stderr": 0.031581495393387324 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.40723683293857477, "mc2_stderr": 0.01336809717170015 }, "harness\|winogrande\|5": { "acc": 0.7734806629834254, "acc_stderr": 0.011764149054698329 }, "harness\|gsm8k\|5": { "acc": 0.013646702047005308, "acc_stderr": 0.0031957470754808027 } } ``` ### 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]
Felipefloke/audiomodelo	--- license: openrail ---
Minglii/r_pv4_wiz70	--- dataset_info: features: - name: data struct: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: id dtype: string splits: - name: train num_bytes: 118128783 num_examples: 46064 download_size: 57212134 dataset_size: 118128783 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "r_pv4_wiz70" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
nyntany/REPO	--- license: openrail ---
Math47/y	--- license: openrail ---
Shularp/BDMS02_TH_AR_unchanged_with_quotation	--- dataset_info: features: - name: th dtype: string - name: ar dtype: string splits: - name: train num_bytes: 19731 num_examples: 85 download_size: 9903 dataset_size: 19731 --- # Dataset Card for "BDMS02_TH_AR_unchanged_with_quotation" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
PJMixers/coedit-reworded-deduped-multiturn-sharegpt	--- language: - en size_categories: - 1K<n<10K --- Each sample contains 1 to 32 pairs. ``` pair_lengths Minimum: 44 pair_lengths Maximum: 2573 pair_lengths Average: 1053 turn_counts Minimum: 1 turn_counts Maximum: 32 turn_counts Average: 16.5 ``` - `pair_lengths` counted using metharme tags, and mistral tokenizer - `turn_counts` counted for pairs of human/gpt
pminervini/averitec	--- dataset_info: features: - name: cached_original_claim_url dtype: string - name: speaker dtype: string - name: required_reannotation dtype: bool - name: reporting_source dtype: string - name: label dtype: string - name: claim_types sequence: string - name: fact_checking_article dtype: string - name: fact_checking_strategies sequence: string - name: claim dtype: string - name: justification dtype: string - name: location_ISO_code dtype: string - name: original_claim_url dtype: string - name: questions list: - name: answers list: - name: answer dtype: string - name: answer_type dtype: string - name: boolean_explanation dtype: string - name: cached_source_url dtype: string - name: source_medium dtype: string - name: source_url dtype: string - name: question dtype: string - name: claim_date dtype: string splits: - name: train num_bytes: 6038474 num_examples: 3068 - name: dev num_bytes: 1087211 num_examples: 500 download_size: 3363933 dataset_size: 7125685 configs: - config_name: default data_files: - split: train path: data/train-* - split: dev path: data/dev-* ---
Mihaiii/OpenHermes-2.5-1k-longest-curated	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 4176433 num_examples: 519 download_size: 1835764 dataset_size: 4176433 configs: - config_name: default data_files: - split: train path: data/train-* --- This is a dataset that was created from [HuggingFaceH4/OpenHermes-2.5-1k-longest](https://huggingface.co/datasets/HuggingFaceH4/OpenHermes-2.5-1k-longest). The purpose is to be able to use in [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) config by adding: ```yaml datasets: - path: Mihaiii/OpenHermes-2.5-1k-longest-curated type: alpaca ``` I elimininated rows that: 1) Had sys prompt (only 3 rows eliminated) 2) Contained on output a character that is repeated 10 times in a row (478 rows eliminated) So from a 1000 rows dataset, I ended up with a 519 rows dataset. See the [OpenHermes-2.5-1k-longest-curated.ipynb](https://huggingface.co/datasets/Mihaiii/OpenHermes-2.5-1k-longest-curated/blob/main/OpenHermes-2.5-1k-longest-curated.ipynb) notebook for details on how the dataset was constructed. Later edit: after a more in depth analysis on the dataset, I noticed that: 1) The imported subset is `test_sft`, but this is the 2nd chunk of top 1k records. The first one is in `train_sft` subset. 2) Valid code records that contained 10 repeated spaces for indentation were also eliminated.
CyberHarem/barbara_genshin	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of barbara/バーバラ/芭芭拉 (Genshin Impact) This is the dataset of barbara/バーバラ/芭芭拉 (Genshin Impact), containing 500 images and their tags. The core tags of this character are `twintails, blonde_hair, blue_eyes, long_hair, drill_hair, twin_drills, hat, bow, white_headwear, breasts, hair_ornament`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:-----------\|:-----------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 500 \| 1.11 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 1200 \| 500 \| 930.77 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1420 \| 1.90 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/barbara_genshin', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 5 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, bare_shoulders, long_sleeves, looking_at_viewer, simple_background, smile, solo, white_background, white_dress, white_pantyhose, ass, blush, closed_mouth, detached_sleeves, looking_back, detached_collar, open_mouth \| \| 1 \| 14 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, bare_shoulders, detached_collar, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, simple_background, smile, solo, white_dress, white_background, white_pantyhose, ;d, one_eye_closed, blush, book, frilled_dress, vision_(genshin_impact), latin_cross, strapless_dress, white_sleeves \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, :d, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, solo, white_background, white_dress, bare_shoulders, blush, book, simple_background, vision_(genshin_impact), cross \| \| 3 \| 5 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, :d, bare_shoulders, detached_collar, hair_between_eyes, long_sleeves, looking_at_viewer, open_mouth, simple_background, solo, upper_body, white_background, white_dress, detached_sleeves, blush, cross, hand_up, teeth \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, :d, bare_shoulders, blush, detached_collar, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, solo, white_dress, sidelocks, book, blurry, hair_between_eyes, cross, white_pantyhose \| \| 5 \| 6 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| 1girl, blue_one-piece_swimsuit, blue_sky, casual_one-piece_swimsuit, choker, cloud, day, detached_sleeves, long_sleeves, looking_at_viewer, official_alternate_costume, open_mouth, outdoors, sailor_hat, solo, thigh_strap, water, :d, duck, ocean, wading, bag, blue_sailor_collar, bowtie, hair_flower, blush \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| 1girl, blue_one-piece_swimsuit, blue_sky, casual_one-piece_swimsuit, covered_navel, day, detached_sleeves, duck, long_sleeves, looking_at_viewer, official_alternate_costume, open_mouth, outdoors, sailor_hat, smile, solo, ;d, bare_shoulders, blue_sailor_collar, blush, bowtie, choker, cloud, cowboy_shot, ocean, one_eye_closed, thigh_strap, water, animal_bag, hair_flower, sunlight, wading, yellow_bow \| \| 7 \| 6 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| 1girl, bare_shoulders, cleavage, detached_collar, fake_animal_ears, looking_at_viewer, playboy_bunny, rabbit_ears, simple_background, solo, strapless_leotard, white_background, blush, wrist_cuffs, bowtie, sitting, alternate_costume, closed_mouth, covered_navel, medium_breasts, pantyhose, thighs, white_leotard \| \| 8 \| 7 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| 1girl, bare_shoulders, blush, cleavage, looking_at_viewer, navel, solo, collarbone, stomach, sitting, large_breasts, medium_breasts, black_bra, black_panties, parted_lips, sidelocks, strap_slip, thighs, underwear_only, white_bra, white_panties \| \| 9 \| 7 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| 1girl, alternate_costume, long_sleeves, looking_at_viewer, open_mouth, solo, blush, bowtie, pleated_skirt, white_shirt, :d, blue_skirt, school_uniform, blue_bow, collared_shirt, thighhighs, hand_up, jacket, open_clothes, simple_background, upper_teeth_only, white_pantyhose, zettai_ryouiki \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| bare_shoulders \| long_sleeves \| looking_at_viewer \| simple_background \| smile \| solo \| white_background \| white_dress \| white_pantyhose \| ass \| blush \| closed_mouth \| detached_sleeves \| looking_back \| detached_collar \| open_mouth \| ;d \| one_eye_closed \| book \| frilled_dress \| vision_(genshin_impact) \| latin_cross \| strapless_dress \| white_sleeves \| :d \| cross \| hair_between_eyes \| upper_body \| hand_up \| teeth \| sidelocks \| blurry \| blue_one-piece_swimsuit \| blue_sky \| casual_one-piece_swimsuit \| choker \| cloud \| day \| official_alternate_costume \| outdoors \| sailor_hat \| thigh_strap \| water \| duck \| ocean \| wading \| bag \| blue_sailor_collar \| bowtie \| hair_flower \| covered_navel \| cowboy_shot \| animal_bag \| sunlight \| yellow_bow \| cleavage \| fake_animal_ears \| playboy_bunny \| rabbit_ears \| strapless_leotard \| wrist_cuffs \| sitting \| alternate_costume \| medium_breasts \| pantyhose \| thighs \| white_leotard \| navel \| collarbone \| stomach \| large_breasts \| black_bra \| black_panties \| parted_lips \| strap_slip \| underwear_only \| white_bra \| white_panties \| pleated_skirt \| white_shirt \| blue_skirt \| school_uniform \| blue_bow \| collared_shirt \| thighhighs \| jacket \| open_clothes \| upper_teeth_only \| zettai_ryouiki \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-----------------\|:---------------\|:--------------------\|:--------------------\|:--------\|:-------\|:-------------------\|:--------------\|:------------------\|:------\|:--------\|:---------------\|:-------------------\|:---------------\|:------------------\|:-------------\|:-----\|:-----------------\|:-------\|:----------------\|:--------------------------\|:--------------\|:------------------\|:----------------\|:-----\|:--------\|:--------------------\|:-------------\|:----------\|:--------\|:------------\|:---------\|:--------------------------\|:-----------\|:----------------------------\|:---------\|:--------\|:------\|:-----------------------------\|:-----------\|:-------------\|:--------------\|:--------\|:-------\|:--------\|:---------\|:------\|:---------------------\|:---------\|:--------------\|:----------------\|:--------------\|:-------------\|:-----------\|:-------------\|:-----------\|:-------------------\|:----------------\|:--------------\|:--------------------\|:--------------\|:----------\|:--------------------\|:-----------------\|:------------\|:---------\|:----------------\|:--------\|:-------------\|:----------\|:----------------\|:------------\|:----------------\|:--------------\|:-------------\|:-----------------\|:------------\|:----------------\|:----------------\|:--------------\|:-------------\|:-----------------\|:-----------\|:-----------------\|:-------------\|:---------\|:---------------\|:-------------------\|:-----------------\| \| 0 \| 5 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 14 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| X \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| X \| X \| \| X \| X \| X \| \| \| X \| \| X \| \| \| X \| \| \| X \| \| X \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 5 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| X \| X \| X \| X \| \| X \| X \| X \| \| \| X \| \| X \| \| X \| X \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| X \| X \| X \| \| \| X \| \| X \| X \| \| X \| \| X \| \| X \| X \| \| \| X \| \| \| \| \| \| X \| X \| X \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 6 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| \| X \| X \| \| \| X \| \| \| \| \| X \| \| X \| \| \| X \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| X \| X \| X \| X \| \| X \| X \| \| \| \| \| X \| \| X \| \| \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 7 \| 6 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| X \| X \| \| X \| X \| \| X \| X \| \| \| \| X \| X \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| X \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 8 \| 7 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| X \| X \| \| X \| \| \| X \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| X \| \| X \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| 9 \| 7 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| X \| \| X \| X \| X \| \| X \| \| \| X \| \| X \| \| \| \| \| X \| \| \| \| \| \| \| \| \| X \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
uetchy/thesession	--- license: odbl ---
hayden-donnelly/remilio	--- license: other license_name: viral-public-license license_link: LICENSE size_categories: - 1K<n<10K task_categories: - image-classification - unconditional-image-generation - text-to-image language: - en pretty_name: Remilio --- # Remilio [Redacted Remilio Babies](https://remilio.org/) is a collection of 10,000 neochibi pfpNFT's evolving the proven Milady Maker paradigm with the introduction of young J.I.T. energy, schizophrenic reactionary aesthetics, and digital sales terrorism. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/643ae6350e5495afdefb26e1/18r2_9iN3SmU-ME_He31N.png)
Aruno/guanaco_jp	--- license: apache-2.0 task_categories: - text-generation language: - ja pretty_name: Guanaco Japanese Prompt --- Japanese Prompt of [GuanacoDataset](https://huggingface.co/datasets/JosephusCheung/GuanacoDataset) extracted using `langdetect`.
wenzhuoliu/MOOC_Answer_Reformulation	--- dataset_info: config_name: Query_Answers features: - name: query dtype: string - name: input_docs sequence: string - name: gpt_answer dtype: string splits: - name: religion num_bytes: 162873 num_examples: 124 - name: python num_bytes: 84949 num_examples: 79 - name: history num_bytes: 50557 num_examples: 58 - name: recherche_reproductible num_bytes: 59372 num_examples: 52 download_size: 488352 dataset_size: 408308 configs: - config_name: Query_Answers data_files: - split: history path: Query_Answers/history-* - split: religion path: Query_Answers/religion-* - split: recherche_reproductible path: Query_Answers/recherche_reproductible-* - split: python path: Query_Answers/python-* ---
cogumelo22/cogumelo22	--- license: openrail ---
Arthur91284/Arthur91284	--- license: openrail ---
lilacai/lilac-dolphin	--- tags: - Lilac --- # lilac/dolphin This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/cognitivecomputations/dolphin](https://huggingface.co/datasets/cognitivecomputations/dolphin) To download the dataset to a local directory: ```bash lilac download lilacai/lilac-dolphin ``` or from python with: ```py ll.download("lilacai/lilac-dolphin") ```
pvduy/ultra-mix-7k-code	--- dataset_info: features: - name: chosen list: - name: content dtype: string - name: role dtype: string - name: rejected list: - name: content dtype: string - name: role dtype: string - name: content dtype: string - name: is_code dtype: bool splits: - name: train num_bytes: 71828083 num_examples: 8228 download_size: 33892874 dataset_size: 71828083 configs: - config_name: default data_files: - split: train path: data/train-* ---
Gabriel1322/xit	--- license: openrail ---
sohonjit/brats2023_multidomain_i2i	--- license: mit task_categories: - image-to-image language: - en tags: - medical --- ## Dataset Description - Paper: Under Review. - Point of Contact: Arijit Ghosh, arijit.ghosh@fau.de ### Dataset Summary This dataset is based on the BraTS2023 dataset and is supposed to be used for Multi-domain Image-to-Image Translation task. It takes 5 middle slices from each nifti volume of the BraTS2023 dataset after normalizing to a value of (-1,1). All of these images are `.npy` files and one can load them using the `np.load(FILEPATH).astype(np.float32)`. We provide the training and the test set which contains 6255 and 1095 files respectively for each domain. These are actually 4 domains, and are named accordingly. It is highly recommend to create a separate validation set from the training dataset for applications. We use `Pytorch` to do this. We do this by using the following command. ```python seed = 97 train_dataset, val_dataset = torch.utils.data.random_split( dataset, lengths=(0.9, 0.1), generator=torch.Generator().manual_seed(seed) ) # dataset is the dataset instance. ``` This dataset is actually part of a paper which is under peer-review currently. We hope this helps the community.
bigscience-data/roots_eu_wikibooks	--- language: eu license: cc-by-sa-3.0 extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience Ethical Charter. The charter can be found at: https://hf.co/spaces/bigscience/ethical-charter' extra_gated_fields: I have read and agree to abide by the BigScience Ethical Charter: checkbox --- ROOTS Subset: roots_eu_wikibooks # wikibooks_filtered - Dataset uid: `wikibooks_filtered` ### Description ### Homepage ### Licensing ### Speaker Locations ### Sizes - 0.0897 % of total - 0.2591 % of en - 0.0965 % of fr - 0.1691 % of es - 0.2834 % of indic-hi - 0.2172 % of pt - 0.0149 % of zh - 0.0279 % of ar - 0.1374 % of vi - 0.5025 % of id - 0.3694 % of indic-ur - 0.5744 % of eu - 0.0769 % of ca - 0.0519 % of indic-ta - 0.1470 % of indic-mr - 0.0751 % of indic-te - 0.0156 % of indic-bn - 0.0476 % of indic-ml - 0.0087 % of indic-pa ### BigScience processing steps #### Filters applied to: en - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_en - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: fr - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_fr - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: es - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_es - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: indic-hi - dedup_document - filter_remove_empty_docs - split_sentences_indic-hi - dedup_template_soft - filter_small_docs_bytes_300 #### Filters applied to: pt - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_pt - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: zh - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_zhs - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: ar - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_ar - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: vi - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_vi - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: id - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_id - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-ur - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - dedup_template_soft - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: eu - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_eu - dedup_template_soft - replace_newline_with_space #### Filters applied to: ca - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_ca - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: indic-ta - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-ta - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-mr - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-mr - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-te - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-te - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-bn - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-bn - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-ml - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-ml - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-pa - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-pa - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300
nikchar/konstantinaki_paper_test_top_5	--- dataset_info: features: - name: label dtype: string - name: claim dtype: string - name: evidence_wiki_url dtype: string - name: text dtype: string - name: retrieved_evidence sequence: string - name: retrieved_evidence_text sequence: string splits: - name: train num_bytes: 50870680 num_examples: 11073 download_size: 21296684 dataset_size: 50870680 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "konstantinaki_paper_test_top_5" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
akkang321/testlecode	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5818 num_examples: 30 download_size: 3673 dataset_size: 5818 configs: - config_name: default data_files: - split: train path: data/train-* ---
amd-nicknick/bert-base-uncased-2022_tokenized_dataset	--- dataset_info: features: - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 - name: special_tokens_mask sequence: int8 splits: - name: train num_bytes: 25352412298 num_examples: 80462898 download_size: 6782996622 dataset_size: 25352412298 configs: - config_name: default data_files: - split: train path: data/train-* ---
avaliev/drugchat	--- license: bsd-3-clause task_categories: - question-answering language: - en tags: - biology - chemistry - medical pretty_name: DrugChat Dataset size_categories: - 10K<n<100K --- This dataset is for the "DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs" paper. @article{liang2023drugchat, title={DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs}, author={Liang, Youwei and Zhang, Ruiyi and Zhang, li and Xie, Pengtao}, journal={TechRxiv}, year={2023} } There are no changes in data; only added datasets class to download the set from HF and generate split from data in .json files.
hzydashi/KatagoExceptGo	--- license: mit tags: - alphago - alphazero - board games - gomoku - katago - NNUE - Stockfish size_categories: - 100M<n<1B ---
Iftitahu/sundanese_instruct_stories	--- license: cc-by-4.0 task_categories: - translation - text-generation - text2text-generation language: - id - jv - su - en size_categories: - n<1K --- A dataset of parallel translation-based instructions for Sundanese language as a target language. </br> Materials are taken from randomly selected children stories at https://storyweaver.org.in, under CC-By-SA-4.0 license. </br> The template IDs are:</br> (1, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Inggris kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'),</br> (2, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Indonesia kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'),</br> (3, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Jawa kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'),</br></br> Data is mainly composed of three parallel language samples as prompt inputs and target completions:</br> 1. <b>en_sunda</b></br> Prompt/instruction language: <i>Sundanese</i></br> Source/input language:<i>English</i></br> Target/output language:<i>Sundanese</i></br> Size: 94 samples.</br> Prompt Template:</br> <i>inputs</i>:</br> Tarjamahkeun teks dongeng barudak di handap tina teks basa Inggris kana teks basa Sunda:\n\n{input}\n\n</br> <i>targets</i>:</br> Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output}</br> 2. <b>id_sunda</b></br> Prompt/instruction language: <i>Sundanese</i></br> Source/input language: <i>Indonesia</i></br> Target/output language:<i>Sundanese</i></br> Size: 94 samples.</br> Prompt Template:</br> <i>inputs</i>:</br> Tarjamahkeun teks dongeng barudak di handap tina teks basa Indonesia kana teks basa Sunda:\n\n{input}\n\n</br> <i>targets</i>:</br> Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output}</br> 3. <b>javanese_sunda</b></br> Prompt/instruction language: <i>Sundanese</i></br> Source/input language: <i>Javanese</i></br> Target/output language: <i>Sundanese</i></br> Size: 20 samples.</br> Prompt Template:</br> <i>inputs</i>:</br> Tarjamahkeun teks dongeng barudak di handap tina teks basa Jawa kana teks basa Sunda:\n\n{input}\n\n</br> <i>targets</i>:</br> Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output}</br> Data was originally prepared for enriching multilingual resources in Open Science AYA Project (2023).
CorpuSlave/expertise_1	--- license: cc-by-nc-sa-4.0 configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string - name: doc_id dtype: string splits: - name: train num_bytes: 8027905291 num_examples: 1379830 download_size: 3070150673 dataset_size: 8027905291 ---
tomaarsen/setfit-absa-semeval-restaurants	--- dataset_info: features: - name: text dtype: string - name: span dtype: string - name: label dtype: string - name: ordinal dtype: int64 splits: - name: train num_bytes: 490223 num_examples: 3693 - name: test num_bytes: 138187 num_examples: 1134 download_size: 193352 dataset_size: 628410 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "tomaarsen/setfit-absa-semeval-restaurants" ### Dataset Summary This dataset contains the manually annotated restaurant reviews from SemEval-2014 Task 4, in the format as understood by [SetFit](https://github.com/huggingface/setfit) ABSA. For more details, see https://aclanthology.org/S14-2004/ ### Data Instances An example of "train" looks as follows. ```json {"text": "But the staff was so horrible to us.", "span": "staff", "label": "negative", "ordinal": 0} {"text": "To be completely fair, the only redeeming factor was the food, which was above average, but couldn't make up for all the other deficiencies of Teodora.", "span": "food", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "food", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "kitchen", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "menu", "label": "neutral", "ordinal": 0} ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. - `span`: a `string` feature showing the aspect span from the text. - `label`: a `string` feature showing the polarity of the aspect span. - `ordinal`: an `int64` feature showing the n-th occurrence of the span in the text. This is useful for if the span occurs within the same text multiple times. ### Data Splits \| name \|train\|test\| \|---------\|----:\|---:\| \|tomaarsen/setfit-absa-semeval-restaurants\|3693\|1134\| ### Training ABSA models using SetFit ABSA To train using this dataset, first install the SetFit library: ```bash pip install setfit ``` And then you can use the following script as a guideline of how to train an ABSA model on this dataset: ```python from setfit import AbsaModel, AbsaTrainer, TrainingArguments from datasets import load_dataset from transformers import EarlyStoppingCallback # You can initialize a AbsaModel using one or two SentenceTransformer models, or two ABSA models model = AbsaModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2") # The training/eval dataset must have `text`, `span`, `polarity`, and `ordinal` columns dataset = load_dataset("tomaarsen/setfit-absa-semeval-restaurants") train_dataset = dataset["train"] eval_dataset = dataset["test"] args = TrainingArguments( output_dir="models", use_amp=True, batch_size=256, eval_steps=50, save_steps=50, load_best_model_at_end=True, ) trainer = AbsaTrainer( model, args=args, train_dataset=train_dataset, eval_dataset=eval_dataset, callbacks=[EarlyStoppingCallback(early_stopping_patience=5)], ) trainer.train() metrics = trainer.evaluate(eval_dataset) print(metrics) trainer.push_to_hub("tomaarsen/setfit-absa-restaurants") ``` You can then run inference like so: ```python from setfit import AbsaModel # Download from Hub and run inference model = AbsaModel.from_pretrained( "tomaarsen/setfit-absa-restaurants-aspect", "tomaarsen/setfit-absa-restaurants-polarity", ) # Run inference preds = model([ "The best pizza outside of Italy and really tasty.", "The food here is great but the service is terrible", ]) ``` ### Citation Information ```bibtex @inproceedings{pontiki-etal-2014-semeval, title = "{S}em{E}val-2014 Task 4: Aspect Based Sentiment Analysis", author = "Pontiki, Maria and Galanis, Dimitris and Pavlopoulos, John and Papageorgiou, Harris and Androutsopoulos, Ion and Manandhar, Suresh", editor = "Nakov, Preslav and Zesch, Torsten", booktitle = "Proceedings of the 8th International Workshop on Semantic Evaluation ({S}em{E}val 2014)", month = aug, year = "2014", address = "Dublin, Ireland", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/S14-2004", doi = "10.3115/v1/S14-2004", pages = "27--35", } ```
open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1	--- pretty_name: Evaluation run of mlabonne/GML-Mistral-merged-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mlabonne/GML-Mistral-merged-v1](https://huggingface.co/mlabonne/GML-Mistral-merged-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_mlabonne__GML-Mistral-merged-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T10:46:26.609299](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1/blob/main/results_2023-12-29T10-46-26.609299.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\": 0.6238015653000757,\n\ \ \"acc_stderr\": 0.03193933734157293,\n \"acc_norm\": 0.6367462570659438,\n\ \ \"acc_norm_stderr\": 0.032818108624919226,\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148125,\n \"mc2\": 0.5157810759126963,\n\ \ \"mc2_stderr\": 0.01645251270460575\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.3993174061433447,\n \"acc_stderr\": 0.0143120945579467,\n\ \ \"acc_norm\": 0.4377133105802048,\n \"acc_norm_stderr\": 0.014497573881108294\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.3623780123481378,\n\ \ \"acc_stderr\": 0.0047970481548939665,\n \"acc_norm\": 0.578868751244772,\n\ \ \"acc_norm_stderr\": 0.0049273147294335564\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047423976,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047423976\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119669,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119669\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.61,\n\ \ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7169811320754716,\n \"acc_stderr\": 0.027724236492700918,\n\ \ \"acc_norm\": 0.7169811320754716,\n \"acc_norm_stderr\": 0.027724236492700918\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7708333333333334,\n\ \ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\ \ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness\|hendrycksTest-college_chemistry\|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-college_computer_science\|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-college_mathematics\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6589595375722543,\n\ \ \"acc_stderr\": 0.03614665424180826,\n \"acc_norm\": 0.6589595375722543,\n\ \ \"acc_norm_stderr\": 0.03614665424180826\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.048786087144669955,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.048786087144669955\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n\ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.548936170212766,\n \"acc_stderr\": 0.032529096196131965,\n\ \ \"acc_norm\": 0.548936170212766,\n \"acc_norm_stderr\": 0.032529096196131965\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\": 0.5586206896551724,\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\"\ : 0.4312169312169312,\n \"acc_stderr\": 0.02550648169813821,\n \"\ acc_norm\": 0.4312169312169312,\n \"acc_norm_stderr\": 0.02550648169813821\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7774193548387097,\n\ \ \"acc_stderr\": 0.023664216671642518,\n \"acc_norm\": 0.7774193548387097,\n\ \ \"acc_norm_stderr\": 0.023664216671642518\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5172413793103449,\n \"acc_stderr\": 0.035158955511656986,\n\ \ \"acc_norm\": 0.5172413793103449,\n \"acc_norm_stderr\": 0.035158955511656986\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\ : 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\ acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9067357512953368,\n \"acc_stderr\": 0.020986854593289733,\n\ \ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.020986854593289733\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.023901157979402534,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.023901157979402534\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6512605042016807,\n \"acc_stderr\": 0.030956636328566545,\n\ \ \"acc_norm\": 0.6512605042016807,\n \"acc_norm_stderr\": 0.030956636328566545\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.33112582781456956,\n \"acc_stderr\": 0.038425817186598696,\n \"\ acc_norm\": 0.33112582781456956,\n \"acc_norm_stderr\": 0.038425817186598696\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8513761467889909,\n \"acc_stderr\": 0.015251253773660836,\n \"\ acc_norm\": 0.8513761467889909,\n \"acc_norm_stderr\": 0.015251253773660836\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.47685185185185186,\n \"acc_stderr\": 0.03406315360711507,\n \"\ acc_norm\": 0.47685185185185186,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078962,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078962\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601446,\n \ \ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601446\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159463,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159463\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8099173553719008,\n \"acc_stderr\": 0.03581796951709282,\n \"\ acc_norm\": 0.8099173553719008,\n \"acc_norm_stderr\": 0.03581796951709282\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8675213675213675,\n\ \ \"acc_stderr\": 0.02220930907316562,\n \"acc_norm\": 0.8675213675213675,\n\ \ \"acc_norm_stderr\": 0.02220930907316562\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8250319284802043,\n\ \ \"acc_stderr\": 0.01358661921990334,\n \"acc_norm\": 0.8250319284802043,\n\ \ \"acc_norm_stderr\": 0.01358661921990334\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3888268156424581,\n\ \ \"acc_stderr\": 0.01630389953079613,\n \"acc_norm\": 0.3888268156424581,\n\ \ \"acc_norm_stderr\": 0.01630389953079613\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.025829163272757482,\n\ \ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.025829163272757482\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7170418006430869,\n\ \ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\ \ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"acc\"\ : 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \"\ acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.46740547588005216,\n\ \ \"acc_stderr\": 0.01274307294265335,\n \"acc_norm\": 0.46740547588005216,\n\ \ \"acc_norm_stderr\": 0.01274307294265335\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6801470588235294,\n \"acc_stderr\": 0.02833295951403121,\n\ \ \"acc_norm\": 0.6801470588235294,\n \"acc_norm_stderr\": 0.02833295951403121\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6715686274509803,\n \"acc_stderr\": 0.018999707383162673,\n \ \ \"acc_norm\": 0.6715686274509803,\n \"acc_norm_stderr\": 0.018999707383162673\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7510204081632653,\n \"acc_stderr\": 0.027682979522960234,\n\ \ \"acc_norm\": 0.7510204081632653,\n \"acc_norm_stderr\": 0.027682979522960234\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8557213930348259,\n\ \ \"acc_stderr\": 0.024845753212306046,\n \"acc_norm\": 0.8557213930348259,\n\ \ \"acc_norm_stderr\": 0.024845753212306046\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148125,\n \"mc2\": 0.5157810759126963,\n\ \ \"mc2_stderr\": 0.01645251270460575\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7387529597474349,\n \"acc_stderr\": 0.0123469148634153\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/mlabonne/GML-Mistral-merged-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|arc:challenge\|25_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-29T10-46-26.609299.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|gsm8k\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hellaswag\|10_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T10-46-26.609299.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T10-46-26.609299.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '/details_harness\|winogrande\|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-29T10-46-26.609299.parquet' - config_name: results data_files: - split: 2023_12_29T10_46_26.609299 path: - results_2023-12-29T10-46-26.609299.parquet - split: latest path: - results_2023-12-29T10-46-26.609299.parquet --- # Dataset Card for Evaluation run of mlabonne/GML-Mistral-merged-v1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mlabonne/GML-Mistral-merged-v1](https://huggingface.co/mlabonne/GML-Mistral-merged-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_mlabonne__GML-Mistral-merged-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T10:46:26.609299](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1/blob/main/results_2023-12-29T10-46-26.609299.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": 0.6238015653000757, "acc_stderr": 0.03193933734157293, "acc_norm": 0.6367462570659438, "acc_norm_stderr": 0.032818108624919226, "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148125, "mc2": 0.5157810759126963, "mc2_stderr": 0.01645251270460575 }, "harness\|arc:challenge\|25": { "acc": 0.3993174061433447, "acc_stderr": 0.0143120945579467, "acc_norm": 0.4377133105802048, "acc_norm_stderr": 0.014497573881108294 }, "harness\|hellaswag\|10": { "acc": 0.3623780123481378, "acc_stderr": 0.0047970481548939665, "acc_norm": 0.578868751244772, "acc_norm_stderr": 0.0049273147294335564 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047423976, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047423976 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119669, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119669 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7169811320754716, "acc_stderr": 0.027724236492700918, "acc_norm": 0.7169811320754716, "acc_norm_stderr": 0.027724236492700918 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6589595375722543, "acc_stderr": 0.03614665424180826, "acc_norm": 0.6589595375722543, "acc_norm_stderr": 0.03614665424180826 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.548936170212766, "acc_stderr": 0.032529096196131965, "acc_norm": 0.548936170212766, "acc_norm_stderr": 0.032529096196131965 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4312169312169312, "acc_stderr": 0.02550648169813821, "acc_norm": 0.4312169312169312, "acc_norm_stderr": 0.02550648169813821 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7774193548387097, "acc_stderr": 0.023664216671642518, "acc_norm": 0.7774193548387097, "acc_norm_stderr": 0.023664216671642518 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5172413793103449, "acc_stderr": 0.035158955511656986, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.035158955511656986 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586815, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586815 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9067357512953368, "acc_stderr": 0.020986854593289733, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.020986854593289733 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.023901157979402534, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.023901157979402534 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340492, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340492 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6512605042016807, "acc_stderr": 0.030956636328566545, "acc_norm": 0.6512605042016807, "acc_norm_stderr": 0.030956636328566545 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.33112582781456956, "acc_stderr": 0.038425817186598696, "acc_norm": 0.33112582781456956, "acc_norm_stderr": 0.038425817186598696 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8513761467889909, "acc_stderr": 0.015251253773660836, "acc_norm": 0.8513761467889909, "acc_norm_stderr": 0.015251253773660836 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.47685185185185186, "acc_stderr": 0.03406315360711507, "acc_norm": 0.47685185185185186, "acc_norm_stderr": 0.03406315360711507 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078962, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078962 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7974683544303798, "acc_stderr": 0.026160568246601446, "acc_norm": 0.7974683544303798, "acc_norm_stderr": 0.026160568246601446 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159463, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159463 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8099173553719008, "acc_stderr": 0.03581796951709282, "acc_norm": 0.8099173553719008, "acc_norm_stderr": 0.03581796951709282 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7791411042944786, "acc_stderr": 0.03259177392742178, "acc_norm": 0.7791411042944786, "acc_norm_stderr": 0.03259177392742178 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8675213675213675, "acc_stderr": 0.02220930907316562, "acc_norm": 0.8675213675213675, "acc_norm_stderr": 0.02220930907316562 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8250319284802043, "acc_stderr": 0.01358661921990334, "acc_norm": 0.8250319284802043, "acc_norm_stderr": 0.01358661921990334 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3888268156424581, "acc_stderr": 0.01630389953079613, "acc_norm": 0.3888268156424581, "acc_norm_stderr": 0.01630389953079613 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7156862745098039, "acc_stderr": 0.025829163272757482, "acc_norm": 0.7156862745098039, "acc_norm_stderr": 0.025829163272757482 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7170418006430869, "acc_stderr": 0.02558306248998481, "acc_norm": 0.7170418006430869, "acc_norm_stderr": 0.02558306248998481 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.46740547588005216, "acc_stderr": 0.01274307294265335, "acc_norm": 0.46740547588005216, "acc_norm_stderr": 0.01274307294265335 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6801470588235294, "acc_stderr": 0.02833295951403121, "acc_norm": 0.6801470588235294, "acc_norm_stderr": 0.02833295951403121 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6715686274509803, "acc_stderr": 0.018999707383162673, "acc_norm": 0.6715686274509803, "acc_norm_stderr": 0.018999707383162673 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7510204081632653, "acc_stderr": 0.027682979522960234, "acc_norm": 0.7510204081632653, "acc_norm_stderr": 0.027682979522960234 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8557213930348259, "acc_stderr": 0.024845753212306046, "acc_norm": 0.8557213930348259, "acc_norm_stderr": 0.024845753212306046 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640044, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640044 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148125, "mc2": 0.5157810759126963, "mc2_stderr": 0.01645251270460575 }, "harness\|winogrande\|5": { "acc": 0.7387529597474349, "acc_stderr": 0.0123469148634153 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset 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It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
CyberHarem/anastasia_hoshin_rezero	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of anastasia_hoshin (Re:Zero Kara Hajimeru Isekai Seikatsu) This is the dataset of anastasia_hoshin (Re:Zero Kara Hajimeru Isekai Seikatsu), containing 56 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
wefussell/amasum-final-test	--- license: mit ---
thomasavare/waste-classification-audio-deepl	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio dtype: audio - name: speaker dtype: string - name: transcription dtype: string - name: translation dtype: string - name: Class dtype: string - name: Class_index dtype: float64 splits: - name: train num_bytes: 397554225.0 num_examples: 500 download_size: 300753479 dataset_size: 397554225.0 --- # Dataset Card for "waste-classification-audio-deepl" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
marasaki/github-issues	--- dataset_info: features: - name: url dtype: string - name: repository_url dtype: string - name: labels_url dtype: string - name: comments_url dtype: string - name: events_url dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: user struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: labels list: - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: id dtype: int64 - name: name dtype: string - name: node_id dtype: string - name: url dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: assignees list: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: milestone struct: - name: closed_at dtype: string - name: closed_issues dtype: int64 - name: created_at dtype: string - name: creator struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: description dtype: string - name: due_on dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: labels_url dtype: string - name: node_id dtype: string - name: number dtype: int64 - name: open_issues dtype: int64 - name: state dtype: string - name: title dtype: string - name: updated_at dtype: string - name: url dtype: string - name: comments sequence: string - name: created_at dtype: timestamp[ns, tz=UTC] - name: updated_at dtype: timestamp[ns, tz=UTC] - name: closed_at dtype: timestamp[ns, tz=UTC] - name: author_association dtype: string - name: active_lock_reason dtype: float64 - name: draft dtype: float64 - name: pull_request struct: - name: diff_url dtype: string - name: html_url dtype: string - name: merged_at dtype: string - name: patch_url dtype: string - name: url dtype: string - name: body dtype: string - name: reactions struct: - name: '+1' dtype: int64 - name: '-1' dtype: int64 - name: confused dtype: int64 - name: eyes dtype: int64 - name: heart dtype: int64 - name: hooray dtype: int64 - name: laugh dtype: int64 - name: rocket dtype: int64 - name: total_count dtype: int64 - name: url dtype: string - name: timeline_url dtype: string - name: performed_via_github_app dtype: float64 - name: state_reason dtype: string - name: is_pull_request dtype: bool splits: - name: train num_bytes: 17110932 num_examples: 3000 download_size: 5364770 dataset_size: 17110932 configs: - config_name: default data_files: - split: train path: data/train-* license: unknown task_categories: - text-classification - token-classification language: - en pretty_name: GitHub Issues Small size_categories: - 1K<n<10K --- # Dataset Card for "github-issues" [Hugging Face NLP Course 5章5節]https://huggingface.co/learn/nlp-course/chapter5/5?fw=pt)で作ったGitHubのイシューをスクレイピングしたデータセットです。
jlbaker361/wikiart-balanced500	--- dataset_info: features: - name: image dtype: image - name: text dtype: string - name: style dtype: string - name: name dtype: string - name: gen_style dtype: string splits: - name: train num_bytes: 457748372.7 num_examples: 12150 - name: test num_bytes: 51892420.75 num_examples: 1350 download_size: 512269037 dataset_size: 509640793.45 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
TiagoJacobs/lamma2-bigbluebutton	--- license: apache-2.0 ---
DamarJati/GreenLabel-Waste-Types	--- viewer: true task_categories: - text-classification language: - en pretty_name: GreenLabel-Waste-Types size_categories: - 10K<n<100K --- Original Datasets: https://www.kaggle.com/datasets/techsash/waste-classification-data?select=DATASET
Intuit-GenSRF/sexting-nsfw-adultconten-es	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string - name: labels sequence: string - name: processed_text sequence: string - name: text_es dtype: string splits: - name: train num_bytes: 89678 num_examples: 538 download_size: 0 dataset_size: 89678 --- # Dataset Card for "sexting-nsfw-adultconten-es" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Slapping/FlowCharts	--- license: mit ---
TREC-AToMiC/AToMiC-Images-v0.1	--- license: other dataset_info: features: - name: image_id dtype: string - name: image_url dtype: string - name: caption_reference_description sequence: string - name: caption_attribution_description sequence: string - name: caption_alt_text_description sequence: string - name: image dtype: image splits: - name: train num_bytes: 56792080050.0 num_examples: 3723512 - name: validation num_bytes: 458681067.375 num_examples: 30365 - name: test num_bytes: 316081601.5 num_examples: 20732 download_size: 57119923069 dataset_size: 57566842718.875 --- ## Licensing Information In exchange for permission to use the AToMiC database (the "Database") at TREC-AToMiC, Researcher hereby agrees to the following terms and conditions: 1. Researcher shall use the Database only for non-commercial research and educational purposes. 2. TREC-AToMiC makes no representations or warranties regarding the Database, including but not limited to warranties of non-infringement or fitness for a particular purpose. 3. Researcher accepts full responsibility for his or her use of the Database and shall defend and indemnify the TREC-AToMiC team including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Database, including but not limited to Researcher's use of any copies of copyrighted images that he or she may create from the Database. 4. Researcher may provide research associates and colleagues with access to the Database provided that they first agree to be bound by these terms and conditions. 5. TREC-AToMiC reserve the right to terminate Researcher's access to the Database at any time. 6. If Researcher is employed by a for-profit, commercial entity, Researcher's employer shall also be bound by these terms and conditions, and Researcher hereby represents that he or she is fully authorized to enter into this agreement on behalf of such employer.
mikkaelmoura/myllakarvalho1	--- license: openrail ---
CyberHarem/tilty_claret_tenseioujototensaireijounomahoukakumei	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Tilty Claret This is the dataset of Tilty Claret, containing 147 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). \| Name \| Images \| Download \| Description \| \|:------------\|---------:\|:------------------------------------\|:-------------------------------------------------------------------------\| \| raw \| 147 \| [Download](dataset-raw.zip) \| Raw data with meta information. \| \| raw-stage3 \| 288 \| [Download](dataset-raw-stage3.zip) \| 3-stage cropped raw data with meta information. \| \| 384x512 \| 147 \| [Download](dataset-384x512.zip) \| 384x512 aligned dataset. \| \| 512x512 \| 147 \| [Download](dataset-512x512.zip) \| 512x512 aligned dataset. \| \| 512x704 \| 147 \| [Download](dataset-512x704.zip) \| 512x704 aligned dataset. \| \| 640x640 \| 147 \| [Download](dataset-640x640.zip) \| 640x640 aligned dataset. \| \| 640x880 \| 147 \| [Download](dataset-640x880.zip) \| 640x880 aligned dataset. \| \| stage3-640 \| 288 \| [Download](dataset-stage3-640.zip) \| 3-stage cropped dataset with the shorter side not exceeding 640 pixels. \| \| stage3-800 \| 288 \| [Download](dataset-stage3-800.zip) \| 3-stage cropped dataset with the shorter side not exceeding 800 pixels. \| \| stage3-1200 \| 288 \| [Download](dataset-stage3-1200.zip) \| 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. \|
vilm/viet-pretrained-002	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 4502549932 num_examples: 258823 download_size: 2324002719 dataset_size: 4502549932 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "viet-pretrained-002" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_haoranxu__ALMA-7B	--- pretty_name: Evaluation run of haoranxu/ALMA-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [haoranxu/ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_haoranxu__ALMA-7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-09T14:49:25.025957](https://huggingface.co/datasets/open-llm-leaderboard/details_haoranxu__ALMA-7B/blob/main/results_2023-12-09T14-49-25.025957.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\": 0.3842750602900277,\n\ \ \"acc_stderr\": 0.0337414380010653,\n \"acc_norm\": 0.388832150301939,\n\ \ \"acc_norm_stderr\": 0.03466152745310896,\n \"mc1\": 0.2350061199510404,\n\ \ \"mc1_stderr\": 0.014843061507731613,\n \"mc2\": 0.3564384771875291,\n\ \ \"mc2_stderr\": 0.013567943486529975\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.47013651877133106,\n \"acc_stderr\": 0.0145853058400071,\n\ \ \"acc_norm\": 0.5034129692832765,\n \"acc_norm_stderr\": 0.014611050403244081\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5642302330213105,\n\ \ \"acc_stderr\": 0.004948439229523914,\n \"acc_norm\": 0.7550288787094205,\n\ \ \"acc_norm_stderr\": 0.004291911350430712\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.42962962962962964,\n\ \ \"acc_stderr\": 0.04276349494376599,\n \"acc_norm\": 0.42962962962962964,\n\ \ \"acc_norm_stderr\": 0.04276349494376599\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\": 0.44,\n\ \ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.44,\n \ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.37358490566037733,\n \"acc_stderr\": 0.02977308271331987,\n\ \ \"acc_norm\": 0.37358490566037733,\n \"acc_norm_stderr\": 0.02977308271331987\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.3541666666666667,\n\ \ \"acc_stderr\": 0.039994111357535424,\n \"acc_norm\": 0.3541666666666667,\n\ \ \"acc_norm_stderr\": 0.039994111357535424\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816506,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816506\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n\ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816508,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816508\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3468208092485549,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.3468208092485549,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.18627450980392157,\n \"acc_stderr\": 0.038739587141493524,\n\ \ \"acc_norm\": 0.18627450980392157,\n \"acc_norm_stderr\": 0.038739587141493524\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.51,\n \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.51,\n\ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.3872340425531915,\n \"acc_stderr\": 0.03184389265339525,\n\ \ \"acc_norm\": 0.3872340425531915,\n \"acc_norm_stderr\": 0.03184389265339525\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2719298245614035,\n\ \ \"acc_stderr\": 0.04185774424022056,\n \"acc_norm\": 0.2719298245614035,\n\ \ \"acc_norm_stderr\": 0.04185774424022056\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04082482904638629,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04082482904638629\n },\n\ \ \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\": 0.26455026455026454,\n\ \ \"acc_stderr\": 0.022717467897708617,\n \"acc_norm\": 0.26455026455026454,\n\ \ \"acc_norm_stderr\": 0.022717467897708617\n },\n \"harness\|hendrycksTest-formal_logic\|5\"\ : {\n \"acc\": 0.19047619047619047,\n \"acc_stderr\": 0.035122074123020514,\n\ \ \"acc_norm\": 0.19047619047619047,\n \"acc_norm_stderr\": 0.035122074123020514\n\ \ },\n \"harness\|hendrycksTest-global_facts\|5\": {\n \"acc\": 0.37,\n\ \ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.37,\n \ \ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness\|hendrycksTest-high_school_biology\|5\"\ : {\n \"acc\": 0.36129032258064514,\n \"acc_stderr\": 0.027327548447957543,\n\ \ \"acc_norm\": 0.36129032258064514,\n \"acc_norm_stderr\": 0.027327548447957543\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.33497536945812806,\n \"acc_stderr\": 0.0332085274234831,\n \"\ acc_norm\": 0.33497536945812806,\n \"acc_norm_stderr\": 0.0332085274234831\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\"\ : 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.43636363636363634,\n \"acc_stderr\": 0.03872592983524753,\n\ \ \"acc_norm\": 0.43636363636363634,\n \"acc_norm_stderr\": 0.03872592983524753\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.398989898989899,\n \"acc_stderr\": 0.03488901616852731,\n \"acc_norm\"\ : 0.398989898989899,\n \"acc_norm_stderr\": 0.03488901616852731\n },\n\ \ \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n \ \ \"acc\": 0.48186528497409326,\n \"acc_stderr\": 0.036060650018329185,\n\ \ \"acc_norm\": 0.48186528497409326,\n \"acc_norm_stderr\": 0.036060650018329185\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.34615384615384615,\n \"acc_stderr\": 0.024121125416941187,\n\ \ \"acc_norm\": 0.34615384615384615,\n \"acc_norm_stderr\": 0.024121125416941187\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2777777777777778,\n \"acc_stderr\": 0.027309140588230186,\n \ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.027309140588230186\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.31512605042016806,\n \"acc_stderr\": 0.03017680828897434,\n\ \ \"acc_norm\": 0.31512605042016806,\n \"acc_norm_stderr\": 0.03017680828897434\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2582781456953642,\n \"acc_stderr\": 0.035737053147634576,\n \"\ acc_norm\": 0.2582781456953642,\n \"acc_norm_stderr\": 0.035737053147634576\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.48440366972477067,\n \"acc_stderr\": 0.02142689153920805,\n \"\ acc_norm\": 0.48440366972477067,\n \"acc_norm_stderr\": 0.02142689153920805\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.20833333333333334,\n \"acc_stderr\": 0.027696910713093936,\n \"\ acc_norm\": 0.20833333333333334,\n \"acc_norm_stderr\": 0.027696910713093936\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.4362745098039216,\n \"acc_stderr\": 0.03480693138457039,\n \"\ acc_norm\": 0.4362745098039216,\n \"acc_norm_stderr\": 0.03480693138457039\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.48523206751054854,\n \"acc_stderr\": 0.032533028078777386,\n \ \ \"acc_norm\": 0.48523206751054854,\n \"acc_norm_stderr\": 0.032533028078777386\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.4798206278026906,\n\ \ \"acc_stderr\": 0.033530461674123,\n \"acc_norm\": 0.4798206278026906,\n\ \ \"acc_norm_stderr\": 0.033530461674123\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.3969465648854962,\n \"acc_stderr\": 0.04291135671009224,\n\ \ \"acc_norm\": 0.3969465648854962,\n \"acc_norm_stderr\": 0.04291135671009224\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.5702479338842975,\n \"acc_stderr\": 0.04519082021319772,\n \"\ acc_norm\": 0.5702479338842975,\n \"acc_norm_stderr\": 0.04519082021319772\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.42592592592592593,\n\ \ \"acc_stderr\": 0.0478034362693679,\n \"acc_norm\": 0.42592592592592593,\n\ \ \"acc_norm_stderr\": 0.0478034362693679\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.39263803680981596,\n \"acc_stderr\": 0.03836740907831029,\n\ \ \"acc_norm\": 0.39263803680981596,\n \"acc_norm_stderr\": 0.03836740907831029\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.32142857142857145,\n\ \ \"acc_stderr\": 0.044328040552915185,\n \"acc_norm\": 0.32142857142857145,\n\ \ \"acc_norm_stderr\": 0.044328040552915185\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.42718446601941745,\n \"acc_stderr\": 0.04897957737781168,\n\ \ \"acc_norm\": 0.42718446601941745,\n \"acc_norm_stderr\": 0.04897957737781168\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.5555555555555556,\n\ \ \"acc_stderr\": 0.03255326307272486,\n \"acc_norm\": 0.5555555555555556,\n\ \ \"acc_norm_stderr\": 0.03255326307272486\n },\n \"harness\|hendrycksTest-medical_genetics\|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-miscellaneous\|5\": {\n \"acc\": 0.5197956577266922,\n\ \ \"acc_stderr\": 0.017865944827291626,\n \"acc_norm\": 0.5197956577266922,\n\ \ \"acc_norm_stderr\": 0.017865944827291626\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.41040462427745666,\n \"acc_stderr\": 0.02648339204209818,\n\ \ \"acc_norm\": 0.41040462427745666,\n \"acc_norm_stderr\": 0.02648339204209818\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.38562091503267976,\n \"acc_stderr\": 0.027870745278290313,\n\ \ \"acc_norm\": 0.38562091503267976,\n \"acc_norm_stderr\": 0.027870745278290313\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.5080385852090032,\n\ \ \"acc_stderr\": 0.02839442137098453,\n \"acc_norm\": 0.5080385852090032,\n\ \ \"acc_norm_stderr\": 0.02839442137098453\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.44753086419753085,\n \"acc_stderr\": 0.027667138569422704,\n\ \ \"acc_norm\": 0.44753086419753085,\n \"acc_norm_stderr\": 0.027667138569422704\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.3723404255319149,\n \"acc_stderr\": 0.028838921471251458,\n \ \ \"acc_norm\": 0.3723404255319149,\n \"acc_norm_stderr\": 0.028838921471251458\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.29465449804432853,\n\ \ \"acc_stderr\": 0.011643576764069548,\n \"acc_norm\": 0.29465449804432853,\n\ \ \"acc_norm_stderr\": 0.011643576764069548\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4007352941176471,\n \"acc_stderr\": 0.029768263528933112,\n\ \ \"acc_norm\": 0.4007352941176471,\n \"acc_norm_stderr\": 0.029768263528933112\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.3937908496732026,\n \"acc_stderr\": 0.019766211991073056,\n \ \ \"acc_norm\": 0.3937908496732026,\n \"acc_norm_stderr\": 0.019766211991073056\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\": 0.30612244897959184,\n \"acc_stderr\": 0.02950489645459596,\n\ \ \"acc_norm\": 0.30612244897959184,\n \"acc_norm_stderr\": 0.02950489645459596\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.4527363184079602,\n\ \ \"acc_stderr\": 0.03519702717576915,\n \"acc_norm\": 0.4527363184079602,\n\ \ \"acc_norm_stderr\": 0.03519702717576915\n },\n \"harness\|hendrycksTest-us_foreign_policy\|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-virology\|5\": {\n \"acc\": 0.3313253012048193,\n\ \ \"acc_stderr\": 0.03664314777288085,\n \"acc_norm\": 0.3313253012048193,\n\ \ \"acc_norm_stderr\": 0.03664314777288085\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.5847953216374269,\n \"acc_stderr\": 0.037792759455032014,\n\ \ \"acc_norm\": 0.5847953216374269,\n \"acc_norm_stderr\": 0.037792759455032014\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2350061199510404,\n\ \ \"mc1_stderr\": 0.014843061507731613,\n \"mc2\": 0.3564384771875291,\n\ \ \"mc2_stderr\": 0.013567943486529975\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7237569060773481,\n \"acc_stderr\": 0.012566815015698157\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/haoranxu/ALMA-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|arc:challenge\|25_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-09T14-49-25.025957.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|gsm8k\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hellaswag\|10_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T14-49-25.025957.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-09T14-49-25.025957.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '/details_harness\|winogrande\|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-09T14-49-25.025957.parquet' - config_name: results data_files: - split: 2023_12_09T14_49_25.025957 path: - results_2023-12-09T14-49-25.025957.parquet - split: latest path: - results_2023-12-09T14-49-25.025957.parquet --- # Dataset Card for Evaluation run of haoranxu/ALMA-7B ## Dataset Description - Homepage: - Repository: https://huggingface.co/haoranxu/ALMA-7B - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [haoranxu/ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_haoranxu__ALMA-7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-09T14:49:25.025957](https://huggingface.co/datasets/open-llm-leaderboard/details_haoranxu__ALMA-7B/blob/main/results_2023-12-09T14-49-25.025957.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": 0.3842750602900277, "acc_stderr": 0.0337414380010653, "acc_norm": 0.388832150301939, "acc_norm_stderr": 0.03466152745310896, "mc1": 0.2350061199510404, "mc1_stderr": 0.014843061507731613, "mc2": 0.3564384771875291, "mc2_stderr": 0.013567943486529975 }, "harness\|arc:challenge\|25": { "acc": 0.47013651877133106, "acc_stderr": 0.0145853058400071, "acc_norm": 0.5034129692832765, "acc_norm_stderr": 0.014611050403244081 }, "harness\|hellaswag\|10": { "acc": 0.5642302330213105, "acc_stderr": 0.004948439229523914, "acc_norm": 0.7550288787094205, "acc_norm_stderr": 0.004291911350430712 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "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": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.37358490566037733, "acc_stderr": 0.02977308271331987, "acc_norm": 0.37358490566037733, "acc_norm_stderr": 0.02977308271331987 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.3541666666666667, "acc_stderr": 0.039994111357535424, "acc_norm": 0.3541666666666667, "acc_norm_stderr": 0.039994111357535424 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816508, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816508 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3468208092485549, "acc_stderr": 0.036291466701596636, "acc_norm": 0.3468208092485549, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3872340425531915, "acc_stderr": 0.03184389265339525, "acc_norm": 0.3872340425531915, "acc_norm_stderr": 0.03184389265339525 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4, "acc_stderr": 0.04082482904638629, "acc_norm": 0.4, "acc_norm_stderr": 0.04082482904638629 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.26455026455026454, "acc_stderr": 0.022717467897708617, "acc_norm": 0.26455026455026454, "acc_norm_stderr": 0.022717467897708617 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.19047619047619047, "acc_stderr": 0.035122074123020514, "acc_norm": 0.19047619047619047, "acc_norm_stderr": 0.035122074123020514 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.36129032258064514, "acc_stderr": 0.027327548447957543, "acc_norm": 0.36129032258064514, "acc_norm_stderr": 0.027327548447957543 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.33497536945812806, "acc_stderr": 0.0332085274234831, "acc_norm": 0.33497536945812806, "acc_norm_stderr": 0.0332085274234831 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.43636363636363634, "acc_stderr": 0.03872592983524753, "acc_norm": 0.43636363636363634, "acc_norm_stderr": 0.03872592983524753 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.398989898989899, "acc_stderr": 0.03488901616852731, "acc_norm": 0.398989898989899, "acc_norm_stderr": 0.03488901616852731 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.48186528497409326, "acc_stderr": 0.036060650018329185, "acc_norm": 0.48186528497409326, "acc_norm_stderr": 0.036060650018329185 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.34615384615384615, "acc_stderr": 0.024121125416941187, "acc_norm": 0.34615384615384615, "acc_norm_stderr": 0.024121125416941187 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.027309140588230186, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.027309140588230186 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.31512605042016806, "acc_stderr": 0.03017680828897434, "acc_norm": 0.31512605042016806, "acc_norm_stderr": 0.03017680828897434 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2582781456953642, "acc_stderr": 0.035737053147634576, "acc_norm": 0.2582781456953642, "acc_norm_stderr": 0.035737053147634576 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.48440366972477067, "acc_stderr": 0.02142689153920805, "acc_norm": 0.48440366972477067, "acc_norm_stderr": 0.02142689153920805 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.20833333333333334, "acc_stderr": 0.027696910713093936, "acc_norm": 0.20833333333333334, "acc_norm_stderr": 0.027696910713093936 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.4362745098039216, "acc_stderr": 0.03480693138457039, "acc_norm": 0.4362745098039216, "acc_norm_stderr": 0.03480693138457039 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.48523206751054854, "acc_stderr": 0.032533028078777386, "acc_norm": 0.48523206751054854, "acc_norm_stderr": 0.032533028078777386 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.4798206278026906, "acc_stderr": 0.033530461674123, "acc_norm": 0.4798206278026906, "acc_norm_stderr": 0.033530461674123 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.3969465648854962, "acc_stderr": 0.04291135671009224, "acc_norm": 0.3969465648854962, "acc_norm_stderr": 0.04291135671009224 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.5702479338842975, "acc_stderr": 0.04519082021319772, "acc_norm": 0.5702479338842975, "acc_norm_stderr": 0.04519082021319772 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.42592592592592593, "acc_stderr": 0.0478034362693679, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.0478034362693679 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.39263803680981596, "acc_stderr": 0.03836740907831029, "acc_norm": 0.39263803680981596, "acc_norm_stderr": 0.03836740907831029 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.32142857142857145, "acc_stderr": 0.044328040552915185, "acc_norm": 0.32142857142857145, "acc_norm_stderr": 0.044328040552915185 }, "harness\|hendrycksTest-management\|5": { "acc": 0.42718446601941745, "acc_stderr": 0.04897957737781168, "acc_norm": 0.42718446601941745, "acc_norm_stderr": 0.04897957737781168 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.5555555555555556, "acc_stderr": 0.03255326307272486, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.03255326307272486 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.5197956577266922, "acc_stderr": 0.017865944827291626, "acc_norm": 0.5197956577266922, "acc_norm_stderr": 0.017865944827291626 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.41040462427745666, "acc_stderr": 0.02648339204209818, "acc_norm": 0.41040462427745666, "acc_norm_stderr": 0.02648339204209818 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.38562091503267976, "acc_stderr": 0.027870745278290313, "acc_norm": 0.38562091503267976, "acc_norm_stderr": 0.027870745278290313 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.5080385852090032, "acc_stderr": 0.02839442137098453, "acc_norm": 0.5080385852090032, "acc_norm_stderr": 0.02839442137098453 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.44753086419753085, "acc_stderr": 0.027667138569422704, "acc_norm": 0.44753086419753085, "acc_norm_stderr": 0.027667138569422704 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.3723404255319149, "acc_stderr": 0.028838921471251458, "acc_norm": 0.3723404255319149, "acc_norm_stderr": 0.028838921471251458 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.29465449804432853, "acc_stderr": 0.011643576764069548, "acc_norm": 0.29465449804432853, "acc_norm_stderr": 0.011643576764069548 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4007352941176471, "acc_stderr": 0.029768263528933112, "acc_norm": 0.4007352941176471, "acc_norm_stderr": 0.029768263528933112 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.3937908496732026, "acc_stderr": 0.019766211991073056, "acc_norm": 0.3937908496732026, "acc_norm_stderr": 0.019766211991073056 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.44545454545454544, "acc_stderr": 0.047605488214603246, "acc_norm": 0.44545454545454544, "acc_norm_stderr": 0.047605488214603246 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.30612244897959184, "acc_stderr": 0.02950489645459596, "acc_norm": 0.30612244897959184, "acc_norm_stderr": 0.02950489645459596 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.4527363184079602, "acc_stderr": 0.03519702717576915, "acc_norm": 0.4527363184079602, "acc_norm_stderr": 0.03519702717576915 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.3313253012048193, "acc_stderr": 0.03664314777288085, "acc_norm": 0.3313253012048193, "acc_norm_stderr": 0.03664314777288085 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.5847953216374269, "acc_stderr": 0.037792759455032014, "acc_norm": 0.5847953216374269, "acc_norm_stderr": 0.037792759455032014 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2350061199510404, "mc1_stderr": 0.014843061507731613, "mc2": 0.3564384771875291, "mc2_stderr": 0.013567943486529975 }, "harness\|winogrande\|5": { "acc": 0.7237569060773481, "acc_stderr": 0.012566815015698157 }, "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]
AdapterOcean/python-code-instructions-18k-alpaca-standardized_unified	--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 splits: - name: train num_bytes: 11288801 num_examples: 18611 download_size: 5543097 dataset_size: 11288801 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "python-code-instructions-18k-alpaca-standardized_unified" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ppdev/medtext-llama2	--- license: cc-by-4.0 --- Original data from: https://huggingface.co/datasets/BI55/MedText I just reformat it for fine tunning in lamma2 based on this article https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html Another important point related to the data quality is the prompt template. Prompts are comprised of similar elements: system prompt (optional) to guide the model, user prompt (required) to give the instruction, additional inputs (optional) to take into consideration, and the model’s answer (required). In the case of Llama 2, the authors used the following template for the chat models: [INST] User prompt [/INST] Model answer
nsanghi/axterix-obelix	--- license: apache-2.0 task_categories: - image-to-image language: - en tags: - asterix - diffusion - dreambooth size_categories: - n<1K --- This dataset contains 10 images of asterix and Obelix cartoon characters taken from internet
cartesinus/leyzer-fedcsis-translated	--- license: cc-by-4.0 task_categories: - text-classification language: - pl tags: - natural-language-understanding size_categories: - 10K<n<100K --- # Leyzer: A Dataset for Multilingual Virtual Assistants Leyzer is a multilingual text corpus designed to study multilingual and cross-lingual natural language understanding (NLU) models and the strategies of localization of virtual assistants. It consists of 20 domains across three languages: English, Spanish and Polish, with 186 intents and a wide range of samples, ranging from 1 to 672 sentences per intent. For more stats please refer to wiki.
mstz/arhythmia	--- language: - en tags: - arrhythmia - tabular_classification - multiclass_classification - binary_classification - UCI pretty_name: Arhythmia size_categories: - n<1K task_categories: - tabular-classification configs: - arhytmia - has_arhytmia license: cc --- # Arhythmia The [Arrhythmia dataset](https://archive.ics.uci.edu/ml/datasets/Arrhythmia) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets). Does the patient have arhythmia? If so, what type? # Configurations and tasks \| Configuration \| Task \| Description \| \|-------------------\|---------------------------\|---------------------------------------------------------------\| \| arhytmia \| Multiclass classification \| What type of arhythmia does the patient have? \| \| has_arhytmia \| Binary classification \| Does the patient have arhythmia? \| # Usage ```python from datasets import load_dataset dataset = load_dataset("mstz/arhythmia", "arhythmia")["train"] ``` # Features Target feature changes according to the selected configuration and is always in last position in the dataset.
tyzhu/find_sent_before_sent_train_400_eval_40_baseline	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 3760579 num_examples: 1994 - name: validation num_bytes: 386422 num_examples: 200 download_size: 791972 dataset_size: 4147001 --- # Dataset Card for "find_sent_before_sent_train_400_eval_40_baseline" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
andstor/output	--- license: mit task_categories: - text-generation language: - en dataset_info: - config_name: gpt2-xl features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 60221138 num_examples: 22169 download_size: 66419674 dataset_size: 60221138 - config_name: EleutherAI.gpt-j-6B features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 67625587 num_examples: 20665 download_size: 73049509 dataset_size: 67625587 - config_name: NinedayWang.PolyCoder-2.7B features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 58822858 num_examples: 20342 download_size: 63717236 dataset_size: 58822858 - config_name: Salesforce.codegen-16B-multi features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 2509745 num_examples: 820 download_size: 2694784 dataset_size: 2509745 - config_name: openai.gpt-3.5-turbo-0613 features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 958178 num_examples: 820 download_size: 1067958 dataset_size: 958178 - config_name: openai.gpt-4-0613 features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 875401 num_examples: 820 - name: THUDM.humaneval_x.random num_bytes: 906274 num_examples: 820 download_size: 1995455 dataset_size: 1781675 --- # Dataset Card for Output ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://github.com/andstor/lm-output-dataset - Repository: https://github.com/andstor/lm-output-dataset - Paper: - Leaderboard: - Point of Contact: [André Storhaug](mailto:andr3.storhaug@gmail.com) ### Dataset Summary This is a dataset of various language model outputs from different datasets. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@andstor](https://github.com/andstor) for adding this dataset.
liangyupu/DoTA_dataset	--- license: mit language: - zh - en - fr - de size_categories: - 100K<n<1M --- # Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling This is the official repository for DoTA dataset (Document image machine Translation dataset of ArXiv articles in markdown format) introduced by the following paper: [*Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling (NAACL 2024 Main)](https://openreview.net/forum?id=XH2TgKlXWv) In addition to the 126K samples mentioned in the paper, we provide all 139K samples that have not been filtered. Each sample contains original English image, transcripted English mmd file and translated Chinese/French/German mmd file. Samples used in the paper are listed in a json file. Text files can be decompressed as follows: ```bash tar -xzvf zh_mmd.tar.gz -C ./ ``` Image files can be decompressed as follows: ```bash cat imgs.tar.gz. \| tar -xzvf - -C ./ ``` If you want to use our dataset, please cite as follows: ```BibTex @inproceedings{ liang2024document, title={Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling}, author={Yupu Liang and Yaping Zhang and Cong MA and Zhiyang Zhang and Yang Zhao and Lu Xiang and Chengqing Zong and Yu Zhou}, booktitle={2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics}, year={2024}, url={https://openreview.net/forum?id=XH2TgKlXWv} } ```
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-markdown-88000	--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 1113664 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
claudios/cubert_ETHPy150Open	--- license: apache-2.0 task_categories: - text-classification pretty_name: CuBERT ETH Py150 Benchmarks arxiv: 2001.00059 dataset_info: - config_name: exception_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 25423003 num_examples: 18480 - name: dev num_bytes: 2845822 num_examples: 2088 - name: test num_bytes: 14064500 num_examples: 10348 download_size: 16935273 dataset_size: 42333325 - config_name: function_docstring_datasets features: - name: function dtype: string - name: docstring dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 261700491 num_examples: 340846 - name: dev num_bytes: 28498757 num_examples: 37592 - name: test num_bytes: 141660242 num_examples: 186698 download_size: 121724722 dataset_size: 431859490 - config_name: swapped_operands_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 271097336 num_examples: 236246 - name: dev num_bytes: 29986397 num_examples: 26118 - name: test num_bytes: 148544957 num_examples: 130972 download_size: 105243573 dataset_size: 449628690 - config_name: variable_misuse_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 474283355 num_examples: 700708 - name: dev num_bytes: 50447683 num_examples: 75478 - name: test num_bytes: 251591448 num_examples: 378440 download_size: 231302039 dataset_size: 776322486 - config_name: variable_misuse_repair_datasets features: - name: function sequence: string - name: target_mask sequence: int64 - name: error_location_mask sequence: int64 - name: candidate_mask sequence: int64 - name: provenance dtype: string splits: - name: train num_bytes: 4417505142 num_examples: 700708 - name: dev num_bytes: 469436314 num_examples: 75478 - name: test num_bytes: 2331355329 num_examples: 378440 download_size: 498300512 dataset_size: 7218296785 - config_name: wrong_binary_operator_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 439948844 num_examples: 459400 - name: dev num_bytes: 47620848 num_examples: 49804 - name: test num_bytes: 239409450 num_examples: 251804 download_size: 163088211 dataset_size: 726979142 configs: - config_name: exception_datasets data_files: - split: train path: exception_datasets/train-* - split: dev path: exception_datasets/dev-* - split: test path: exception_datasets/test-* - config_name: function_docstring_datasets data_files: - split: train path: function_docstring_datasets/train-* - split: dev path: function_docstring_datasets/dev-* - split: test path: function_docstring_datasets/test-* - config_name: swapped_operands_datasets data_files: - split: train path: swapped_operands_datasets/train-* - split: dev path: swapped_operands_datasets/dev-* - split: test path: swapped_operands_datasets/test-* - config_name: variable_misuse_datasets data_files: - split: train path: variable_misuse_datasets/train-* - split: dev path: variable_misuse_datasets/dev-* - split: test path: variable_misuse_datasets/test-* - config_name: variable_misuse_repair_datasets data_files: - split: train path: variable_misuse_repair_datasets/train-* - split: dev path: variable_misuse_repair_datasets/dev-* - split: test path: variable_misuse_repair_datasets/test-* - config_name: wrong_binary_operator_datasets data_files: - split: train path: wrong_binary_operator_datasets/train-* - split: dev path: wrong_binary_operator_datasets/dev-* - split: test path: wrong_binary_operator_datasets/test-* tags: - code --- # CuBERT ETH150 Open Benchmarks This is an unofficial HuggingFace upload of the [CuBERT ETH150 Open Benchmarks](https://github.com/google-research/google-research/tree/master/cubert). This dataset was released along with [Learning and Evaluating Contextual Embedding of Source Code](https://arxiv.org/abs/2001.00059). --- ## Benchmarks and Fine-Tuned Models Here we describe the 6 Python benchmarks we created. All 6 benchmarks were derived from [ETH Py150 Open](https://github.com/google-research-datasets/eth_py150_open). All examples are stored as sharded text files. Each text line corresponds to a separate example encoded as a JSON object. For each dataset, we release separate training/validation/testing splits along the same boundaries that ETH Py150 Open splits its files to the corresponding splits. The fine-tuned models are the checkpoints of each model with the highest validation accuracy. 1. Function-docstring classification. Combinations of functions with their correct or incorrect documentation string, used to train a classifier that can tell which pairs go together. The JSON fields are: * `function`: string, the source code of a function as text * `docstring`: string, the documentation string for that function. Note that the string is unquoted. To be able to properly tokenize it with the CuBERT tokenizers, you have to wrap it in quotes first. For example, in Python, use `string_to_tokenize = f'"""{docstring}"""'`. * `label`: string, one of (“Incorrect”, “Correct”), the label of the example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function name and, for “Incorrect” examples, the function whose docstring was substituted. 1. Exception classification. Combinations of functions where one exception type has been masked, along with a label indicating the masked exception type. The JSON fields are: * `function`: string, the source code of a function as text, in which one exception type has been replaced with the special token “__HOLE__” * `label`: string, one of (`ValueError`, `KeyError`, `AttributeError`, `TypeError`, `OSError`, `IOError`, `ImportError`, `IndexError`, `DoesNotExist`, `KeyboardInterrupt`, `StopIteration`, `AssertionError`, `SystemExit`, `RuntimeError`, `HTTPError`, `UnicodeDecodeError`, `NotImplementedError`, `ValidationError`, `ObjectDoesNotExist`, `NameError`, `None`), the masked exception type. Note that `None` never occurs in the data and will be removed in a future release. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, and the fully-qualified function name. 1. Variable-misuse classification. Combinations of functions where one use of a variable may have been replaced with another variable defined in the same context, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Variable misuse”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the variable substitution that has occurred (e.g., “correct_variable” → “incorrect_variable”). 1. Swapped-operand classification. Combinations of functions where one use binary operator’s arguments have been swapped, to create a buggy example, or left undisturbed, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Swapped operands”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the operand swap has occurred (e.g., “swapped operands of `not in`”). 1. Wrong-binary-operator classification. Combinations of functions where one binary operator has been swapped with another, to create a buggy example, or left undisturbed, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Wrong binary operator”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the operator replacement has occurred (e.g., “`==`-> `!=`”). 1. Variable-misuse localization and repair. Combinations of functions where one use of a variable may have been replaced with another variable defined in the same context, along with information that can be used to localize and repair the bug, as well as the location of the bug if such a bug exists. The JSON fields are: * `function`: a list of strings, the source code of a function, tokenized with the vocabulary from item b. Note that, unlike other task datasets, this dataset gives a tokenized function, rather than the code as a single string. * `target_mask`: a list of integers (0 or 1). If the integer at some position is 1, then the token at the corresponding position of the function token list is a correct repair for the introduced bug. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask. If the example is bug-free, all integers are 0. * `error_location_mask`: a list of integers (0 or 1). If the integer at some position is 1, then there is a variable-misuse bug at the corresponding location of the tokenized function. In a bug-free example, the first integer is 1. There is exactly one integer set to 1 for all examples. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask. * `candidate_mask`: a list of integers (0 or 1). If the integer at some position is 1, then the variable starting at that position in the tokenized function is a candidate to consider when repairing a bug. Candidates are all variables defined in the function parameters or via variable declarations in the function. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask, for each candidate. * `provenance`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the buggy/repair token positions and variables (e.g., “16/18 `kwargs` → `self`”). 16 is the position of the introduced error, 18 is the location of the repair. ## Citation ```bibtex @inproceedings{cubert, author = {Aditya Kanade and Petros Maniatis and Gogul Balakrishnan and Kensen Shi}, title = {Learning and evaluating contextual embedding of source code}, booktitle = {Proceedings of the 37th International Conference on Machine Learning, {ICML} 2020, 12-18 July 2020}, series = {Proceedings of Machine Learning Research}, publisher = {{PMLR}}, year = {2020}, } ```
thbndi/Mimic4Dataset	--- tags: - medical --- # Dataset Usage ## Description The Mimic-IV dataset generate data by executing the Pipeline available on https://github.com/healthylaife/MIMIC-IV-Data-Pipeline. ## Function Signature ```python load_dataset('thbndi/Mimic4Dataset', task, mimic_path=mimic_data, config_path=config_file, encoding=encod, generate_cohort=gen_cohort, val_size=size, cache_dir=cache) ``` ## Arguments 1. `task` (string) : - Description: Specifies the task you want to perform with the dataset. - Default: "Mortality" - Note: Possible Values : 'Phenotype', 'Length of Stay', 'Readmission', 'Mortality' 2. `mimic_path` (string) : - Description: Complete path to the Mimic-IV raw data on user's machine. - Note: You need to provide the appropriate path where the Mimic-IV data is stored. The path should end with the version of mimic (eg : mimiciv/2.2). Supported version : 2.2 and 1.0 as provided by the authors of the pipeline. 3. `config_path` (string) optionnal : - Description: Path to the configuration file for the cohort generation choices (more infos in '/config/readme.md'). - Default: Configuration file provided in the 'config' folder. 4. `encoding` (string) optionnal : - Description: Data encoding option for the features. - Options: "concat", "aggreg", "tensor", "raw", "text" - Default: "concat" - Note: Choose one of the following options for data encoding: - "concat": Concatenates the one-hot encoded diagnoses, demographic data vector, and dynamic features at each measured time instant, resulting in a high-dimensional feature vector. - "aggreg": Concatenates the one-hot encoded diagnoses, demographic data vector, and dynamic features, where each item_id is replaced by the average of the measured time instants, resulting in a reduced-dimensional feature vector. - "tensor": Represents each feature as an 2D array. There are separate arrays for labels, demographic data ('DEMO'), diagnosis ('COND'), medications ('MEDS'), procedures ('PROC'), chart/lab events ('CHART/LAB'), and output events data ('OUT'). Dynamic features are represented as 2D arrays where each row contains values at a specific time instant. - "raw": Provide cohort from the pipeline without any encoding for custom data processing. - "text": Represents diagnoses as text suitable for BERT or other similar text-based models. - For 'concat' and 'aggreg' the composition of the vector is given in './data/dict/"task"/features_aggreg.csv' or './data/dict/"task"/features_concat.csv' file and in 'features_names' column of the dataset. 5. `generate_cohort` (bool) optionnal : - Description: Determines whether to generate a new cohort from Mimic-IV data. - Default: True - Note: Set it to True to generate a cohort, or False to skip cohort generation. 6. `val_size`, 'test_size' (float) optionnal : - Description: Proportion of the dataset used for validation during training. - Default: 0.1 for validation size and 0.2 for testing size. - Note: Can be set to 0. 7. `cache_dir` (string) optionnal : - Description: Directory where the processed dataset will be cached. - Note: Providing a cache directory for each encoding type can avoid errors when changing the encoding type. ## Example Usage ```python import datasets from datasets import load_dataset # Example 1: Load dataset with default settings dataset = load_dataset('thbndi/Mimic4Dataset', task="Mortality", mimic_path="/path/to/mimic_data") # Example 2: Load dataset with custom settings dataset = load_dataset('thbndi/Mimic4Dataset', task="Phenotype", mimic_path="/path/to/mimic_data", config_path="/path/to/config_file", encoding="aggreg", generate_cohort=False, val_size=0.2, cache_dir="/path/to/cache_dir") ``` Please note that the provided examples are for illustrative purposes only, and you should adjust the paths and settings based on your actual dataset and specific use case.
yuan-sf63/chenyu_mask_32	--- dataset_info: features: - name: feature dtype: string - name: target dtype: string splits: - name: train num_bytes: 4349637.991911224 num_examples: 53852 - name: validation num_bytes: 483329.00808877597 num_examples: 5984 download_size: 0 dataset_size: 4832967.0 --- # Dataset Card for "chenyu_mask_32" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
allegro/klej-nkjp-ner-en	--- license: apache-2.0 task_categories: - text-classification language: - en - pl pretty_name: NKPJ-NER translated to English size_categories: - n<1K --- All instances from the `allegro/klej-nkjp-ner` (train, val, test) translated to English with Google Translate API. Columns: - `source` - text instance in Polish. - `target` - text instance in English.
UnbiasedMoldInspectionsIN/glmra1m4-9	--- license: apache-2.0 ---
communityai/OdiaGenAI___gpt-teacher-roleplay-odia-3k	--- dataset_info: features: - name: source dtype: string - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 6893531.0 num_examples: 3146 download_size: 2480702 dataset_size: 6893531.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
ovior/twitter_dataset_1713094312	--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 2391221 num_examples: 7063 download_size: 1380144 dataset_size: 2391221 configs: - config_name: default data_files: - split: train path: data/train-* ---
Maximax67/Words-CEFR-Dataset	--- license: mit task_categories: - token-classification language: - en pretty_name: Words CEFR Dataset size_categories: - 100K<n<1M tags: - CEFR - POS - NLP - SQLite configs: - config_name: sqlite_db data_files: word_cefr_minified.db --- # Words CEFR Dataset This project focuses on analyzing and categorizing English words based on their CEFR levels (from A1 to C2). I computed CEFR levels for every valid English word and its corresponding part of speech by by considering various factors including the average levels of other parts of speech for the same word, lemma levels, stem levels, as well as lemma, stem, and word frequencies. This dataset on GitHub: https://github.com/Maximax67/Words-CEFR-Dataset ## Example of usage To perform a basic word CEFR analysis, execute the Text-Analizer.ipynb file. This notebook provides a practical demonstration of how to analyze words and determine their corresponding CEFR levels. ### Demo text (generated by ChatGPT 3.5): ``` In the heart of every forest, a hidden world thrives among the towering trees. Trees, those silent giants, are more than just passive observers of nature's drama; they are active participants in an intricate dance of life. Did you know that trees communicate with each other? It's not through words or gestures like ours, but rather through a complex network of fungi that connect their roots underground. This network, often called the "wood wide web," allows trees to share nutrients, water, and even warnings about potential threats. But trees are not just generous benefactors; they are also masters of adaptation. Take the mighty sequoias, for example, towering giants that have stood the test of time for thousands of years. These giants have evolved thick, fire-resistant bark to withstand the frequent wildfires of their native California. And speaking of longevity, did you know that some trees have been around for centuries, witnessing history unfold? The ancient bristlecone pines of the American West, for instance, can live for over 5,000 years, making them some of the oldest living organisms on Earth. So the next time you find yourself wandering through a forest, take a moment to appreciate the remarkable world of trees. They may seem like silent spectators, but their lives are full of fascinating stories waiting to be discovered. ``` ### Results: ``` NLP: 318 ms CEFR levels: 3 ms ------------------------------ Text length: 1370 Total tokens: 275 ``` ``` CEFR statistic (total words): A1: 136 A2: 37 B1: 27 B2: 11 C1: 2 C2: 7 CEFR statistic (unique words): A1: 69 A2: 34 B1: 23 B2: 11 C1: 2 C2: 7 ``` ``` Not found words: 0 ``` ``` Words with level B2 and higher: 17 mighty JJ 4.00 B2 potential JJ 4.00 B2 bristlecone NN 6.00 C2 living NN 4.00 B2 longevity NN 5.97 C2 california NNP 6.00 C2 benefactors NNS 6.00 C2 fungi NNS 5.19 C1 masters NNS 4.00 B2 observers NNS 4.00 B2 pines NNS 4.00 B2 sequoias NNS 6.00 C2 wildfires NNS 6.00 C2 underground RB 4.00 B2 withstand VB 5.12 C1 evolved VBN 4.00 B2 thrives VBZ 5.86 C2 ``` ## Data Collection Process ### Making English valid words list For this project I created a [valid English words list](https://github.com/Maximax67/English-Valid-Words). It includes word, frequency count and word stems along with their associated probabilities of being valid words. For this project I used [valid_words_sorted_by_frequency.csv](https://github.com/Maximax67/English-Valid-Words/blob/main/valid_words_sorted_by_frequency.csv) file, so all words in words table in SQLite database are sorted by frequency. ### Data Processing Steps The data processing pipeline, implemented in the Word-CEFR.ipynb notebook, involves the following steps: 1. Parsing Google 1-grams Dataset: Extracting frequency data for valid words part of speech with frequency counts more than 10,000. I used [spaCy](https://spacy.io/) for more accurate part-of-speech (POS) tagging based on the [Penn Treebank Project's list of POS tags](https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html). Additionally, I used [LemmInflect](https://github.com/bjascob/LemmInflect) for obtaining word lemmas. 2. Parsing CEFR-J Dataset: I parsed it to get CEFR level for some words based on its POS. In this step I also parsed core usage categories. 3. Calculation of Average Frequencies for each CEFR level and Interpolation. 4. Assigning CEFR Levels: Determining the CEFR level for each word's POS based on average levels of other POS for the same word, lemma levels, stem levels, as well as lemma, stem and word frequencies. 5. Database Optimization: Minimizing database size by consolidating word frequency data from 1900 to 2019 into a single total value. Additionally, calculating the average POS level from all available sources. SQLite database is now optimized and has a reduced size of 20MB. Refer to the Minify_db.ipynb file for more details. ## Possible Improvements 1. Incorporating Additional Datasets: To obtain more precise data, consider parsing the [Octanove Vocabulary profile](https://github.com/openlanguageprofiles/olp-en-cefrj/blob/master/octanove-vocabulary-profile-c1c2-1.0.csv) dataset, which provides C1 and C2 level vocabulary data. However, please note that this dataset is licensed under the [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/). Also you can parse [World level survey by Zenodo](https://zenodo.org/records/12501) dataset to further enrich the dataset. This dataset, licensed under the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/legalcode). 2. Filtering Personal Names and Geographical Entities: you can improve result accuracy by implementing mechanisms to identify and exclude personal names, countries, cities, and other such entities from displaying CEFR levels. This refinement can help ensure that the analysis focuses solely on linguistic content. ## Dataset files included 1. word_cefr_minified.db: SQLite3 database. ![Database Model](database_model.png) 2. csv/words.csv: * word_id * word * stem_word_id 3. csv/word_pos.csv: * word_pos_id * word_id * pos_tag_id * lemma_word_id * frequency_count * level 4. csv/word_categories: * word_pos_id * category_id 5. csv/pos_tags.csv: * tag_id * tag * description 6. csv/categories.csv: * category_id * category_title ## License This project is licensed under the MIT License - see the LICENSE file for details. ## Acknowledgments I would like to acknowledge the contributions of the following resources: - [Spacy](https://spacy.io/) - [CEFR-J](https://cefr-j.org/) - [LemmInflect](https://github.com/bjascob/LemmInflect) - [The Google Books Ngram Viewer (used 1-grams dataset, version 20200217)](https://books.google.com/ngrams/) - [List of pos tags form Penn Treebank Project](https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html) Also I used these resources to create my [valid English words list](https://github.com/Maximax67/English-Valid-Words): - [Word list by infochimps (archived)](https://web.archive.org/web/20131118073324/https://www.infochimps.com/datasets/word-list-350000-simple-english-words-excel-readable) - [English words github repo by dwyl](https://github.com/dwyl/english-words) - [NLTK (Natural Language Toolkit)](https://www.nltk.org/) - [WordNet](https://wordnet.princeton.edu/)
ibranze/araproje_hellaswag_en_f1	--- dataset_info: features: - name: ind dtype: int32 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string splits: - name: validation num_bytes: 149738.0 num_examples: 250 download_size: 0 dataset_size: 149738.0 configs: - config_name: default data_files: - split: validation path: data/validation-* --- # Dataset Card for "araproje_hellaswag_en_f1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
darrel999/java-file-1107	--- dataset_info: features: - name: instruction dtype: string splits: - name: train num_bytes: 5108304 num_examples: 1107 download_size: 1329459 dataset_size: 5108304 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare	--- pretty_name: Evaluation run of louisbrulenaudet/Pearl-7B-0210-dare dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [louisbrulenaudet/Pearl-7B-0210-dare](https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_louisbrulenaudet__Pearl-7B-0210-dare\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-11T16:34:01.841503](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare/blob/main/results_2024-02-11T16-34-01.841503.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\": 0.6238865006281977,\n\ \ \"acc_stderr\": 0.03273771754882751,\n \"acc_norm\": 0.6230212223075242,\n\ \ \"acc_norm_stderr\": 0.03342419316334821,\n \"mc1\": 0.5752753977968176,\n\ \ \"mc1_stderr\": 0.017304000957167477,\n \"mc2\": 0.7146460351141442,\n\ \ \"mc2_stderr\": 0.015047159780719415\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6902730375426621,\n \"acc_stderr\": 0.013512058415238361,\n\ \ \"acc_norm\": 0.7090443686006825,\n \"acc_norm_stderr\": 0.013273077865907597\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7264489145588529,\n\ \ \"acc_stderr\": 0.004448701611795089,\n \"acc_norm\": 0.8879705238000398,\n\ \ \"acc_norm_stderr\": 0.003147581209374547\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.046482319871173156\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5851851851851851,\n\ \ \"acc_stderr\": 0.04256193767901408,\n \"acc_norm\": 0.5851851851851851,\n\ \ \"acc_norm_stderr\": 0.04256193767901408\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.037385206761196686,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.037385206761196686\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.56,\n\ \ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n \ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6754716981132075,\n \"acc_stderr\": 0.028815615713432115,\n\ \ \"acc_norm\": 0.6754716981132075,\n \"acc_norm_stderr\": 0.028815615713432115\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness\|hendrycksTest-college_chemistry\|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-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\": 0.33,\n\ \ \"acc_stderr\": 0.047258156262526045,\n \"acc_norm\": 0.33,\n \ \ \"acc_norm_stderr\": 0.047258156262526045\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.5953757225433526,\n \"acc_stderr\": 0.03742461193887248,\n\ \ \"acc_norm\": 0.5953757225433526,\n \"acc_norm_stderr\": 0.03742461193887248\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\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\":\ \ 0.5531914893617021,\n \"acc_stderr\": 0.032500536843658404,\n \"\ acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.032500536843658404\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3941798941798942,\n \"acc_stderr\": 0.025167982333894143,\n \"\ acc_norm\": 0.3941798941798942,\n \"acc_norm_stderr\": 0.025167982333894143\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4126984126984127,\n\ \ \"acc_stderr\": 0.04403438954768177,\n \"acc_norm\": 0.4126984126984127,\n\ \ \"acc_norm_stderr\": 0.04403438954768177\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7161290322580646,\n\ \ \"acc_stderr\": 0.02564938106302926,\n \"acc_norm\": 0.7161290322580646,\n\ \ \"acc_norm_stderr\": 0.02564938106302926\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4729064039408867,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.4729064039408867,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252607,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479048,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479048\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.023814477086593566,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.023814477086593566\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6461538461538462,\n \"acc_stderr\": 0.024243783994062157,\n\ \ \"acc_norm\": 0.6461538461538462,\n \"acc_norm_stderr\": 0.024243783994062157\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.02840653309060846,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.02840653309060846\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6176470588235294,\n \"acc_stderr\": 0.031566630992154156,\n\ \ \"acc_norm\": 0.6176470588235294,\n \"acc_norm_stderr\": 0.031566630992154156\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8128440366972477,\n \"acc_stderr\": 0.016722684526200154,\n \"\ acc_norm\": 0.8128440366972477,\n \"acc_norm_stderr\": 0.016722684526200154\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4444444444444444,\n \"acc_stderr\": 0.03388857118502326,\n \"\ acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.03388857118502326\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.02862654791243741,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.02862654791243741\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \ \ \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.03149384670994131,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.03149384670994131\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.039153454088478354,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.039153454088478354\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.03941897526516301,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.03941897526516301\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.03512385283705048,\n\ \ \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.03512385283705048\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.047268355537191,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.047268355537191\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8504273504273504,\n\ \ \"acc_stderr\": 0.023365051491753715,\n \"acc_norm\": 0.8504273504273504,\n\ \ \"acc_norm_stderr\": 0.023365051491753715\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7969348659003831,\n\ \ \"acc_stderr\": 0.014385525076611578,\n \"acc_norm\": 0.7969348659003831,\n\ \ \"acc_norm_stderr\": 0.014385525076611578\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7109826589595376,\n \"acc_stderr\": 0.02440517393578323,\n\ \ \"acc_norm\": 0.7109826589595376,\n \"acc_norm_stderr\": 0.02440517393578323\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3564245810055866,\n\ \ \"acc_stderr\": 0.016018239710513398,\n \"acc_norm\": 0.3564245810055866,\n\ \ \"acc_norm_stderr\": 0.016018239710513398\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.026992544339297243,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.026992544339297243\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.707395498392283,\n\ \ \"acc_stderr\": 0.02583989833487798,\n \"acc_norm\": 0.707395498392283,\n\ \ \"acc_norm_stderr\": 0.02583989833487798\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6851851851851852,\n \"acc_stderr\": 0.025842248700902164,\n\ \ \"acc_norm\": 0.6851851851851852,\n \"acc_norm_stderr\": 0.025842248700902164\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.42907801418439717,\n \"acc_stderr\": 0.02952591430255856,\n \ \ \"acc_norm\": 0.42907801418439717,\n \"acc_norm_stderr\": 0.02952591430255856\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.44328552803129073,\n\ \ \"acc_stderr\": 0.012687818419599923,\n \"acc_norm\": 0.44328552803129073,\n\ \ \"acc_norm_stderr\": 0.012687818419599923\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6323529411764706,\n \"acc_stderr\": 0.02928941340940319,\n\ \ \"acc_norm\": 0.6323529411764706,\n \"acc_norm_stderr\": 0.02928941340940319\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6241830065359477,\n \"acc_stderr\": 0.01959402113657744,\n \ \ \"acc_norm\": 0.6241830065359477,\n \"acc_norm_stderr\": 0.01959402113657744\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\": 0.6938775510204082,\n \"acc_stderr\": 0.02950489645459596,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.02950489645459596\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8009950248756219,\n\ \ \"acc_stderr\": 0.028231365092758406,\n \"acc_norm\": 0.8009950248756219,\n\ \ \"acc_norm_stderr\": 0.028231365092758406\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.02878210810540171,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.02878210810540171\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.5752753977968176,\n\ \ \"mc1_stderr\": 0.017304000957167477,\n \"mc2\": 0.7146460351141442,\n\ \ \"mc2_stderr\": 0.015047159780719415\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8453038674033149,\n \"acc_stderr\": 0.010163172650433542\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6338134950720242,\n \ \ \"acc_stderr\": 0.013270100238748831\n }\n}\n```" repo_url: https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|arc:challenge\|25_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-11T16-34-01.841503.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|gsm8k\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hellaswag\|10_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T16-34-01.841503.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-11T16-34-01.841503.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '/details_harness\|winogrande\|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-11T16-34-01.841503.parquet' - config_name: results data_files: - split: 2024_02_11T16_34_01.841503 path: - results_2024-02-11T16-34-01.841503.parquet - split: latest path: - results_2024-02-11T16-34-01.841503.parquet --- # Dataset Card for Evaluation run of louisbrulenaudet/Pearl-7B-0210-dare <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [louisbrulenaudet/Pearl-7B-0210-dare](https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_louisbrulenaudet__Pearl-7B-0210-dare", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-11T16:34:01.841503](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare/blob/main/results_2024-02-11T16-34-01.841503.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": 0.6238865006281977, "acc_stderr": 0.03273771754882751, "acc_norm": 0.6230212223075242, "acc_norm_stderr": 0.03342419316334821, "mc1": 0.5752753977968176, "mc1_stderr": 0.017304000957167477, "mc2": 0.7146460351141442, "mc2_stderr": 0.015047159780719415 }, "harness\|arc:challenge\|25": { "acc": 0.6902730375426621, "acc_stderr": 0.013512058415238361, "acc_norm": 0.7090443686006825, "acc_norm_stderr": 0.013273077865907597 }, "harness\|hellaswag\|10": { "acc": 0.7264489145588529, "acc_stderr": 0.004448701611795089, "acc_norm": 0.8879705238000398, "acc_norm_stderr": 0.003147581209374547 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901408, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901408 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6973684210526315, "acc_stderr": 0.037385206761196686, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.037385206761196686 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6754716981132075, "acc_stderr": 0.028815615713432115, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.028815615713432115 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5531914893617021, "acc_stderr": 0.032500536843658404, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.032500536843658404 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3941798941798942, "acc_stderr": 0.025167982333894143, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.025167982333894143 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4126984126984127, "acc_stderr": 0.04403438954768177, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.04403438954768177 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7161290322580646, "acc_stderr": 0.02564938106302926, "acc_norm": 0.7161290322580646, "acc_norm_stderr": 0.02564938106302926 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4729064039408867, "acc_stderr": 0.03512819077876106, "acc_norm": 0.4729064039408867, "acc_norm_stderr": 0.03512819077876106 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.02962022787479048, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.02962022787479048 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8756476683937824, "acc_stderr": 0.023814477086593566, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.023814477086593566 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6461538461538462, "acc_stderr": 0.024243783994062157, "acc_norm": 0.6461538461538462, "acc_norm_stderr": 0.024243783994062157 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.31851851851851853, "acc_stderr": 0.02840653309060846, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.02840653309060846 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6176470588235294, "acc_stderr": 0.031566630992154156, "acc_norm": 0.6176470588235294, "acc_norm_stderr": 0.031566630992154156 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8128440366972477, "acc_stderr": 0.016722684526200154, "acc_norm": 0.8128440366972477, "acc_norm_stderr": 0.016722684526200154 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.03388857118502326, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.03388857118502326 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7892156862745098, "acc_stderr": 0.02862654791243741, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.02862654791243741 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7805907172995781, "acc_stderr": 0.026939106581553945, "acc_norm": 0.7805907172995781, "acc_norm_stderr": 0.026939106581553945 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.672645739910314, "acc_stderr": 0.03149384670994131, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.03149384670994131 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7251908396946565, "acc_stderr": 0.039153454088478354, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.039153454088478354 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7520661157024794, "acc_stderr": 0.03941897526516301, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.03941897526516301 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7239263803680982, "acc_stderr": 0.03512385283705048, "acc_norm": 0.7239263803680982, "acc_norm_stderr": 0.03512385283705048 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.45535714285714285, "acc_stderr": 0.047268355537191, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.047268355537191 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8504273504273504, "acc_stderr": 0.023365051491753715, "acc_norm": 0.8504273504273504, "acc_norm_stderr": 0.023365051491753715 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7969348659003831, "acc_stderr": 0.014385525076611578, "acc_norm": 0.7969348659003831, "acc_norm_stderr": 0.014385525076611578 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7109826589595376, "acc_stderr": 0.02440517393578323, "acc_norm": 0.7109826589595376, "acc_norm_stderr": 0.02440517393578323 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3564245810055866, "acc_stderr": 0.016018239710513398, "acc_norm": 0.3564245810055866, "acc_norm_stderr": 0.016018239710513398 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.026992544339297243, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.026992544339297243 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.707395498392283, "acc_stderr": 0.02583989833487798, "acc_norm": 0.707395498392283, "acc_norm_stderr": 0.02583989833487798 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6851851851851852, "acc_stderr": 0.025842248700902164, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.025842248700902164 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.42907801418439717, "acc_stderr": 0.02952591430255856, "acc_norm": 0.42907801418439717, "acc_norm_stderr": 0.02952591430255856 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.44328552803129073, "acc_stderr": 0.012687818419599923, "acc_norm": 0.44328552803129073, "acc_norm_stderr": 0.012687818419599923 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6323529411764706, "acc_stderr": 0.02928941340940319, "acc_norm": 0.6323529411764706, "acc_norm_stderr": 0.02928941340940319 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6241830065359477, "acc_stderr": 0.01959402113657744, "acc_norm": 0.6241830065359477, "acc_norm_stderr": 0.01959402113657744 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6938775510204082, "acc_stderr": 0.02950489645459596, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.02950489645459596 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8009950248756219, "acc_stderr": 0.028231365092758406, "acc_norm": 0.8009950248756219, "acc_norm_stderr": 0.028231365092758406 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8304093567251462, "acc_stderr": 0.02878210810540171, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.02878210810540171 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.5752753977968176, "mc1_stderr": 0.017304000957167477, "mc2": 0.7146460351141442, "mc2_stderr": 0.015047159780719415 }, "harness\|winogrande\|5": { "acc": 0.8453038674033149, "acc_stderr": 0.010163172650433542 }, "harness\|gsm8k\|5": { "acc": 0.6338134950720242, "acc_stderr": 0.013270100238748831 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
DavronSherbaev/uzbekvoice	--- license: apache-2.0 task_categories: - automatic-speech-recognition language: - uz size_categories: - 100K<n<1M ---
urialon/converted_narrative_qa	--- dataset_info: features: - name: id dtype: string - name: pid dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 18019445085 num_examples: 55003 - name: validation num_bytes: 1900648400 num_examples: 5878 - name: test num_bytes: 3228274423 num_examples: 10306 download_size: 8524652529 dataset_size: 23148367908 --- # Dataset Card for "converted_narrative_qa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kraykzzz/Voz	--- license: openrail ---
bdsaglam/musique-answerable-2hop-subset-jerx-reward	--- dataset_info: features: - name: id dtype: string - name: jerx.input dtype: string - name: jerx.output dtype: string - name: reward dtype: int64 splits: - name: train num_bytes: 86982 num_examples: 110 download_size: 0 dataset_size: 86982 configs: - config_name: default data_files: - split: train path: data/train-* ---
Nicolas-BZRD/uld_loss_Llama-2-7b-chat-hf-qed	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: context dtype: string - name: question dtype: string - name: answers list: - name: end dtype: int64 - name: start dtype: int64 - name: string dtype: string - name: answers_generated dtype: string splits: - name: train num_bytes: 5124485 num_examples: 7007 - name: validation num_bytes: 449998 num_examples: 610 download_size: 3652432 dataset_size: 5574483 --- # Dataset Card for "uld_loss_Llama-2-7b-chat-hf-qed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

joey234/mmlu-high_school_us_history-neg-prepend-fix

--- configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: ori_prompt dtype: string splits: - name: dev num_bytes: 28257 num_examples: 5 - name: test num_bytes: 1258154 num_examples: 204 download_size: 55081 dataset_size: 1286411 --- # Dataset Card for "mmlu-high_school_us_history-neg-prepend-fix" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

HamdanXI/paradetox-preprocess-editOps

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: en_toxic_comment dtype: string - name: en_neutral_comment dtype: string - name: edit_ops sequence: sequence: string splits: - name: train num_bytes: 4628797 num_examples: 19744 download_size: 1848112 dataset_size: 4628797 --- # Dataset Card for "paradetox-preprocess-editOps" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

autoevaluate/autoeval-eval-adversarial_qa-adversarialQA-1b5bc0-46134145181

--- type: predictions tags: - autotrain - evaluation datasets: - adversarial_qa eval_info: task: extractive_question_answering model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat metrics: [] dataset_name: adversarial_qa dataset_config: adversarialQA dataset_split: validation col_mapping: context: context question: question answers-text: answers.text answers-answer_start: answers.answer_start --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Question Answering * Model: andi611/bert-large-uncased-whole-word-masking-squad2-with-ner-conll2003-with-neg-with-repeat * Dataset: adversarial_qa * Config: adversarialQA * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@nomic-ai](https://huggingface.co/nomic-ai) for evaluating this model.

huggingartists/phish

--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/phish" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of the generated dataset:** 0.372501 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/df85b83684e95f87794aa09580ee0463.919x919x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/phish"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Phish</div> <a href="https://genius.com/artists/phish"> <div style="text-align: center; font-size: 14px;">@phish</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/phish). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/phish") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits | train |validation|test| |------:|---------:|---:| |394| -| -| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/phish") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About *Built by Aleksey Korshuk* [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)

FINNUMBER/FINCH_TRAIN_NQA_ARI_100_NEWFORMAT

--- dataset_info: features: - name: task dtype: string - name: context dtype: string - name: question dtype: string - name: answer dtype: string - name: instruction dtype: string - name: output dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 279758 num_examples: 100 download_size: 175553 dataset_size: 279758 configs: - config_name: default data_files: - split: train path: data/train-* ---

YAGO1818/LunaVB

--- license: apache-2.0 ---

carlavic/Moedas

--- license: openrail ---

YiYiXu/yiyi_test_ds

--- dataset_info: features: - name: image dtype: image - name: condtioning_image dtype: image - name: caption dtype: string splits: - name: train num_bytes: 22659003.0 num_examples: 15 download_size: 22663578 dataset_size: 22659003.0 --- # Dataset Card for "yiyi_test_ds" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

HydraLM/partitioned_v2_standardized_07

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: dataset_id dtype: string - name: unique_conversation_id dtype: string splits: - name: train num_bytes: 33994535.7580061 num_examples: 66505 download_size: 36546793 dataset_size: 33994535.7580061 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "partitioned_v2_standardized_07" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

BangumiBase/seireinomoribito

--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Seirei No Moribito This is the image base of bangumi Seirei no Moribito, we detected 26 characters, 2981 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 593 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 73 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 487 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 450 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 327 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 79 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 33 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 126 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 81 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 46 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 43 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 73 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 16 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 172 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 96 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 18 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 62 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 18 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 53 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 24 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 28 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 11 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 14 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 12 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 12 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | noise | 34 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |

piercemaloney/coqgym_coq_projects_v1

--- dataset_info: features: - name: text dtype: string splits: - name: finmap num_bytes: 745110 num_examples: 3 - name: GeometricAlgebra num_bytes: 2180457 num_examples: 8 - name: bdds num_bytes: 11537326 num_examples: 15 - name: topology num_bytes: 1998914 num_examples: 32 - name: euler_formula num_bytes: 2157257 num_examples: 3 - name: ruler_compass_geometry num_bytes: 105862 num_examples: 10 - name: twoSquare num_bytes: 219009 num_examples: 2 - name: zfc num_bytes: 605621 num_examples: 11 - name: shuffle num_bytes: 87431 num_examples: 6 - name: three_gap num_bytes: 315458 num_examples: 7 - name: regexp num_bytes: 116907 num_examples: 7 - name: automata num_bytes: 1075636 num_examples: 25 - name: izf num_bytes: 146423 num_examples: 8 - name: railroad_crossing num_bytes: 202543 num_examples: 1 - name: idxassoc num_bytes: 139339 num_examples: 2 - name: hoare_tut num_bytes: 39069 num_examples: 3 - name: lesniewski_mereology num_bytes: 123636 num_examples: 2 - name: additions num_bytes: 147048 num_examples: 20 - name: checker num_bytes: 6689 num_examples: 2 - name: domain_theory num_bytes: 67545 num_examples: 4 - name: propcalc num_bytes: 54422 num_examples: 5 - name: area_method num_bytes: 1578799 num_examples: 38 - name: ails num_bytes: 521926 num_examples: 11 - name: dep_map num_bytes: 24951 num_examples: 2 - name: markov num_bytes: 102887 num_examples: 1 - name: rsa num_bytes: 180155 num_examples: 5 - name: goedel num_bytes: 9110441 num_examples: 44 - name: bigenough num_bytes: 5031 num_examples: 1 - name: generic_environments num_bytes: 142529 num_examples: 2 - name: ctltctl num_bytes: 61038 num_examples: 3 - name: schroeder num_bytes: 24958 num_examples: 4 - name: weak_up_to num_bytes: 175365 num_examples: 10 - name: groups num_bytes: 11115 num_examples: 1 - name: pocklington num_bytes: 617483 num_examples: 13 - name: mini_compiler num_bytes: 14459 num_examples: 1 - name: StructTact num_bytes: 293887 num_examples: 17 - name: exceptions num_bytes: 8962 num_examples: 1 - name: coqrel num_bytes: 196290 num_examples: 12 - name: higman_s num_bytes: 198793 num_examples: 5 - name: rem num_bytes: 14504 num_examples: 1 - name: tree_automata num_bytes: 1972575 num_examples: 17 - name: higman_cf num_bytes: 49720 num_examples: 2 - name: coqoban num_bytes: 38285 num_examples: 1 - name: search_trees num_bytes: 59332 num_examples: 5 - name: ieee754 num_bytes: 35416 num_examples: 3 - name: jordan_curve_theorem num_bytes: 12530912 num_examples: 10 - name: hedges num_bytes: 360884 num_examples: 1 - name: zorns_lemma num_bytes: 608752 num_examples: 19 - name: tortoise_hare_algorithm num_bytes: 10084 num_examples: 1 - name: mod_red num_bytes: 636981 num_examples: 5 - name: traversable_fincontainer num_bytes: 429019 num_examples: 1 - name: buchberger num_bytes: 2422607 num_examples: 29 - name: constructive_geometry num_bytes: 80179 num_examples: 7 - name: tarski_geometry num_bytes: 112419 num_examples: 8 - name: int_map num_bytes: 817835 num_examples: 13 - name: float num_bytes: 2994074 num_examples: 31 - name: InfSeqExt num_bytes: 106656 num_examples: 5 - name: zchinese num_bytes: 62626 num_examples: 6 - name: smc num_bytes: 6045540 num_examples: 15 - name: pts num_bytes: 72482 num_examples: 8 - name: param_pi num_bytes: 2596347 num_examples: 11 - name: axiomatic_abp num_bytes: 1204713 num_examples: 7 - name: lambda num_bytes: 181085 num_examples: 10 - name: maths num_bytes: 37685 num_examples: 3 - name: quicksort_complexity num_bytes: 489164 num_examples: 28 - name: fssec_model num_bytes: 1569135 num_examples: 25 - name: ipc num_bytes: 3108901 num_examples: 31 - name: chinese num_bytes: 208365 num_examples: 13 - name: cours_de_coq num_bytes: 71295 num_examples: 11 - name: graphs num_bytes: 644609 num_examples: 2 - name: dictionaries num_bytes: 67746 num_examples: 1 - name: free_groups num_bytes: 63973 num_examples: 1 - name: ramsey num_bytes: 11734 num_examples: 1 - name: angles num_bytes: 322579 num_examples: 5 - name: orb_stab num_bytes: 204783 num_examples: 1 - name: qarith_stern_brocot num_bytes: 10873352 num_examples: 35 - name: group_theory num_bytes: 65160 num_examples: 5 - name: demos num_bytes: 62208 num_examples: 5 - name: distributed_reference_counting num_bytes: 20874 num_examples: 1 - name: subst num_bytes: 362195 num_examples: 17 - name: miniml num_bytes: 114099 num_examples: 1 - name: algebra num_bytes: 3275753 num_examples: 65 - name: fermat4 num_bytes: 172156 num_examples: 5 - name: otway_rees num_bytes: 226052 num_examples: 19 - name: PolTac num_bytes: 157370 num_examples: 13 - name: fundamental_arithmetics num_bytes: 308733 num_examples: 8 download_size: 11353498 dataset_size: 91221719 configs: - config_name: default data_files: - split: finmap path: data/finmap-* - split: GeometricAlgebra path: data/GeometricAlgebra-* - split: bdds path: data/bdds-* - split: topology path: data/topology-* - split: euler_formula path: data/euler_formula-* - split: ruler_compass_geometry path: data/ruler_compass_geometry-* - split: twoSquare path: data/twoSquare-* - split: zfc path: data/zfc-* - split: shuffle path: data/shuffle-* - split: three_gap path: data/three_gap-* - split: regexp path: data/regexp-* - split: automata path: data/automata-* - split: izf path: data/izf-* - split: railroad_crossing path: data/railroad_crossing-* - split: idxassoc path: data/idxassoc-* - split: hoare_tut path: data/hoare_tut-* - split: lesniewski_mereology path: data/lesniewski_mereology-* - split: additions path: data/additions-* - split: checker path: data/checker-* - split: domain_theory path: data/domain_theory-* - split: propcalc path: data/propcalc-* - split: area_method path: data/area_method-* - split: ails path: data/ails-* - split: dep_map path: data/dep_map-* - split: markov path: data/markov-* - split: rsa path: data/rsa-* - split: goedel path: data/goedel-* - split: bigenough path: data/bigenough-* - split: generic_environments path: data/generic_environments-* - split: ctltctl path: data/ctltctl-* - split: schroeder path: data/schroeder-* - split: weak_up_to path: data/weak_up_to-* - split: groups path: data/groups-* - split: pocklington path: data/pocklington-* - split: mini_compiler path: data/mini_compiler-* - split: StructTact path: data/StructTact-* - split: exceptions path: data/exceptions-* - split: coqrel path: data/coqrel-* - split: higman_s path: data/higman_s-* - split: rem path: data/rem-* - split: tree_automata path: data/tree_automata-* - split: higman_cf path: data/higman_cf-* - split: coqoban path: data/coqoban-* - split: search_trees path: data/search_trees-* - split: ieee754 path: data/ieee754-* - split: jordan_curve_theorem path: data/jordan_curve_theorem-* - split: hedges path: data/hedges-* - split: zorns_lemma path: data/zorns_lemma-* - split: tortoise_hare_algorithm path: data/tortoise_hare_algorithm-* - split: mod_red path: data/mod_red-* - split: traversable_fincontainer path: data/traversable_fincontainer-* - split: buchberger path: data/buchberger-* - split: constructive_geometry path: data/constructive_geometry-* - split: tarski_geometry path: data/tarski_geometry-* - split: int_map path: data/int_map-* - split: float path: data/float-* - split: InfSeqExt path: data/InfSeqExt-* - split: zchinese path: data/zchinese-* - split: smc path: data/smc-* - split: pts path: data/pts-* - split: param_pi path: data/param_pi-* - split: axiomatic_abp path: data/axiomatic_abp-* - split: lambda path: data/lambda-* - split: maths path: data/maths-* - split: quicksort_complexity path: data/quicksort_complexity-* - split: fssec_model path: data/fssec_model-* - split: ipc path: data/ipc-* - split: chinese path: data/chinese-* - split: cours_de_coq path: data/cours_de_coq-* - split: graphs path: data/graphs-* - split: dictionaries path: data/dictionaries-* - split: free_groups path: data/free_groups-* - split: ramsey path: data/ramsey-* - split: angles path: data/angles-* - split: orb_stab path: data/orb_stab-* - split: qarith_stern_brocot path: data/qarith_stern_brocot-* - split: group_theory path: data/group_theory-* - split: demos path: data/demos-* - split: distributed_reference_counting path: data/distributed_reference_counting-* - split: subst path: data/subst-* - split: miniml path: data/miniml-* - split: algebra path: data/algebra-* - split: fermat4 path: data/fermat4-* - split: otway_rees path: data/otway_rees-* - split: PolTac path: data/PolTac-* - split: fundamental_arithmetics path: data/fundamental_arithmetics-* ---

YidaM4396/Test

--- license: mit ---

Mizukico/sd-config

--- license: openrail ---

filwsyl/ascend

--- annotations_creators: - expert-generated language_creators: - crowdsourced language: - en - zh language_bcp47: - en - zh-CN license: - cc-by-sa-4.0 multilinguality: - multilingual pretty_name: 'ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation' size_categories: - 10K<n<100K source_datasets: - original task_categories: - automatic-speech-recognition task_ids: - code-switching - speech-recognition --- # Dataset Card for ASCEND ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - **Homepage:** [Needs More Information] - **Repository:** [Needs More Information] - **Paper:** https://arxiv.org/abs/2112.06223 - **Leaderboard:** [Needs More Information] - **Point of Contact:** [Needs More Information] ### Dataset Summary ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set. ### Supported Tasks and Leaderboards [Needs More Information] ### Languages Chinese and English ## Dataset Structure ### Data Instances [Needs More Information] ### Data Fields [Needs More Information] ### Data Splits [Needs More Information] ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information [Needs More Information] ### Citation Information [Needs More Information]

sunhaozhepy/ag_news_roberta_keywords_embeddings

--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': World '1': Sports '2': Business '3': Sci/Tech - name: keywords dtype: string - name: keywords_embeddings sequence: float32 splits: - name: train num_bytes: 401783299 num_examples: 120000 - name: test num_bytes: 25437883 num_examples: 7600 download_size: 493380668 dataset_size: 427221182 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

suchirsalhan/MAO-CHILDES

--- license: mit ---

open-llm-leaderboard/details_mosaicml__mpt-7b-instruct

--- pretty_name: Evaluation run of mosaicml/mpt-7b-instruct dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) 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_mosaicml__mpt-7b-instruct\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T07:03:23.990596](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b-instruct/blob/main/results_2023-09-23T07-03-23.990596.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\": 0.2429739932885906,\n\ \ \"em_stderr\": 0.004392127579519805,\n \"f1\": 0.2939712667785233,\n\ \ \"f1_stderr\": 0.004382684089142145,\n \"acc\": 0.3664330383509068,\n\ \ \"acc_stderr\": 0.00868382013779556\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.2429739932885906,\n \"em_stderr\": 0.004392127579519805,\n\ \ \"f1\": 0.2939712667785233,\n \"f1_stderr\": 0.004382684089142145\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.028051554207733132,\n \ \ \"acc_stderr\": 0.0045482295338363475\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7048145224940805,\n \"acc_stderr\": 0.012819410741754772\n\ \ }\n}\n```" repo_url: https://huggingface.co/mosaicml/mpt-7b-instruct leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|arc:challenge|25_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-07-20T10:01:10.556120.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T07_03_23.990596 path: - '**/details_harness|drop|3_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '**/details_harness|drop|3_2023-09-23T07-03-23.990596.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T07_03_23.990596 path: - '**/details_harness|gsm8k|5_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-09-23T07-03-23.990596.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hellaswag|10_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-20T10:01:10.556120.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-management|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-virology|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-20T10:01:10.556120.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_20T10_01_10.556120 path: - '**/details_harness|truthfulqa:mc|0_2023-07-20T10:01:10.556120.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-07-20T10:01:10.556120.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T07_03_23.990596 path: - '**/details_harness|winogrande|5_2023-09-23T07-03-23.990596.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-09-23T07-03-23.990596.parquet' - config_name: results data_files: - split: 2023_07_20T10_01_10.556120 path: - results_2023-07-20T10:01:10.556120.parquet - split: 2023_09_23T07_03_23.990596 path: - results_2023-09-23T07-03-23.990596.parquet - split: latest path: - results_2023-09-23T07-03-23.990596.parquet --- # Dataset Card for Evaluation run of mosaicml/mpt-7b-instruct ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/mosaicml/mpt-7b-instruct - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) 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_mosaicml__mpt-7b-instruct", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T07:03:23.990596](https://huggingface.co/datasets/open-llm-leaderboard/details_mosaicml__mpt-7b-instruct/blob/main/results_2023-09-23T07-03-23.990596.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": 0.2429739932885906, "em_stderr": 0.004392127579519805, "f1": 0.2939712667785233, "f1_stderr": 0.004382684089142145, "acc": 0.3664330383509068, "acc_stderr": 0.00868382013779556 }, "harness|drop|3": { "em": 0.2429739932885906, "em_stderr": 0.004392127579519805, "f1": 0.2939712667785233, "f1_stderr": 0.004382684089142145 }, "harness|gsm8k|5": { "acc": 0.028051554207733132, "acc_stderr": 0.0045482295338363475 }, "harness|winogrande|5": { "acc": 0.7048145224940805, "acc_stderr": 0.012819410741754772 } } ``` ### 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]

mtalrefaie/arallama-dataset-v1.0

--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string - name: meta struct: - name: warc_headers struct: - name: warc-record-id dtype: string - name: warc-date dtype: string - name: content-type dtype: string - name: content-length dtype: int32 - name: warc-type dtype: string - name: warc-identified-content-language dtype: string - name: warc-refers-to dtype: string - name: warc-target-uri dtype: string - name: warc-block-digest dtype: string - name: identification struct: - name: label dtype: string - name: prob dtype: float32 - name: harmful_pp dtype: float32 - name: tlsh dtype: string - name: quality_warnings sequence: string - name: categories sequence: string - name: sentence_identifications list: - name: label dtype: string - name: prob dtype: float32 splits: - name: train num_bytes: 63195041070 num_examples: 4975268 download_size: 29939473314 dataset_size: 63195041070 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1

--- pretty_name: Evaluation run of mistralai/Mixtral-8x7B-Instruct-v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_mistralai__Mixtral-8x7B-Instruct-v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-05T04:20:22.140239](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1/blob/main/results_2024-01-05T04-20-22.140239.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\": 0.7126033327488117,\n\ \ \"acc_stderr\": 0.030215739102142546,\n \"acc_norm\": 0.7164863994184663,\n\ \ \"acc_norm_stderr\": 0.030796061622697008,\n \"mc1\": 0.5006119951040392,\n\ \ \"mc1_stderr\": 0.01750348793889251,\n \"mc2\": 0.649788114114722,\n\ \ \"mc2_stderr\": 0.015119260704075871\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6655290102389079,\n \"acc_stderr\": 0.013787460322441377,\n\ \ \"acc_norm\": 0.7013651877133106,\n \"acc_norm_stderr\": 0.013374078615068738\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6858195578570006,\n\ \ \"acc_stderr\": 0.004632399677490809,\n \"acc_norm\": 0.8755228042222665,\n\ \ \"acc_norm_stderr\": 0.003294504807555227\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6666666666666666,\n\ \ \"acc_stderr\": 0.04072314811876837,\n \"acc_norm\": 0.6666666666666666,\n\ \ \"acc_norm_stderr\": 0.04072314811876837\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7894736842105263,\n \"acc_stderr\": 0.03317672787533157,\n\ \ \"acc_norm\": 0.7894736842105263,\n \"acc_norm_stderr\": 0.03317672787533157\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.73,\n\ \ \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n \ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7773584905660378,\n \"acc_stderr\": 0.025604233470899098,\n\ \ \"acc_norm\": 0.7773584905660378,\n \"acc_norm_stderr\": 0.025604233470899098\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8263888888888888,\n\ \ \"acc_stderr\": 0.03167473383795718,\n \"acc_norm\": 0.8263888888888888,\n\ \ \"acc_norm_stderr\": 0.03167473383795718\n },\n \"harness|hendrycksTest-college_chemistry|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-college_computer_science|5\": {\n \"acc\"\ : 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\": 0.66,\n\ \ \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-college_mathematics|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_medicine|5\": {\n \"acc\": 0.7572254335260116,\n\ \ \"acc_stderr\": 0.0326926380614177,\n \"acc_norm\": 0.7572254335260116,\n\ \ \"acc_norm_stderr\": 0.0326926380614177\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287534,\n\ \ \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287534\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.81,\n \"acc_stderr\": 0.039427724440366234,\n \"acc_norm\": 0.81,\n\ \ \"acc_norm_stderr\": 0.039427724440366234\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6680851063829787,\n \"acc_stderr\": 0.03078373675774564,\n\ \ \"acc_norm\": 0.6680851063829787,\n \"acc_norm_stderr\": 0.03078373675774564\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.6140350877192983,\n\ \ \"acc_stderr\": 0.04579639422070434,\n \"acc_norm\": 0.6140350877192983,\n\ \ \"acc_norm_stderr\": 0.04579639422070434\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6482758620689655,\n \"acc_stderr\": 0.0397923663749741,\n\ \ \"acc_norm\": 0.6482758620689655,\n \"acc_norm_stderr\": 0.0397923663749741\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.47883597883597884,\n \"acc_stderr\": 0.025728230952130726,\n \"\ acc_norm\": 0.47883597883597884,\n \"acc_norm_stderr\": 0.025728230952130726\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\": 0.42,\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\"\ : 0.8516129032258064,\n \"acc_stderr\": 0.020222737554330378,\n \"\ acc_norm\": 0.8516129032258064,\n \"acc_norm_stderr\": 0.020222737554330378\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.6206896551724138,\n \"acc_stderr\": 0.034139638059062345,\n \"\ acc_norm\": 0.6206896551724138,\n \"acc_norm_stderr\": 0.034139638059062345\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.78,\n \"acc_stderr\": 0.041633319989322626,\n \"acc_norm\"\ : 0.78,\n \"acc_norm_stderr\": 0.041633319989322626\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.03123475237772117,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.03123475237772117\n },\n\ \ \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\": 0.8686868686868687,\n\ \ \"acc_stderr\": 0.024063156416822523,\n \"acc_norm\": 0.8686868686868687,\n\ \ \"acc_norm_stderr\": 0.024063156416822523\n },\n \"harness|hendrycksTest-high_school_government_and_politics|5\"\ : {\n \"acc\": 0.9585492227979274,\n \"acc_stderr\": 0.01438543285747646,\n\ \ \"acc_norm\": 0.9585492227979274,\n \"acc_norm_stderr\": 0.01438543285747646\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3888888888888889,\n \"acc_stderr\": 0.029723278961476664,\n \ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.029723278961476664\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.8025210084033614,\n \"acc_stderr\": 0.02585916412205145,\n \ \ \"acc_norm\": 0.8025210084033614,\n \"acc_norm_stderr\": 0.02585916412205145\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\"\ : 0.8844036697247707,\n \"acc_stderr\": 0.013708749534172636,\n \"\ acc_norm\": 0.8844036697247707,\n \"acc_norm_stderr\": 0.013708749534172636\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5972222222222222,\n \"acc_stderr\": 0.03344887382997866,\n \"\ acc_norm\": 0.5972222222222222,\n \"acc_norm_stderr\": 0.03344887382997866\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8529411764705882,\n \"acc_stderr\": 0.024857478080250447,\n \"\ acc_norm\": 0.8529411764705882,\n \"acc_norm_stderr\": 0.024857478080250447\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8481012658227848,\n \"acc_stderr\": 0.023363878096632446,\n \ \ \"acc_norm\": 0.8481012658227848,\n \"acc_norm_stderr\": 0.023363878096632446\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.757847533632287,\n\ \ \"acc_stderr\": 0.028751392398694755,\n \"acc_norm\": 0.757847533632287,\n\ \ \"acc_norm_stderr\": 0.028751392398694755\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8091603053435115,\n \"acc_stderr\": 0.034465133507525975,\n\ \ \"acc_norm\": 0.8091603053435115,\n \"acc_norm_stderr\": 0.034465133507525975\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8760330578512396,\n \"acc_stderr\": 0.030083098716035202,\n \"\ acc_norm\": 0.8760330578512396,\n \"acc_norm_stderr\": 0.030083098716035202\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8425925925925926,\n\ \ \"acc_stderr\": 0.03520703990517963,\n \"acc_norm\": 0.8425925925925926,\n\ \ \"acc_norm_stderr\": 0.03520703990517963\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8159509202453987,\n \"acc_stderr\": 0.030446777687971716,\n\ \ \"acc_norm\": 0.8159509202453987,\n \"acc_norm_stderr\": 0.030446777687971716\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5714285714285714,\n\ \ \"acc_stderr\": 0.04697113923010213,\n \"acc_norm\": 0.5714285714285714,\n\ \ \"acc_norm_stderr\": 0.04697113923010213\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.035865947385739734,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.035865947385739734\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9230769230769231,\n\ \ \"acc_stderr\": 0.017456987872436193,\n \"acc_norm\": 0.9230769230769231,\n\ \ \"acc_norm_stderr\": 0.017456987872436193\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.879948914431673,\n\ \ \"acc_stderr\": 0.011622736692041287,\n \"acc_norm\": 0.879948914431673,\n\ \ \"acc_norm_stderr\": 0.011622736692041287\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7803468208092486,\n \"acc_stderr\": 0.022289638852617897,\n\ \ \"acc_norm\": 0.7803468208092486,\n \"acc_norm_stderr\": 0.022289638852617897\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.46033519553072627,\n\ \ \"acc_stderr\": 0.016669799592112032,\n \"acc_norm\": 0.46033519553072627,\n\ \ \"acc_norm_stderr\": 0.016669799592112032\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.8202614379084967,\n \"acc_stderr\": 0.02198603218206415,\n\ \ \"acc_norm\": 0.8202614379084967,\n \"acc_norm_stderr\": 0.02198603218206415\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.797427652733119,\n\ \ \"acc_stderr\": 0.022827317491059686,\n \"acc_norm\": 0.797427652733119,\n\ \ \"acc_norm_stderr\": 0.022827317491059686\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8333333333333334,\n \"acc_stderr\": 0.020736358408060006,\n\ \ \"acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.020736358408060006\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5531914893617021,\n \"acc_stderr\": 0.029658235097666907,\n \ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.029658235097666907\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5443285528031291,\n\ \ \"acc_stderr\": 0.012719949543032228,\n \"acc_norm\": 0.5443285528031291,\n\ \ \"acc_norm_stderr\": 0.012719949543032228\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7941176470588235,\n \"acc_stderr\": 0.02456220431414231,\n\ \ \"acc_norm\": 0.7941176470588235,\n \"acc_norm_stderr\": 0.02456220431414231\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7647058823529411,\n \"acc_stderr\": 0.01716058723504635,\n \ \ \"acc_norm\": 0.7647058823529411,\n \"acc_norm_stderr\": 0.01716058723504635\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7090909090909091,\n\ \ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.7090909090909091,\n\ \ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7714285714285715,\n \"acc_stderr\": 0.02688214492230774,\n\ \ \"acc_norm\": 0.7714285714285715,\n \"acc_norm_stderr\": 0.02688214492230774\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.02207632610182466,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.02207632610182466\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5060240963855421,\n\ \ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.5060240963855421,\n\ \ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.02517298435015577,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.02517298435015577\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5006119951040392,\n\ \ \"mc1_stderr\": 0.01750348793889251,\n \"mc2\": 0.649788114114722,\n\ \ \"mc2_stderr\": 0.015119260704075871\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8105761641673244,\n \"acc_stderr\": 0.011012790432989247\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6110689916603488,\n \ \ \"acc_stderr\": 0.01342838248127424\n }\n}\n```" repo_url: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|arc:challenge|25_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-05T04-20-22.140239.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|gsm8k|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hellaswag|10_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-05T04-20-22.140239.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-management|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T04-20-22.140239.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|truthfulqa:mc|0_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-05T04-20-22.140239.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_05T04_20_22.140239 path: - '**/details_harness|winogrande|5_2024-01-05T04-20-22.140239.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-05T04-20-22.140239.parquet' - config_name: results data_files: - split: 2024_01_05T04_20_22.140239 path: - results_2024-01-05T04-20-22.140239.parquet - split: latest path: - results_2024-01-05T04-20-22.140239.parquet --- # Dataset Card for Evaluation run of mistralai/Mixtral-8x7B-Instruct-v0.1  Dataset automatically created during the evaluation run of model [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_mistralai__Mixtral-8x7B-Instruct-v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-05T04:20:22.140239](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mixtral-8x7B-Instruct-v0.1/blob/main/results_2024-01-05T04-20-22.140239.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": 0.7126033327488117, "acc_stderr": 0.030215739102142546, "acc_norm": 0.7164863994184663, "acc_norm_stderr": 0.030796061622697008, "mc1": 0.5006119951040392, "mc1_stderr": 0.01750348793889251, "mc2": 0.649788114114722, "mc2_stderr": 0.015119260704075871 }, "harness|arc:challenge|25": { "acc": 0.6655290102389079, "acc_stderr": 0.013787460322441377, "acc_norm": 0.7013651877133106, "acc_norm_stderr": 0.013374078615068738 }, "harness|hellaswag|10": { "acc": 0.6858195578570006, "acc_stderr": 0.004632399677490809, "acc_norm": 0.8755228042222665, "acc_norm_stderr": 0.003294504807555227 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6666666666666666, "acc_stderr": 0.04072314811876837, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.04072314811876837 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7894736842105263, "acc_stderr": 0.03317672787533157, "acc_norm": 0.7894736842105263, "acc_norm_stderr": 0.03317672787533157 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7773584905660378, "acc_stderr": 0.025604233470899098, "acc_norm": 0.7773584905660378, "acc_norm_stderr": 0.025604233470899098 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8263888888888888, "acc_stderr": 0.03167473383795718, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.03167473383795718 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7572254335260116, "acc_stderr": 0.0326926380614177, "acc_norm": 0.7572254335260116, "acc_norm_stderr": 0.0326926380614177 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6680851063829787, "acc_stderr": 0.03078373675774564, "acc_norm": 0.6680851063829787, "acc_norm_stderr": 0.03078373675774564 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6140350877192983, "acc_stderr": 0.04579639422070434, "acc_norm": 0.6140350877192983, "acc_norm_stderr": 0.04579639422070434 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6482758620689655, "acc_stderr": 0.0397923663749741, "acc_norm": 0.6482758620689655, "acc_norm_stderr": 0.0397923663749741 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.47883597883597884, "acc_stderr": 0.025728230952130726, "acc_norm": 0.47883597883597884, "acc_norm_stderr": 0.025728230952130726 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5238095238095238, "acc_stderr": 0.04467062628403273, "acc_norm": 0.5238095238095238, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8516129032258064, "acc_stderr": 0.020222737554330378, "acc_norm": 0.8516129032258064, "acc_norm_stderr": 0.020222737554330378 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6206896551724138, "acc_stderr": 0.034139638059062345, "acc_norm": 0.6206896551724138, "acc_norm_stderr": 0.034139638059062345 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.78, "acc_stderr": 0.041633319989322626, "acc_norm": 0.78, "acc_norm_stderr": 0.041633319989322626 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8, "acc_stderr": 0.03123475237772117, "acc_norm": 0.8, "acc_norm_stderr": 0.03123475237772117 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8686868686868687, "acc_stderr": 0.024063156416822523, "acc_norm": 0.8686868686868687, "acc_norm_stderr": 0.024063156416822523 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9585492227979274, "acc_stderr": 0.01438543285747646, "acc_norm": 0.9585492227979274, "acc_norm_stderr": 0.01438543285747646 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.029723278961476664, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.029723278961476664 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.8025210084033614, "acc_stderr": 0.02585916412205145, "acc_norm": 0.8025210084033614, "acc_norm_stderr": 0.02585916412205145 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.47019867549668876, "acc_stderr": 0.040752249922169775, "acc_norm": 0.47019867549668876, "acc_norm_stderr": 0.040752249922169775 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8844036697247707, "acc_stderr": 0.013708749534172636, "acc_norm": 0.8844036697247707, "acc_norm_stderr": 0.013708749534172636 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5972222222222222, "acc_stderr": 0.03344887382997866, "acc_norm": 0.5972222222222222, "acc_norm_stderr": 0.03344887382997866 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8529411764705882, "acc_stderr": 0.024857478080250447, "acc_norm": 0.8529411764705882, "acc_norm_stderr": 0.024857478080250447 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8481012658227848, "acc_stderr": 0.023363878096632446, "acc_norm": 0.8481012658227848, "acc_norm_stderr": 0.023363878096632446 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.757847533632287, "acc_stderr": 0.028751392398694755, "acc_norm": 0.757847533632287, "acc_norm_stderr": 0.028751392398694755 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8091603053435115, "acc_stderr": 0.034465133507525975, "acc_norm": 0.8091603053435115, "acc_norm_stderr": 0.034465133507525975 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8760330578512396, "acc_stderr": 0.030083098716035202, "acc_norm": 0.8760330578512396, "acc_norm_stderr": 0.030083098716035202 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8425925925925926, "acc_stderr": 0.03520703990517963, "acc_norm": 0.8425925925925926, "acc_norm_stderr": 0.03520703990517963 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8159509202453987, "acc_stderr": 0.030446777687971716, "acc_norm": 0.8159509202453987, "acc_norm_stderr": 0.030446777687971716 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5714285714285714, "acc_stderr": 0.04697113923010213, "acc_norm": 0.5714285714285714, "acc_norm_stderr": 0.04697113923010213 }, "harness|hendrycksTest-management|5": { "acc": 0.8446601941747572, "acc_stderr": 0.035865947385739734, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.035865947385739734 }, "harness|hendrycksTest-marketing|5": { "acc": 0.9230769230769231, "acc_stderr": 0.017456987872436193, "acc_norm": 0.9230769230769231, "acc_norm_stderr": 0.017456987872436193 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.77, "acc_stderr": 0.042295258468165065, "acc_norm": 0.77, "acc_norm_stderr": 0.042295258468165065 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.879948914431673, "acc_stderr": 0.011622736692041287, "acc_norm": 0.879948914431673, "acc_norm_stderr": 0.011622736692041287 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7803468208092486, "acc_stderr": 0.022289638852617897, "acc_norm": 0.7803468208092486, "acc_norm_stderr": 0.022289638852617897 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.46033519553072627, "acc_stderr": 0.016669799592112032, "acc_norm": 0.46033519553072627, "acc_norm_stderr": 0.016669799592112032 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.8202614379084967, "acc_stderr": 0.02198603218206415, "acc_norm": 0.8202614379084967, "acc_norm_stderr": 0.02198603218206415 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.797427652733119, "acc_stderr": 0.022827317491059686, "acc_norm": 0.797427652733119, "acc_norm_stderr": 0.022827317491059686 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8333333333333334, "acc_stderr": 0.020736358408060006, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.020736358408060006 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5531914893617021, "acc_stderr": 0.029658235097666907, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.029658235097666907 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5443285528031291, "acc_stderr": 0.012719949543032228, "acc_norm": 0.5443285528031291, "acc_norm_stderr": 0.012719949543032228 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7941176470588235, "acc_stderr": 0.02456220431414231, "acc_norm": 0.7941176470588235, "acc_norm_stderr": 0.02456220431414231 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7647058823529411, "acc_stderr": 0.01716058723504635, "acc_norm": 0.7647058823529411, "acc_norm_stderr": 0.01716058723504635 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7090909090909091, "acc_stderr": 0.04350271442923243, "acc_norm": 0.7090909090909091, "acc_norm_stderr": 0.04350271442923243 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7714285714285715, "acc_stderr": 0.02688214492230774, "acc_norm": 0.7714285714285715, "acc_norm_stderr": 0.02688214492230774 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8905472636815921, "acc_stderr": 0.02207632610182466, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.02207632610182466 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness|hendrycksTest-virology|5": { "acc": 0.5060240963855421, "acc_stderr": 0.03892212195333045, "acc_norm": 0.5060240963855421, "acc_norm_stderr": 0.03892212195333045 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8771929824561403, "acc_stderr": 0.02517298435015577, "acc_norm": 0.8771929824561403, "acc_norm_stderr": 0.02517298435015577 }, "harness|truthfulqa:mc|0": { "mc1": 0.5006119951040392, "mc1_stderr": 0.01750348793889251, "mc2": 0.649788114114722, "mc2_stderr": 0.015119260704075871 }, "harness|winogrande|5": { "acc": 0.8105761641673244, "acc_stderr": 0.011012790432989247 }, "harness|gsm8k|5": { "acc": 0.6110689916603488, "acc_stderr": 0.01342838248127424 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection 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[More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

open-llm-leaderboard/details_01-ai__Yi-9B

--- pretty_name: Evaluation run of 01-ai/Yi-9B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [01-ai/Yi-9B](https://huggingface.co/01-ai/Yi-9B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_01-ai__Yi-9B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-07T00:53:16.402231](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-9B/blob/main/results_2024-03-07T00-53-16.402231.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\": 0.6944616852197417,\n\ \ \"acc_stderr\": 0.030657841258996534,\n \"acc_norm\": 0.7006110175468258,\n\ \ \"acc_norm_stderr\": 0.031247040652107712,\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.42448173501507824,\n\ \ \"mc2_stderr\": 0.014715889893086314\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5725255972696246,\n \"acc_stderr\": 0.01445686294465065,\n\ \ \"acc_norm\": 0.6117747440273038,\n \"acc_norm_stderr\": 0.014241614207414044\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5887273451503684,\n\ \ \"acc_stderr\": 0.004910588449330019,\n \"acc_norm\": 0.7881896036646087,\n\ \ \"acc_norm_stderr\": 0.00407756134927239\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695236\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5777777777777777,\n\ \ \"acc_stderr\": 0.042667634040995814,\n \"acc_norm\": 0.5777777777777777,\n\ \ \"acc_norm_stderr\": 0.042667634040995814\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.756578947368421,\n \"acc_stderr\": 0.034923496688842384,\n\ \ \"acc_norm\": 0.756578947368421,\n \"acc_norm_stderr\": 0.034923496688842384\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.8,\n\ \ \"acc_stderr\": 0.04020151261036844,\n \"acc_norm\": 0.8,\n \ \ \"acc_norm_stderr\": 0.04020151261036844\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7320754716981132,\n \"acc_stderr\": 0.027257260322494845,\n\ \ \"acc_norm\": 0.7320754716981132,\n \"acc_norm_stderr\": 0.027257260322494845\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8263888888888888,\n\ \ \"acc_stderr\": 0.03167473383795718,\n \"acc_norm\": 0.8263888888888888,\n\ \ \"acc_norm_stderr\": 0.03167473383795718\n },\n \"harness|hendrycksTest-college_chemistry|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-college_computer_science|5\": {\n \"acc\"\ : 0.62,\n \"acc_stderr\": 0.04878317312145633,\n \"acc_norm\": 0.62,\n\ \ \"acc_norm_stderr\": 0.04878317312145633\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.7456647398843931,\n\ \ \"acc_stderr\": 0.0332055644308557,\n \"acc_norm\": 0.7456647398843931,\n\ \ \"acc_norm_stderr\": 0.0332055644308557\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4215686274509804,\n \"acc_stderr\": 0.04913595201274498,\n\ \ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.04913595201274498\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\ \ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.7191489361702128,\n \"acc_stderr\": 0.029379170464124818,\n\ \ \"acc_norm\": 0.7191489361702128,\n \"acc_norm_stderr\": 0.029379170464124818\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5263157894736842,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.5263157894736842,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.7241379310344828,\n \"acc_stderr\": 0.037245636197746325,\n\ \ \"acc_norm\": 0.7241379310344828,\n \"acc_norm_stderr\": 0.037245636197746325\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.6005291005291006,\n \"acc_stderr\": 0.02522545028406793,\n \"\ acc_norm\": 0.6005291005291006,\n \"acc_norm_stderr\": 0.02522545028406793\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5873015873015873,\n\ \ \"acc_stderr\": 0.04403438954768177,\n \"acc_norm\": 0.5873015873015873,\n\ \ \"acc_norm_stderr\": 0.04403438954768177\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8451612903225807,\n\ \ \"acc_stderr\": 0.020579287326583227,\n \"acc_norm\": 0.8451612903225807,\n\ \ \"acc_norm_stderr\": 0.020579287326583227\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5812807881773399,\n \"acc_stderr\": 0.034711928605184676,\n\ \ \"acc_norm\": 0.5812807881773399,\n \"acc_norm_stderr\": 0.034711928605184676\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.032250781083062896,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.032250781083062896\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8535353535353535,\n \"acc_stderr\": 0.02519092111460391,\n \"\ acc_norm\": 0.8535353535353535,\n \"acc_norm_stderr\": 0.02519092111460391\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240514,\n\ \ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240514\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.7589743589743589,\n \"acc_stderr\": 0.02168554666533319,\n \ \ \"acc_norm\": 0.7589743589743589,\n \"acc_norm_stderr\": 0.02168554666533319\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.4,\n \"acc_stderr\": 0.02986960509531691,\n \"acc_norm\"\ : 0.4,\n \"acc_norm_stderr\": 0.02986960509531691\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\ : {\n \"acc\": 0.8235294117647058,\n \"acc_stderr\": 0.024762902678057922,\n\ \ \"acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.024762902678057922\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.4105960264900662,\n \"acc_stderr\": 0.04016689594849927,\n \"\ acc_norm\": 0.4105960264900662,\n \"acc_norm_stderr\": 0.04016689594849927\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8678899082568807,\n \"acc_stderr\": 0.014517801914598238,\n \"\ acc_norm\": 0.8678899082568807,\n \"acc_norm_stderr\": 0.014517801914598238\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.6851851851851852,\n \"acc_stderr\": 0.03167468706828978,\n \"\ acc_norm\": 0.6851851851851852,\n \"acc_norm_stderr\": 0.03167468706828978\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8627450980392157,\n \"acc_stderr\": 0.024152225962801598,\n \"\ acc_norm\": 0.8627450980392157,\n \"acc_norm_stderr\": 0.024152225962801598\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579654,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579654\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7443946188340808,\n\ \ \"acc_stderr\": 0.029275891003969923,\n \"acc_norm\": 0.7443946188340808,\n\ \ \"acc_norm_stderr\": 0.029275891003969923\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8347107438016529,\n \"acc_stderr\": 0.03390780612972776,\n \"\ acc_norm\": 0.8347107438016529,\n \"acc_norm_stderr\": 0.03390780612972776\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7607361963190185,\n \"acc_stderr\": 0.0335195387952127,\n\ \ \"acc_norm\": 0.7607361963190185,\n \"acc_norm_stderr\": 0.0335195387952127\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5803571428571429,\n\ \ \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.5803571428571429,\n\ \ \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\ \ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9102564102564102,\n\ \ \"acc_stderr\": 0.01872430174194166,\n \"acc_norm\": 0.9102564102564102,\n\ \ \"acc_norm_stderr\": 0.01872430174194166\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8390804597701149,\n\ \ \"acc_stderr\": 0.013140225515611724,\n \"acc_norm\": 0.8390804597701149,\n\ \ \"acc_norm_stderr\": 0.013140225515611724\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071124,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071124\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4,\n\ \ \"acc_stderr\": 0.01638463841038082,\n \"acc_norm\": 0.4,\n \ \ \"acc_norm_stderr\": 0.01638463841038082\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7549019607843137,\n \"acc_stderr\": 0.024630048979824775,\n\ \ \"acc_norm\": 0.7549019607843137,\n \"acc_norm_stderr\": 0.024630048979824775\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.77491961414791,\n\ \ \"acc_stderr\": 0.023720088516179027,\n \"acc_norm\": 0.77491961414791,\n\ \ \"acc_norm_stderr\": 0.023720088516179027\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7685185185185185,\n \"acc_stderr\": 0.023468429832451163,\n\ \ \"acc_norm\": 0.7685185185185185,\n \"acc_norm_stderr\": 0.023468429832451163\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5638297872340425,\n \"acc_stderr\": 0.029583452036284066,\n \ \ \"acc_norm\": 0.5638297872340425,\n \"acc_norm_stderr\": 0.029583452036284066\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.49478487614080835,\n\ \ \"acc_stderr\": 0.012769541449652547,\n \"acc_norm\": 0.49478487614080835,\n\ \ \"acc_norm_stderr\": 0.012769541449652547\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7095588235294118,\n \"acc_stderr\": 0.02757646862274053,\n\ \ \"acc_norm\": 0.7095588235294118,\n \"acc_norm_stderr\": 0.02757646862274053\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.704248366013072,\n \"acc_stderr\": 0.01846315413263281,\n \ \ \"acc_norm\": 0.704248366013072,\n \"acc_norm_stderr\": 0.01846315413263281\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.041723430387053825,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.041723430387053825\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7591836734693878,\n \"acc_stderr\": 0.02737294220178816,\n\ \ \"acc_norm\": 0.7591836734693878,\n \"acc_norm_stderr\": 0.02737294220178816\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8606965174129353,\n\ \ \"acc_stderr\": 0.02448448716291397,\n \"acc_norm\": 0.8606965174129353,\n\ \ \"acc_norm_stderr\": 0.02448448716291397\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.028782108105401705,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.028782108105401705\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.42448173501507824,\n\ \ \"mc2_stderr\": 0.014715889893086314\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7750591949486977,\n \"acc_stderr\": 0.01173504356412674\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.489764973464746,\n \ \ \"acc_stderr\": 0.013769598923012397\n }\n}\n```" repo_url: https://huggingface.co/01-ai/Yi-9B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|arc:challenge|25_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-07T00-53-16.402231.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|gsm8k|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hellaswag|10_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-07T00-53-16.402231.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-management|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-07T00-53-16.402231.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|truthfulqa:mc|0_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-07T00-53-16.402231.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_07T00_53_16.402231 path: - '**/details_harness|winogrande|5_2024-03-07T00-53-16.402231.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-07T00-53-16.402231.parquet' - config_name: results data_files: - split: 2024_03_07T00_53_16.402231 path: - results_2024-03-07T00-53-16.402231.parquet - split: latest path: - results_2024-03-07T00-53-16.402231.parquet --- # Dataset Card for Evaluation run of 01-ai/Yi-9B  Dataset automatically created during the evaluation run of model [01-ai/Yi-9B](https://huggingface.co/01-ai/Yi-9B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_01-ai__Yi-9B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-07T00:53:16.402231](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-9B/blob/main/results_2024-03-07T00-53-16.402231.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": 0.6944616852197417, "acc_stderr": 0.030657841258996534, "acc_norm": 0.7006110175468258, "acc_norm_stderr": 0.031247040652107712, "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.42448173501507824, "mc2_stderr": 0.014715889893086314 }, "harness|arc:challenge|25": { "acc": 0.5725255972696246, "acc_stderr": 0.01445686294465065, "acc_norm": 0.6117747440273038, "acc_norm_stderr": 0.014241614207414044 }, "harness|hellaswag|10": { "acc": 0.5887273451503684, "acc_stderr": 0.004910588449330019, "acc_norm": 0.7881896036646087, "acc_norm_stderr": 0.00407756134927239 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5777777777777777, "acc_stderr": 0.042667634040995814, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.042667634040995814 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.756578947368421, "acc_stderr": 0.034923496688842384, "acc_norm": 0.756578947368421, "acc_norm_stderr": 0.034923496688842384 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.8, "acc_stderr": 0.04020151261036844, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036844 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7320754716981132, "acc_stderr": 0.027257260322494845, "acc_norm": 0.7320754716981132, "acc_norm_stderr": 0.027257260322494845 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8263888888888888, "acc_stderr": 0.03167473383795718, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.03167473383795718 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4215686274509804, "acc_stderr": 0.04913595201274498, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.04913595201274498 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7191489361702128, "acc_stderr": 0.029379170464124818, "acc_norm": 0.7191489361702128, "acc_norm_stderr": 0.029379170464124818 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5263157894736842, "acc_stderr": 0.046970851366478626, "acc_norm": 0.5263157894736842, "acc_norm_stderr": 0.046970851366478626 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7241379310344828, "acc_stderr": 0.037245636197746325, "acc_norm": 0.7241379310344828, "acc_norm_stderr": 0.037245636197746325 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6005291005291006, "acc_stderr": 0.02522545028406793, "acc_norm": 0.6005291005291006, "acc_norm_stderr": 0.02522545028406793 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5873015873015873, "acc_stderr": 0.04403438954768177, "acc_norm": 0.5873015873015873, "acc_norm_stderr": 0.04403438954768177 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8451612903225807, "acc_stderr": 0.020579287326583227, "acc_norm": 0.8451612903225807, "acc_norm_stderr": 0.020579287326583227 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5812807881773399, "acc_stderr": 0.034711928605184676, "acc_norm": 0.5812807881773399, "acc_norm_stderr": 0.034711928605184676 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.032250781083062896, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.032250781083062896 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8535353535353535, "acc_stderr": 0.02519092111460391, "acc_norm": 0.8535353535353535, "acc_norm_stderr": 0.02519092111460391 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240514, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240514 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7589743589743589, "acc_stderr": 0.02168554666533319, "acc_norm": 0.7589743589743589, "acc_norm_stderr": 0.02168554666533319 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4, "acc_stderr": 0.02986960509531691, "acc_norm": 0.4, "acc_norm_stderr": 0.02986960509531691 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.8235294117647058, "acc_stderr": 0.024762902678057922, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.024762902678057922 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.4105960264900662, "acc_stderr": 0.04016689594849927, "acc_norm": 0.4105960264900662, "acc_norm_stderr": 0.04016689594849927 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8678899082568807, "acc_stderr": 0.014517801914598238, "acc_norm": 0.8678899082568807, "acc_norm_stderr": 0.014517801914598238 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.6851851851851852, "acc_stderr": 0.03167468706828978, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.03167468706828978 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8627450980392157, "acc_stderr": 0.024152225962801598, "acc_norm": 0.8627450980392157, "acc_norm_stderr": 0.024152225962801598 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579654, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579654 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7443946188340808, "acc_stderr": 0.029275891003969923, "acc_norm": 0.7443946188340808, "acc_norm_stderr": 0.029275891003969923 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8347107438016529, "acc_stderr": 0.03390780612972776, "acc_norm": 0.8347107438016529, "acc_norm_stderr": 0.03390780612972776 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7607361963190185, "acc_stderr": 0.0335195387952127, "acc_norm": 0.7607361963190185, "acc_norm_stderr": 0.0335195387952127 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5803571428571429, "acc_stderr": 0.04684099321077106, "acc_norm": 0.5803571428571429, "acc_norm_stderr": 0.04684099321077106 }, "harness|hendrycksTest-management|5": { "acc": 0.8349514563106796, "acc_stderr": 0.03675668832233188, "acc_norm": 0.8349514563106796, "acc_norm_stderr": 0.03675668832233188 }, "harness|hendrycksTest-marketing|5": { "acc": 0.9102564102564102, "acc_stderr": 0.01872430174194166, "acc_norm": 0.9102564102564102, "acc_norm_stderr": 0.01872430174194166 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8390804597701149, "acc_stderr": 0.013140225515611724, "acc_norm": 0.8390804597701149, "acc_norm_stderr": 0.013140225515611724 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071124, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071124 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4, "acc_stderr": 0.01638463841038082, "acc_norm": 0.4, "acc_norm_stderr": 0.01638463841038082 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7549019607843137, "acc_stderr": 0.024630048979824775, "acc_norm": 0.7549019607843137, "acc_norm_stderr": 0.024630048979824775 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.77491961414791, "acc_stderr": 0.023720088516179027, "acc_norm": 0.77491961414791, "acc_norm_stderr": 0.023720088516179027 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7685185185185185, "acc_stderr": 0.023468429832451163, "acc_norm": 0.7685185185185185, "acc_norm_stderr": 0.023468429832451163 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5638297872340425, "acc_stderr": 0.029583452036284066, "acc_norm": 0.5638297872340425, "acc_norm_stderr": 0.029583452036284066 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.49478487614080835, "acc_stderr": 0.012769541449652547, "acc_norm": 0.49478487614080835, "acc_norm_stderr": 0.012769541449652547 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7095588235294118, "acc_stderr": 0.02757646862274053, "acc_norm": 0.7095588235294118, "acc_norm_stderr": 0.02757646862274053 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.704248366013072, "acc_stderr": 0.01846315413263281, "acc_norm": 0.704248366013072, "acc_norm_stderr": 0.01846315413263281 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7454545454545455, "acc_stderr": 0.041723430387053825, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.041723430387053825 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7591836734693878, "acc_stderr": 0.02737294220178816, "acc_norm": 0.7591836734693878, "acc_norm_stderr": 0.02737294220178816 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8606965174129353, "acc_stderr": 0.02448448716291397, "acc_norm": 0.8606965174129353, "acc_norm_stderr": 0.02448448716291397 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness|hendrycksTest-virology|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8304093567251462, "acc_stderr": 0.028782108105401705, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.028782108105401705 }, "harness|truthfulqa:mc|0": { "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.42448173501507824, "mc2_stderr": 0.014715889893086314 }, "harness|winogrande|5": { "acc": 0.7750591949486977, "acc_stderr": 0.01173504356412674 }, "harness|gsm8k|5": { "acc": 0.489764973464746, "acc_stderr": 0.013769598923012397 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

mboth/kaelteErzeugen-50-undersampled

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* dataset_info: features: - name: Datatype dtype: string - name: Beschreibung dtype: string - name: Name dtype: string - name: Unit dtype: string - name: Grundfunktion dtype: string - name: ScoreGrundfunktion dtype: float64 - name: ZweiteGrundfunktion dtype: string - name: ScoreZweiteGrundfunktion dtype: float64 - name: label dtype: class_label: names: '0': Kaelteanlage '1': KaeltekreisAllgemein '2': Kaeltemaschine '3': Kaeltemengenzaehler '4': Klappe '5': Pumpe '6': RKW '7': Regler '8': Ruecklauf '9': Ventil '10': Vorlauf '11': Waermemengenzaehler - name: ScoreKomponente dtype: float64 - name: Datenpunkt dtype: string - name: ScoreDatenpunkt dtype: float64 - name: text dtype: string splits: - name: train num_bytes: 72126.24090121317 num_examples: 293 - name: test num_bytes: 18282 num_examples: 73 - name: valid num_bytes: 18282 num_examples: 73 download_size: 54220 dataset_size: 108690.24090121317 --- # Dataset Card for "kaelteErzeugen-50-undersampled" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

baptistecolle/sam-controlnet-2

--- dataset_info: features: - name: image dtype: image - name: filepath dtype: string - name: sentids list: int32 - name: filename dtype: string - name: imgid dtype: int32 - name: split dtype: string - name: sentences struct: - name: tokens list: string - name: raw dtype: string - name: imgid dtype: int32 - name: sentid dtype: int32 - name: cocoid dtype: int32 splits: - name: original num_bytes: 160172316.0 num_examples: 1000 download_size: 0 dataset_size: 160172316.0 --- # Dataset Card for "sam-controlnet-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

dura-garage/nep-spell-eval-dataset-6200

--- license: mit ---

tr416/_dataset_20231007_153958

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 762696.0 num_examples: 297 - name: test num_bytes: 7704.0 num_examples: 3 download_size: 73889 dataset_size: 770400.0 --- # Dataset Card for "_dataset_20231007_153958" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

mukayese/truthful_qa-tr

--- license: apache-2.0 ---

Sleoruiz/disc_cla_primera-2

--- dataset_info: features: - name: text dtype: 'null' - name: inputs struct: - name: comision dtype: string - name: fecha_gaceta dtype: string - name: gaceta_numero dtype: string - name: name dtype: string - 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: 32328969 num_examples: 11713 download_size: 16700030 dataset_size: 32328969 --- # Dataset Card for "disc_cla_primera-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Pablao0948/Marina_Sena

--- license: openrail ---

arbml/TinyCalliFont

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 489803410.8 num_examples: 1600 - name: test num_bytes: 61689478.0 num_examples: 200 - name: validation num_bytes: 62852027.0 num_examples: 200 download_size: 617998205 dataset_size: 614344915.8 --- # Dataset Card for "TinyCalliFont" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ovior/twitter_dataset_1713002663

--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 2460067 num_examples: 7251 download_size: 1409617 dataset_size: 2460067 configs: - config_name: default data_files: - split: train path: data/train-* ---

lightblue/gpt4_conversations_multilingual

--- dataset_info: features: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: language dtype: string splits: - name: train num_bytes: 97523643.84159379 num_examples: 9217 download_size: 43657898 dataset_size: 97523643.84159379 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp

--- pretty_name: Evaluation run of RatanRohith/NeuralPizza-Valor-7B-Merge-slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [RatanRohith/NeuralPizza-Valor-7B-Merge-slerp](https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-22T23:00:14.356889](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp/blob/main/results_2024-01-22T23-00-14.356889.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\": 0.23196194129343728,\n\ \ \"acc_stderr\": 0.029934654752561563,\n \"acc_norm\": 0.2314240573187148,\n\ \ \"acc_norm_stderr\": 0.03071122006512167,\n \"mc1\": 1.0,\n \ \ \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n \"mc2_stderr\": NaN\n\ \ },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.22696245733788395,\n\ \ \"acc_stderr\": 0.012240491536132861,\n \"acc_norm\": 0.22696245733788395,\n\ \ \"acc_norm_stderr\": 0.012240491536132861\n },\n \"harness|hellaswag|10\"\ : {\n \"acc\": 0.2504481179047998,\n \"acc_stderr\": 0.004323856300539177,\n\ \ \"acc_norm\": 0.2504481179047998,\n \"acc_norm_stderr\": 0.004323856300539177\n\ \ },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.22,\n\ \ \"acc_stderr\": 0.04163331998932268,\n \"acc_norm\": 0.22,\n \ \ \"acc_norm_stderr\": 0.04163331998932268\n },\n \"harness|hendrycksTest-anatomy|5\"\ : {\n \"acc\": 0.18518518518518517,\n \"acc_stderr\": 0.03355677216313142,\n\ \ \"acc_norm\": 0.18518518518518517,\n \"acc_norm_stderr\": 0.03355677216313142\n\ \ },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.17763157894736842,\n\ \ \"acc_stderr\": 0.031103182383123398,\n \"acc_norm\": 0.17763157894736842,\n\ \ \"acc_norm_stderr\": 0.031103182383123398\n },\n \"harness|hendrycksTest-business_ethics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.21509433962264152,\n\ \ \"acc_stderr\": 0.02528839450289137,\n \"acc_norm\": 0.21509433962264152,\n\ \ \"acc_norm_stderr\": 0.02528839450289137\n },\n \"harness|hendrycksTest-college_biology|5\"\ : {\n \"acc\": 0.2569444444444444,\n \"acc_stderr\": 0.03653946969442099,\n\ \ \"acc_norm\": 0.2569444444444444,\n \"acc_norm_stderr\": 0.03653946969442099\n\ \ },\n \"harness|hendrycksTest-college_chemistry|5\": {\n \"acc\":\ \ 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.2,\n\ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness|hendrycksTest-college_computer_science|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.21,\n\ \ \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n \ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-college_medicine|5\"\ : {\n \"acc\": 0.20809248554913296,\n \"acc_stderr\": 0.030952890217749874,\n\ \ \"acc_norm\": 0.20809248554913296,\n \"acc_norm_stderr\": 0.030952890217749874\n\ \ },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.21568627450980393,\n\ \ \"acc_stderr\": 0.04092563958237654,\n \"acc_norm\": 0.21568627450980393,\n\ \ \"acc_norm_stderr\": 0.04092563958237654\n },\n \"harness|hendrycksTest-computer_security|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\":\ \ 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n \"\ acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\ \ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\ acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2857142857142857,\n\ \ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\ \ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \ \ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\ acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\ acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\ acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\ \ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\ \ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \ \ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\ \ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\ acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\ acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\ acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.31390134529147984,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25925925925925924,\n\ \ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\ \ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\ \ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2905982905982906,\n\ \ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\ \ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.23754789272030652,\n\ \ \"acc_stderr\": 0.015218733046150193,\n \"acc_norm\": 0.23754789272030652,\n\ \ \"acc_norm_stderr\": 0.015218733046150193\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\ \ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.1864951768488746,\n\ \ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\ \ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\ \ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \ \ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness|hendrycksTest-public_relations|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\ \ },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.18775510204081633,\n\ \ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\ \ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness|hendrycksTest-sociology|5\"\ : {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\ \ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\ \ },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\":\ \ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-virology|5\"\ : {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\ \ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\ \ },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.3216374269005848,\n\ \ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\ \ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness|truthfulqa:mc|0\"\ : {\n \"mc1\": 1.0,\n \"mc1_stderr\": 0.0,\n \"mc2\": NaN,\n\ \ \"mc2_stderr\": NaN\n },\n \"harness|winogrande|5\": {\n \"\ acc\": 0.4956590370955012,\n \"acc_stderr\": 0.014051956064076911\n },\n\ \ \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\": 0.0\n\ \ }\n}\n```" repo_url: https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|arc:challenge|25_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-22T23-00-14.356889.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|gsm8k|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hellaswag|10_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-22T23-00-14.356889.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-management|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-22T23-00-14.356889.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|truthfulqa:mc|0_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-22T23-00-14.356889.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_22T23_00_14.356889 path: - '**/details_harness|winogrande|5_2024-01-22T23-00-14.356889.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-22T23-00-14.356889.parquet' - config_name: results data_files: - split: 2024_01_22T23_00_14.356889 path: - results_2024-01-22T23-00-14.356889.parquet - split: latest path: - results_2024-01-22T23-00-14.356889.parquet --- # Dataset Card for Evaluation run of RatanRohith/NeuralPizza-Valor-7B-Merge-slerp  Dataset automatically created during the evaluation run of model [RatanRohith/NeuralPizza-Valor-7B-Merge-slerp](https://huggingface.co/RatanRohith/NeuralPizza-Valor-7B-Merge-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-22T23:00:14.356889](https://huggingface.co/datasets/open-llm-leaderboard/details_RatanRohith__NeuralPizza-Valor-7B-Merge-slerp/blob/main/results_2024-01-22T23-00-14.356889.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": 0.23196194129343728, "acc_stderr": 0.029934654752561563, "acc_norm": 0.2314240573187148, "acc_norm_stderr": 0.03071122006512167, "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN }, "harness|arc:challenge|25": { "acc": 0.22696245733788395, "acc_stderr": 0.012240491536132861, "acc_norm": 0.22696245733788395, "acc_norm_stderr": 0.012240491536132861 }, "harness|hellaswag|10": { "acc": 0.2504481179047998, "acc_stderr": 0.004323856300539177, "acc_norm": 0.2504481179047998, "acc_norm_stderr": 0.004323856300539177 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.18518518518518517, "acc_stderr": 0.03355677216313142, "acc_norm": 0.18518518518518517, "acc_norm_stderr": 0.03355677216313142 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.17763157894736842, "acc_stderr": 0.031103182383123398, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.031103182383123398 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.21509433962264152, "acc_stderr": 0.02528839450289137, "acc_norm": 0.21509433962264152, "acc_norm_stderr": 0.02528839450289137 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.2, "acc_stderr": 0.04020151261036845, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749874, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749874 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102973, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102973 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813365, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813365 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2413793103448276, "acc_stderr": 0.03565998174135302, "acc_norm": 0.2413793103448276, "acc_norm_stderr": 0.03565998174135302 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.20899470899470898, "acc_stderr": 0.02094048156533486, "acc_norm": 0.20899470899470898, "acc_norm_stderr": 0.02094048156533486 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2857142857142857, "acc_stderr": 0.04040610178208841, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.04040610178208841 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.18, "acc_stderr": 0.038612291966536934, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.1774193548387097, "acc_stderr": 0.02173254068932927, "acc_norm": 0.1774193548387097, "acc_norm_stderr": 0.02173254068932927 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.15270935960591134, "acc_stderr": 0.02530890453938063, "acc_norm": 0.15270935960591134, "acc_norm_stderr": 0.02530890453938063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.17676767676767677, "acc_stderr": 0.027178752639044915, "acc_norm": 0.17676767676767677, "acc_norm_stderr": 0.027178752639044915 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860664, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860664 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.20256410256410257, "acc_stderr": 0.020377660970371372, "acc_norm": 0.20256410256410257, "acc_norm_stderr": 0.020377660970371372 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2111111111111111, "acc_stderr": 0.024882116857655075, "acc_norm": 0.2111111111111111, "acc_norm_stderr": 0.024882116857655075 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.21008403361344538, "acc_stderr": 0.026461398717471874, "acc_norm": 0.21008403361344538, "acc_norm_stderr": 0.026461398717471874 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.1986754966887417, "acc_stderr": 0.03257847384436776, "acc_norm": 0.1986754966887417, "acc_norm_stderr": 0.03257847384436776 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.1926605504587156, "acc_stderr": 0.016909276884936094, "acc_norm": 0.1926605504587156, "acc_norm_stderr": 0.016909276884936094 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.1527777777777778, "acc_stderr": 0.024536326026134224, "acc_norm": 0.1527777777777778, "acc_norm_stderr": 0.024536326026134224 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.31390134529147984, "acc_stderr": 0.031146796482972465, "acc_norm": 0.31390134529147984, "acc_norm_stderr": 0.031146796482972465 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.2595419847328244, "acc_stderr": 0.03844876139785271, "acc_norm": 0.2595419847328244, "acc_norm_stderr": 0.03844876139785271 }, "harness|hendrycksTest-international_law|5": { "acc": 0.2396694214876033, "acc_stderr": 0.03896878985070417, "acc_norm": 0.2396694214876033, "acc_norm_stderr": 0.03896878985070417 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.25925925925925924, "acc_stderr": 0.042365112580946336, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.042365112580946336 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.22085889570552147, "acc_stderr": 0.032591773927421776, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.032591773927421776 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness|hendrycksTest-management|5": { "acc": 0.17475728155339806, "acc_stderr": 0.037601780060266224, "acc_norm": 0.17475728155339806, "acc_norm_stderr": 0.037601780060266224 }, "harness|hendrycksTest-marketing|5": { "acc": 0.2905982905982906, "acc_stderr": 0.02974504857267404, "acc_norm": 0.2905982905982906, "acc_norm_stderr": 0.02974504857267404 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.23754789272030652, "acc_stderr": 0.015218733046150193, "acc_norm": 0.23754789272030652, "acc_norm_stderr": 0.015218733046150193 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.24855491329479767, "acc_stderr": 0.023267528432100174, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.023267528432100174 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.22549019607843138, "acc_stderr": 0.023929155517351284, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.023929155517351284 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.1864951768488746, "acc_stderr": 0.02212243977248077, "acc_norm": 0.1864951768488746, "acc_norm_stderr": 0.02212243977248077 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.21604938271604937, "acc_stderr": 0.022899162918445806, "acc_norm": 0.21604938271604937, "acc_norm_stderr": 0.022899162918445806 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.23404255319148937, "acc_stderr": 0.025257861359432417, "acc_norm": 0.23404255319148937, "acc_norm_stderr": 0.025257861359432417 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.25, "acc_stderr": 0.01751781884501444, "acc_norm": 0.25, "acc_norm_stderr": 0.01751781884501444 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03955932861795833, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03955932861795833 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness|hendrycksTest-sociology|5": { "acc": 0.24378109452736318, "acc_stderr": 0.03036049015401465, "acc_norm": 0.24378109452736318, "acc_norm_stderr": 0.03036049015401465 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-virology|5": { "acc": 0.28313253012048195, "acc_stderr": 0.03507295431370518, "acc_norm": 0.28313253012048195, "acc_norm_stderr": 0.03507295431370518 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness|truthfulqa:mc|0": { "mc1": 1.0, "mc1_stderr": 0.0, "mc2": NaN, "mc2_stderr": NaN }, "harness|winogrande|5": { "acc": 0.4956590370955012, "acc_stderr": 0.014051956064076911 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1

--- pretty_name: Evaluation run of zyh3826/llama2-13b-ft-openllm-leaderboard-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [zyh3826/llama2-13b-ft-openllm-leaderboard-v1](https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_zyh3826__llama2-13b-ft-openllm-leaderboard-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-09T15:33:42.644192](https://huggingface.co/datasets/open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1/blob/main/results_2023-12-09T15-33-42.644192.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\": 0.6016495918139398,\n\ \ \"acc_stderr\": 0.03270798736533002,\n \"acc_norm\": 0.612894192678486,\n\ \ \"acc_norm_stderr\": 0.033541474205616734,\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.40723683293857477,\n\ \ \"mc2_stderr\": 0.01336809717170015\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.552901023890785,\n \"acc_stderr\": 0.014529380160526842,\n\ \ \"acc_norm\": 0.5964163822525598,\n \"acc_norm_stderr\": 0.01433715891426844\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6276638119896435,\n\ \ \"acc_stderr\": 0.004824393076826628,\n \"acc_norm\": 0.8314080860386377,\n\ \ \"acc_norm_stderr\": 0.0037362592995204874\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952365,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952365\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5259259259259259,\n\ \ \"acc_stderr\": 0.04313531696750575,\n \"acc_norm\": 0.5259259259259259,\n\ \ \"acc_norm_stderr\": 0.04313531696750575\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.631578947368421,\n \"acc_stderr\": 0.03925523381052932,\n\ \ \"acc_norm\": 0.631578947368421,\n \"acc_norm_stderr\": 0.03925523381052932\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.55,\n\ \ \"acc_stderr\": 0.04999999999999999,\n \"acc_norm\": 0.55,\n \ \ \"acc_norm_stderr\": 0.04999999999999999\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6377358490566037,\n \"acc_stderr\": 0.029582245128384303,\n\ \ \"acc_norm\": 0.6377358490566037,\n \"acc_norm_stderr\": 0.029582245128384303\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6944444444444444,\n\ \ \"acc_stderr\": 0.03852084696008534,\n \"acc_norm\": 0.6944444444444444,\n\ \ \"acc_norm_stderr\": 0.03852084696008534\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\"\ : 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6069364161849711,\n\ \ \"acc_stderr\": 0.03724249595817731,\n \"acc_norm\": 0.6069364161849711,\n\ \ \"acc_norm_stderr\": 0.03724249595817731\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105653,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105653\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768079\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4765957446808511,\n \"acc_stderr\": 0.03265019475033582,\n\ \ \"acc_norm\": 0.4765957446808511,\n \"acc_norm_stderr\": 0.03265019475033582\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3386243386243386,\n \"acc_stderr\": 0.024373197867983056,\n \"\ acc_norm\": 0.3386243386243386,\n \"acc_norm_stderr\": 0.024373197867983056\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3968253968253968,\n\ \ \"acc_stderr\": 0.043758884927270605,\n \"acc_norm\": 0.3968253968253968,\n\ \ \"acc_norm_stderr\": 0.043758884927270605\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7193548387096774,\n\ \ \"acc_stderr\": 0.02556060472102288,\n \"acc_norm\": 0.7193548387096774,\n\ \ \"acc_norm_stderr\": 0.02556060472102288\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4975369458128079,\n \"acc_stderr\": 0.03517945038691063,\n\ \ \"acc_norm\": 0.4975369458128079,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness|hendrycksTest-high_school_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-high_school_european_history|5\"\ : {\n \"acc\": 0.7272727272727273,\n \"acc_stderr\": 0.03477691162163659,\n\ \ \"acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.03477691162163659\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8131313131313131,\n \"acc_stderr\": 0.027772533334218957,\n \"\ acc_norm\": 0.8131313131313131,\n \"acc_norm_stderr\": 0.027772533334218957\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8497409326424871,\n \"acc_stderr\": 0.025787723180723875,\n\ \ \"acc_norm\": 0.8497409326424871,\n \"acc_norm_stderr\": 0.025787723180723875\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5948717948717949,\n \"acc_stderr\": 0.024890471769938145,\n\ \ \"acc_norm\": 0.5948717948717949,\n \"acc_norm_stderr\": 0.024890471769938145\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3333333333333333,\n \"acc_stderr\": 0.02874204090394849,\n \ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.02874204090394849\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6092436974789915,\n \"acc_stderr\": 0.03169380235712996,\n \ \ \"acc_norm\": 0.6092436974789915,\n \"acc_norm_stderr\": 0.03169380235712996\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"\ acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7944954128440367,\n \"acc_stderr\": 0.017324352325016015,\n \"\ acc_norm\": 0.7944954128440367,\n \"acc_norm_stderr\": 0.017324352325016015\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.49074074074074076,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.49074074074074076,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.02584501798692692,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.02584501798692692\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8016877637130801,\n \"acc_stderr\": 0.02595502084162111,\n \ \ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.02595502084162111\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6591928251121076,\n\ \ \"acc_stderr\": 0.03181149747055359,\n \"acc_norm\": 0.6591928251121076,\n\ \ \"acc_norm_stderr\": 0.03181149747055359\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.03915345408847836,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.03915345408847836\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.03826076324884866,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.03826076324884866\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7177914110429447,\n \"acc_stderr\": 0.03536117886664742,\n\ \ \"acc_norm\": 0.7177914110429447,\n \"acc_norm_stderr\": 0.03536117886664742\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\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n\ \ \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n\ \ \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8135376756066411,\n\ \ \"acc_stderr\": 0.013927751372001505,\n \"acc_norm\": 0.8135376756066411,\n\ \ \"acc_norm_stderr\": 0.013927751372001505\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6647398843930635,\n \"acc_stderr\": 0.025416003773165538,\n\ \ \"acc_norm\": 0.6647398843930635,\n \"acc_norm_stderr\": 0.025416003773165538\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.41675977653631285,\n\ \ \"acc_stderr\": 0.016489134962438954,\n \"acc_norm\": 0.41675977653631285,\n\ \ \"acc_norm_stderr\": 0.016489134962438954\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.673202614379085,\n \"acc_stderr\": 0.026857294663281413,\n\ \ \"acc_norm\": 0.673202614379085,\n \"acc_norm_stderr\": 0.026857294663281413\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6591639871382636,\n\ \ \"acc_stderr\": 0.026920841260776165,\n \"acc_norm\": 0.6591639871382636,\n\ \ \"acc_norm_stderr\": 0.026920841260776165\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7345679012345679,\n \"acc_stderr\": 0.024569223600460845,\n\ \ \"acc_norm\": 0.7345679012345679,\n \"acc_norm_stderr\": 0.024569223600460845\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.49645390070921985,\n \"acc_stderr\": 0.02982674915328092,\n \ \ \"acc_norm\": 0.49645390070921985,\n \"acc_norm_stderr\": 0.02982674915328092\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4589308996088657,\n\ \ \"acc_stderr\": 0.012727084826799798,\n \"acc_norm\": 0.4589308996088657,\n\ \ \"acc_norm_stderr\": 0.012727084826799798\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6029411764705882,\n \"acc_stderr\": 0.029722152099280065,\n\ \ \"acc_norm\": 0.6029411764705882,\n \"acc_norm_stderr\": 0.029722152099280065\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6062091503267973,\n \"acc_stderr\": 0.019766211991073063,\n \ \ \"acc_norm\": 0.6062091503267973,\n \"acc_norm_stderr\": 0.019766211991073063\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6775510204081633,\n \"acc_stderr\": 0.02992310056368391,\n\ \ \"acc_norm\": 0.6775510204081633,\n \"acc_norm_stderr\": 0.02992310056368391\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8059701492537313,\n\ \ \"acc_stderr\": 0.027962677604768907,\n \"acc_norm\": 0.8059701492537313,\n\ \ \"acc_norm_stderr\": 0.027962677604768907\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896308,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896308\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4819277108433735,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.4819277108433735,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.783625730994152,\n \"acc_stderr\": 0.031581495393387324,\n\ \ \"acc_norm\": 0.783625730994152,\n \"acc_norm_stderr\": 0.031581495393387324\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.28151774785801714,\n\ \ \"mc1_stderr\": 0.01574402724825605,\n \"mc2\": 0.40723683293857477,\n\ \ \"mc2_stderr\": 0.01336809717170015\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7734806629834254,\n \"acc_stderr\": 0.011764149054698329\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.013646702047005308,\n \ \ \"acc_stderr\": 0.0031957470754808027\n }\n}\n```" repo_url: https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|arc:challenge|25_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-09T15-33-42.644192.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|gsm8k|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hellaswag|10_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-09T15-33-42.644192.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-management|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T15-33-42.644192.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|truthfulqa:mc|0_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-09T15-33-42.644192.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_09T15_33_42.644192 path: - '**/details_harness|winogrande|5_2023-12-09T15-33-42.644192.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-09T15-33-42.644192.parquet' - config_name: results data_files: - split: 2023_12_09T15_33_42.644192 path: - results_2023-12-09T15-33-42.644192.parquet - split: latest path: - results_2023-12-09T15-33-42.644192.parquet --- # Dataset Card for Evaluation run of zyh3826/llama2-13b-ft-openllm-leaderboard-v1 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1 - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [zyh3826/llama2-13b-ft-openllm-leaderboard-v1](https://huggingface.co/zyh3826/llama2-13b-ft-openllm-leaderboard-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_zyh3826__llama2-13b-ft-openllm-leaderboard-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-09T15:33:42.644192](https://huggingface.co/datasets/open-llm-leaderboard/details_zyh3826__llama2-13b-ft-openllm-leaderboard-v1/blob/main/results_2023-12-09T15-33-42.644192.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": 0.6016495918139398, "acc_stderr": 0.03270798736533002, "acc_norm": 0.612894192678486, "acc_norm_stderr": 0.033541474205616734, "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.40723683293857477, "mc2_stderr": 0.01336809717170015 }, "harness|arc:challenge|25": { "acc": 0.552901023890785, "acc_stderr": 0.014529380160526842, "acc_norm": 0.5964163822525598, "acc_norm_stderr": 0.01433715891426844 }, "harness|hellaswag|10": { "acc": 0.6276638119896435, "acc_stderr": 0.004824393076826628, "acc_norm": 0.8314080860386377, "acc_norm_stderr": 0.0037362592995204874 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5259259259259259, "acc_stderr": 0.04313531696750575, "acc_norm": 0.5259259259259259, "acc_norm_stderr": 0.04313531696750575 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.631578947368421, "acc_stderr": 0.03925523381052932, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.03925523381052932 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6377358490566037, "acc_stderr": 0.029582245128384303, "acc_norm": 0.6377358490566037, "acc_norm_stderr": 0.029582245128384303 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6944444444444444, "acc_stderr": 0.03852084696008534, "acc_norm": 0.6944444444444444, "acc_norm_stderr": 0.03852084696008534 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105653, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105653 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4765957446808511, "acc_stderr": 0.03265019475033582, "acc_norm": 0.4765957446808511, "acc_norm_stderr": 0.03265019475033582 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3386243386243386, "acc_stderr": 0.024373197867983056, "acc_norm": 0.3386243386243386, "acc_norm_stderr": 0.024373197867983056 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.043758884927270605, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.043758884927270605 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7193548387096774, "acc_stderr": 0.02556060472102288, "acc_norm": 0.7193548387096774, "acc_norm_stderr": 0.02556060472102288 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7272727272727273, "acc_stderr": 0.03477691162163659, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.03477691162163659 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8131313131313131, "acc_stderr": 0.027772533334218957, "acc_norm": 0.8131313131313131, "acc_norm_stderr": 0.027772533334218957 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8497409326424871, "acc_stderr": 0.025787723180723875, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.025787723180723875 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5948717948717949, "acc_stderr": 0.024890471769938145, "acc_norm": 0.5948717948717949, "acc_norm_stderr": 0.024890471769938145 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.02874204090394849, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.02874204090394849 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6092436974789915, "acc_stderr": 0.03169380235712996, "acc_norm": 0.6092436974789915, "acc_norm_stderr": 0.03169380235712996 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3841059602649007, "acc_stderr": 0.03971301814719197, "acc_norm": 0.3841059602649007, "acc_norm_stderr": 0.03971301814719197 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.7944954128440367, "acc_stderr": 0.017324352325016015, "acc_norm": 0.7944954128440367, "acc_norm_stderr": 0.017324352325016015 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.49074074074074076, "acc_stderr": 0.034093869469927006, "acc_norm": 0.49074074074074076, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8382352941176471, "acc_stderr": 0.02584501798692692, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.02584501798692692 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8016877637130801, "acc_stderr": 0.02595502084162111, "acc_norm": 0.8016877637130801, "acc_norm_stderr": 0.02595502084162111 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6591928251121076, "acc_stderr": 0.03181149747055359, "acc_norm": 0.6591928251121076, "acc_norm_stderr": 0.03181149747055359 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7251908396946565, "acc_stderr": 0.03915345408847836, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.03915345408847836 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228732, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228732 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8055555555555556, "acc_stderr": 0.03826076324884866, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.03826076324884866 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7177914110429447, "acc_stderr": 0.03536117886664742, "acc_norm": 0.7177914110429447, "acc_norm_stderr": 0.03536117886664742 }, "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": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8717948717948718, "acc_stderr": 0.02190190511507333, "acc_norm": 0.8717948717948718, "acc_norm_stderr": 0.02190190511507333 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8135376756066411, "acc_stderr": 0.013927751372001505, "acc_norm": 0.8135376756066411, "acc_norm_stderr": 0.013927751372001505 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6647398843930635, "acc_stderr": 0.025416003773165538, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.025416003773165538 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.41675977653631285, "acc_stderr": 0.016489134962438954, "acc_norm": 0.41675977653631285, "acc_norm_stderr": 0.016489134962438954 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.673202614379085, "acc_stderr": 0.026857294663281413, "acc_norm": 0.673202614379085, "acc_norm_stderr": 0.026857294663281413 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6591639871382636, "acc_stderr": 0.026920841260776165, "acc_norm": 0.6591639871382636, "acc_norm_stderr": 0.026920841260776165 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7345679012345679, "acc_stderr": 0.024569223600460845, "acc_norm": 0.7345679012345679, "acc_norm_stderr": 0.024569223600460845 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.49645390070921985, "acc_stderr": 0.02982674915328092, "acc_norm": 0.49645390070921985, "acc_norm_stderr": 0.02982674915328092 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4589308996088657, "acc_stderr": 0.012727084826799798, "acc_norm": 0.4589308996088657, "acc_norm_stderr": 0.012727084826799798 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6029411764705882, "acc_stderr": 0.029722152099280065, "acc_norm": 0.6029411764705882, "acc_norm_stderr": 0.029722152099280065 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6062091503267973, "acc_stderr": 0.019766211991073063, "acc_norm": 0.6062091503267973, "acc_norm_stderr": 0.019766211991073063 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6775510204081633, "acc_stderr": 0.02992310056368391, "acc_norm": 0.6775510204081633, "acc_norm_stderr": 0.02992310056368391 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8059701492537313, "acc_stderr": 0.027962677604768907, "acc_norm": 0.8059701492537313, "acc_norm_stderr": 0.027962677604768907 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.87, "acc_stderr": 0.03379976689896308, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896308 }, "harness|hendrycksTest-virology|5": { "acc": 0.4819277108433735, "acc_stderr": 0.038899512528272166, "acc_norm": 0.4819277108433735, "acc_norm_stderr": 0.038899512528272166 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.783625730994152, "acc_stderr": 0.031581495393387324, "acc_norm": 0.783625730994152, "acc_norm_stderr": 0.031581495393387324 }, "harness|truthfulqa:mc|0": { "mc1": 0.28151774785801714, "mc1_stderr": 0.01574402724825605, "mc2": 0.40723683293857477, "mc2_stderr": 0.01336809717170015 }, "harness|winogrande|5": { "acc": 0.7734806629834254, "acc_stderr": 0.011764149054698329 }, "harness|gsm8k|5": { "acc": 0.013646702047005308, "acc_stderr": 0.0031957470754808027 } } ``` ### 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]

Felipefloke/audiomodelo

--- license: openrail ---

Minglii/r_pv4_wiz70

--- dataset_info: features: - name: data struct: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: id dtype: string splits: - name: train num_bytes: 118128783 num_examples: 46064 download_size: 57212134 dataset_size: 118128783 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "r_pv4_wiz70" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

nyntany/REPO

--- license: openrail ---

Math47/y

--- license: openrail ---

Shularp/BDMS02_TH_AR_unchanged_with_quotation

--- dataset_info: features: - name: th dtype: string - name: ar dtype: string splits: - name: train num_bytes: 19731 num_examples: 85 download_size: 9903 dataset_size: 19731 --- # Dataset Card for "BDMS02_TH_AR_unchanged_with_quotation" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

PJMixers/coedit-reworded-deduped-multiturn-sharegpt

--- language: - en size_categories: - 1K<n<10K --- Each sample contains 1 to 32 pairs. ``` pair_lengths Minimum: 44 pair_lengths Maximum: 2573 pair_lengths Average: 1053 turn_counts Minimum: 1 turn_counts Maximum: 32 turn_counts Average: 16.5 ``` - *`pair_lengths` counted using metharme tags, and mistral tokenizer* - *`turn_counts` counted for pairs of human/gpt*

pminervini/averitec

--- dataset_info: features: - name: cached_original_claim_url dtype: string - name: speaker dtype: string - name: required_reannotation dtype: bool - name: reporting_source dtype: string - name: label dtype: string - name: claim_types sequence: string - name: fact_checking_article dtype: string - name: fact_checking_strategies sequence: string - name: claim dtype: string - name: justification dtype: string - name: location_ISO_code dtype: string - name: original_claim_url dtype: string - name: questions list: - name: answers list: - name: answer dtype: string - name: answer_type dtype: string - name: boolean_explanation dtype: string - name: cached_source_url dtype: string - name: source_medium dtype: string - name: source_url dtype: string - name: question dtype: string - name: claim_date dtype: string splits: - name: train num_bytes: 6038474 num_examples: 3068 - name: dev num_bytes: 1087211 num_examples: 500 download_size: 3363933 dataset_size: 7125685 configs: - config_name: default data_files: - split: train path: data/train-* - split: dev path: data/dev-* ---

Mihaiii/OpenHermes-2.5-1k-longest-curated

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 4176433 num_examples: 519 download_size: 1835764 dataset_size: 4176433 configs: - config_name: default data_files: - split: train path: data/train-* --- This is a dataset that was created from [HuggingFaceH4/OpenHermes-2.5-1k-longest](https://huggingface.co/datasets/HuggingFaceH4/OpenHermes-2.5-1k-longest). The purpose is to be able to use in [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) config by adding: ```yaml datasets: - path: Mihaiii/OpenHermes-2.5-1k-longest-curated type: alpaca ``` I elimininated rows that: 1) Had sys prompt (only 3 rows eliminated) 2) Contained on output a character that is repeated 10 times in a row (478 rows eliminated) So from a 1000 rows dataset, I ended up with a 519 rows dataset. See the [OpenHermes-2.5-1k-longest-curated.ipynb](https://huggingface.co/datasets/Mihaiii/OpenHermes-2.5-1k-longest-curated/blob/main/OpenHermes-2.5-1k-longest-curated.ipynb) notebook for details on how the dataset was constructed. **Later edit**: after a more in depth analysis on the dataset, I noticed that: 1) The imported subset is `test_sft`, but this is the 2nd chunk of top 1k records. The first one is in `train_sft` subset. 2) Valid code records that contained 10 repeated spaces for indentation were also eliminated.

CyberHarem/barbara_genshin

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of barbara/バーバラ/芭芭拉 (Genshin Impact) This is the dataset of barbara/バーバラ/芭芭拉 (Genshin Impact), containing 500 images and their tags. The core tags of this character are `twintails, blonde_hair, blue_eyes, long_hair, drill_hair, twin_drills, hat, bow, white_headwear, breasts, hair_ornament`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:-----------|:-----------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 500 | 1.11 GiB | [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 500 | 930.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1420 | 1.90 GiB | [Download](https://huggingface.co/datasets/CyberHarem/barbara_genshin/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/barbara_genshin', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 5 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, bare_shoulders, long_sleeves, looking_at_viewer, simple_background, smile, solo, white_background, white_dress, white_pantyhose, ass, blush, closed_mouth, detached_sleeves, looking_back, detached_collar, open_mouth | | 1 | 14 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, bare_shoulders, detached_collar, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, simple_background, smile, solo, white_dress, white_background, white_pantyhose, ;d, one_eye_closed, blush, book, frilled_dress, vision_(genshin_impact), latin_cross, strapless_dress, white_sleeves | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, :d, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, solo, white_background, white_dress, bare_shoulders, blush, book, simple_background, vision_(genshin_impact), cross | | 3 | 5 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, :d, bare_shoulders, detached_collar, hair_between_eyes, long_sleeves, looking_at_viewer, open_mouth, simple_background, solo, upper_body, white_background, white_dress, detached_sleeves, blush, cross, hand_up, teeth | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, :d, bare_shoulders, blush, detached_collar, detached_sleeves, long_sleeves, looking_at_viewer, open_mouth, solo, white_dress, sidelocks, book, blurry, hair_between_eyes, cross, white_pantyhose | | 5 | 6 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | 1girl, blue_one-piece_swimsuit, blue_sky, casual_one-piece_swimsuit, choker, cloud, day, detached_sleeves, long_sleeves, looking_at_viewer, official_alternate_costume, open_mouth, outdoors, sailor_hat, solo, thigh_strap, water, :d, duck, ocean, wading, bag, blue_sailor_collar, bowtie, hair_flower, blush | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | 1girl, blue_one-piece_swimsuit, blue_sky, casual_one-piece_swimsuit, covered_navel, day, detached_sleeves, duck, long_sleeves, looking_at_viewer, official_alternate_costume, open_mouth, outdoors, sailor_hat, smile, solo, ;d, bare_shoulders, blue_sailor_collar, blush, bowtie, choker, cloud, cowboy_shot, ocean, one_eye_closed, thigh_strap, water, animal_bag, hair_flower, sunlight, wading, yellow_bow | | 7 | 6 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | 1girl, bare_shoulders, cleavage, detached_collar, fake_animal_ears, looking_at_viewer, playboy_bunny, rabbit_ears, simple_background, solo, strapless_leotard, white_background, blush, wrist_cuffs, bowtie, sitting, alternate_costume, closed_mouth, covered_navel, medium_breasts, pantyhose, thighs, white_leotard | | 8 | 7 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | 1girl, bare_shoulders, blush, cleavage, looking_at_viewer, navel, solo, collarbone, stomach, sitting, large_breasts, medium_breasts, black_bra, black_panties, parted_lips, sidelocks, strap_slip, thighs, underwear_only, white_bra, white_panties | | 9 | 7 | ![](samples/9/clu9-sample0.png) | ![](samples/9/clu9-sample1.png) | ![](samples/9/clu9-sample2.png) | ![](samples/9/clu9-sample3.png) | ![](samples/9/clu9-sample4.png) | 1girl, alternate_costume, long_sleeves, looking_at_viewer, open_mouth, solo, blush, bowtie, pleated_skirt, white_shirt, :d, blue_skirt, school_uniform, blue_bow, collared_shirt, thighhighs, hand_up, jacket, open_clothes, simple_background, upper_teeth_only, white_pantyhose, zettai_ryouiki | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bare_shoulders | long_sleeves | looking_at_viewer | simple_background | smile | solo | white_background | white_dress | white_pantyhose | ass | blush | closed_mouth | detached_sleeves | looking_back | detached_collar | open_mouth | ;d | one_eye_closed | book | frilled_dress | vision_(genshin_impact) | latin_cross | strapless_dress | white_sleeves | :d | cross | hair_between_eyes | upper_body | hand_up | teeth | sidelocks | blurry | blue_one-piece_swimsuit | blue_sky | casual_one-piece_swimsuit | choker | cloud | day | official_alternate_costume | outdoors | sailor_hat | thigh_strap | water | duck | ocean | wading | bag | blue_sailor_collar | bowtie | hair_flower | covered_navel | cowboy_shot | animal_bag | sunlight | yellow_bow | cleavage | fake_animal_ears | playboy_bunny | rabbit_ears | strapless_leotard | wrist_cuffs | sitting | alternate_costume | medium_breasts | pantyhose | thighs | white_leotard | navel | collarbone | stomach | large_breasts | black_bra | black_panties | parted_lips | strap_slip | underwear_only | white_bra | white_panties | pleated_skirt | white_shirt | blue_skirt | school_uniform | blue_bow | collared_shirt | thighhighs | jacket | open_clothes | upper_teeth_only | zettai_ryouiki | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------------|:---------------|:--------------------|:--------------------|:--------|:-------|:-------------------|:--------------|:------------------|:------|:--------|:---------------|:-------------------|:---------------|:------------------|:-------------|:-----|:-----------------|:-------|:----------------|:--------------------------|:--------------|:------------------|:----------------|:-----|:--------|:--------------------|:-------------|:----------|:--------|:------------|:---------|:--------------------------|:-----------|:----------------------------|:---------|:--------|:------|:-----------------------------|:-----------|:-------------|:--------------|:--------|:-------|:--------|:---------|:------|:---------------------|:---------|:--------------|:----------------|:--------------|:-------------|:-----------|:-------------|:-----------|:-------------------|:----------------|:--------------|:--------------------|:--------------|:----------|:--------------------|:-----------------|:------------|:---------|:----------------|:--------|:-------------|:----------|:----------------|:------------|:----------------|:--------------|:-------------|:-----------------|:------------|:----------------|:----------------|:--------------|:-------------|:-----------------|:-----------|:-----------------|:-------------|:---------|:---------------|:-------------------|:-----------------| | 0 | 5 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 14 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | X | X | X | X | X | X | X | | X | | X | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | X | X | | X | X | X | | | X | | X | | | X | | | X | | X | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 5 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | X | X | X | X | | X | X | X | | | X | | X | | X | X | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | X | X | X | | | X | | X | X | | X | | X | | X | X | | | X | | | | | | X | X | X | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 6 | 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uetchy/thesession

--- license: odbl ---

hayden-donnelly/remilio

--- license: other license_name: viral-public-license license_link: LICENSE size_categories: - 1K<n<10K task_categories: - image-classification - unconditional-image-generation - text-to-image language: - en pretty_name: Remilio --- # Remilio [Redacted Remilio Babies](https://remilio.org/) is a collection of 10,000 neochibi pfpNFT's evolving the proven Milady Maker paradigm with the introduction of young J.I.T. energy, schizophrenic reactionary aesthetics, and digital sales terrorism. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/643ae6350e5495afdefb26e1/18r2_9iN3SmU-ME_He31N.png)

Aruno/guanaco_jp

--- license: apache-2.0 task_categories: - text-generation language: - ja pretty_name: Guanaco Japanese Prompt --- Japanese Prompt of [GuanacoDataset](https://huggingface.co/datasets/JosephusCheung/GuanacoDataset) extracted using `langdetect`.

wenzhuoliu/MOOC_Answer_Reformulation

--- dataset_info: config_name: Query_Answers features: - name: query dtype: string - name: input_docs sequence: string - name: gpt_answer dtype: string splits: - name: religion num_bytes: 162873 num_examples: 124 - name: python num_bytes: 84949 num_examples: 79 - name: history num_bytes: 50557 num_examples: 58 - name: recherche_reproductible num_bytes: 59372 num_examples: 52 download_size: 488352 dataset_size: 408308 configs: - config_name: Query_Answers data_files: - split: history path: Query_Answers/history-* - split: religion path: Query_Answers/religion-* - split: recherche_reproductible path: Query_Answers/recherche_reproductible-* - split: python path: Query_Answers/python-* ---

cogumelo22/cogumelo22

--- license: openrail ---

Arthur91284/Arthur91284

--- license: openrail ---

lilacai/lilac-dolphin

--- tags: - Lilac --- # lilac/dolphin This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/cognitivecomputations/dolphin](https://huggingface.co/datasets/cognitivecomputations/dolphin) To download the dataset to a local directory: ```bash lilac download lilacai/lilac-dolphin ``` or from python with: ```py ll.download("lilacai/lilac-dolphin") ```

pvduy/ultra-mix-7k-code

--- dataset_info: features: - name: chosen list: - name: content dtype: string - name: role dtype: string - name: rejected list: - name: content dtype: string - name: role dtype: string - name: content dtype: string - name: is_code dtype: bool splits: - name: train num_bytes: 71828083 num_examples: 8228 download_size: 33892874 dataset_size: 71828083 configs: - config_name: default data_files: - split: train path: data/train-* ---

Gabriel1322/xit

--- license: openrail ---

sohonjit/brats2023_multidomain_i2i

--- license: mit task_categories: - image-to-image language: - en tags: - medical --- ## Dataset Description - **Paper:** Under Review. - **Point of Contact:** Arijit Ghosh, arijit.ghosh@fau.de ### Dataset Summary This dataset is based on the BraTS2023 dataset and is supposed to be used for Multi-domain Image-to-Image Translation task. It takes 5 middle slices from each nifti volume of the BraTS2023 dataset after normalizing to a value of (-1,1). All of these images are `.npy` files and one can load them using the `np.load(FILEPATH).astype(np.float32)`. We provide the training and the test set which contains 6255 and 1095 files respectively for each domain. These are actually 4 domains, and are named accordingly. It is highly recommend to create a separate validation set from the training dataset for applications. We use `Pytorch` to do this. We do this by using the following command. ```python seed = 97 train_dataset, val_dataset = torch.utils.data.random_split( dataset, lengths=(0.9, 0.1), generator=torch.Generator().manual_seed(seed) ) # dataset is the dataset instance. ``` This dataset is actually part of a paper which is under peer-review currently. We hope this helps the community.

bigscience-data/roots_eu_wikibooks

--- language: eu license: cc-by-sa-3.0 extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience Ethical Charter. The charter can be found at: https://hf.co/spaces/bigscience/ethical-charter' extra_gated_fields: I have read and agree to abide by the BigScience Ethical Charter: checkbox --- ROOTS Subset: roots_eu_wikibooks # wikibooks_filtered - Dataset uid: `wikibooks_filtered` ### Description ### Homepage ### Licensing ### Speaker Locations ### Sizes - 0.0897 % of total - 0.2591 % of en - 0.0965 % of fr - 0.1691 % of es - 0.2834 % of indic-hi - 0.2172 % of pt - 0.0149 % of zh - 0.0279 % of ar - 0.1374 % of vi - 0.5025 % of id - 0.3694 % of indic-ur - 0.5744 % of eu - 0.0769 % of ca - 0.0519 % of indic-ta - 0.1470 % of indic-mr - 0.0751 % of indic-te - 0.0156 % of indic-bn - 0.0476 % of indic-ml - 0.0087 % of indic-pa ### BigScience processing steps #### Filters applied to: en - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_en - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: fr - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_fr - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: es - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_es - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: indic-hi - dedup_document - filter_remove_empty_docs - split_sentences_indic-hi - dedup_template_soft - filter_small_docs_bytes_300 #### Filters applied to: pt - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_pt - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: zh - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_zhs - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: ar - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_ar - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: vi - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_vi - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: id - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_id - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-ur - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - dedup_template_soft - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: eu - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_eu - dedup_template_soft - replace_newline_with_space #### Filters applied to: ca - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_ca - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: indic-ta - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-ta - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-mr - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-mr - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-te - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-te - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-bn - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-bn - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-ml - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-ml - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-pa - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-pa - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300

nikchar/konstantinaki_paper_test_top_5

--- dataset_info: features: - name: label dtype: string - name: claim dtype: string - name: evidence_wiki_url dtype: string - name: text dtype: string - name: retrieved_evidence sequence: string - name: retrieved_evidence_text sequence: string splits: - name: train num_bytes: 50870680 num_examples: 11073 download_size: 21296684 dataset_size: 50870680 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "konstantinaki_paper_test_top_5" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

akkang321/testlecode

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5818 num_examples: 30 download_size: 3673 dataset_size: 5818 configs: - config_name: default data_files: - split: train path: data/train-* ---

amd-nicknick/bert-base-uncased-2022_tokenized_dataset

--- dataset_info: features: - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 - name: special_tokens_mask sequence: int8 splits: - name: train num_bytes: 25352412298 num_examples: 80462898 download_size: 6782996622 dataset_size: 25352412298 configs: - config_name: default data_files: - split: train path: data/train-* ---

avaliev/drugchat

--- license: bsd-3-clause task_categories: - question-answering language: - en tags: - biology - chemistry - medical pretty_name: DrugChat Dataset size_categories: - 10K<n<100K --- This dataset is for the "DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs" paper. @article{liang2023drugchat, title={DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs}, author={Liang, Youwei and Zhang, Ruiyi and Zhang, li and Xie, Pengtao}, journal={TechRxiv}, year={2023} } There are no changes in data; only added datasets class to download the set from HF and generate split from data in .json files.

hzydashi/KatagoExceptGo

--- license: mit tags: - alphago - alphazero - board games - gomoku - katago - NNUE - Stockfish size_categories: - 100M<n<1B ---

Iftitahu/sundanese_instruct_stories

--- license: cc-by-4.0 task_categories: - translation - text-generation - text2text-generation language: - id - jv - su - en size_categories: - n<1K --- A dataset of parallel translation-based instructions for Sundanese language as a target language. Materials are taken from randomly selected children stories at https://storyweaver.org.in, under CC-By-SA-4.0 license. The template IDs are: (1, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Inggris kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'), (2, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Indonesia kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'), (3, 'Tarjamahkeun teks dongeng barudak di handap tina teks basa Jawa kana teks basa Sunda:', 'Tarjamahan atawa sasaruaan naskah dina basa Sunda:'), Data is mainly composed of three parallel language samples as prompt inputs and target completions: 1. en_sunda Prompt/instruction language: Sundanese Source/input language:English Target/output language:Sundanese Size: 94 samples. Prompt Template: inputs: Tarjamahkeun teks dongeng barudak di handap tina teks basa Inggris kana teks basa Sunda:\n\n{input}\n\n targets: Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output} 2. id_sunda Prompt/instruction language: Sundanese Source/input language: Indonesia Target/output language:Sundanese Size: 94 samples. Prompt Template: inputs: Tarjamahkeun teks dongeng barudak di handap tina teks basa Indonesia kana teks basa Sunda:\n\n{input}\n\n targets: Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output} 3. javanese_sunda Prompt/instruction language: Sundanese Source/input language: Javanese Target/output language: Sundanese Size: 20 samples. Prompt Template: inputs: Tarjamahkeun teks dongeng barudak di handap tina teks basa Jawa kana teks basa Sunda:\n\n{input}\n\n targets: Tarjamahan atawa sasaruaan naskah dina basa Sunda:\n\n{output} Data was originally prepared for enriching multilingual resources in Open Science AYA Project (2023).

CorpuSlave/expertise_1

--- license: cc-by-nc-sa-4.0 configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string - name: doc_id dtype: string splits: - name: train num_bytes: 8027905291 num_examples: 1379830 download_size: 3070150673 dataset_size: 8027905291 ---

tomaarsen/setfit-absa-semeval-restaurants

--- dataset_info: features: - name: text dtype: string - name: span dtype: string - name: label dtype: string - name: ordinal dtype: int64 splits: - name: train num_bytes: 490223 num_examples: 3693 - name: test num_bytes: 138187 num_examples: 1134 download_size: 193352 dataset_size: 628410 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "tomaarsen/setfit-absa-semeval-restaurants" ### Dataset Summary This dataset contains the manually annotated restaurant reviews from SemEval-2014 Task 4, in the format as understood by [SetFit](https://github.com/huggingface/setfit) ABSA. For more details, see https://aclanthology.org/S14-2004/ ### Data Instances An example of "train" looks as follows. ```json {"text": "But the staff was so horrible to us.", "span": "staff", "label": "negative", "ordinal": 0} {"text": "To be completely fair, the only redeeming factor was the food, which was above average, but couldn't make up for all the other deficiencies of Teodora.", "span": "food", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "food", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "kitchen", "label": "positive", "ordinal": 0} {"text": "The food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not.", "span": "menu", "label": "neutral", "ordinal": 0} ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. - `span`: a `string` feature showing the aspect span from the text. - `label`: a `string` feature showing the polarity of the aspect span. - `ordinal`: an `int64` feature showing the n-th occurrence of the span in the text. This is useful for if the span occurs within the same text multiple times. ### Data Splits | name |train|test| |---------|----:|---:| |tomaarsen/setfit-absa-semeval-restaurants|3693|1134| ### Training ABSA models using SetFit ABSA To train using this dataset, first install the SetFit library: ```bash pip install setfit ``` And then you can use the following script as a guideline of how to train an ABSA model on this dataset: ```python from setfit import AbsaModel, AbsaTrainer, TrainingArguments from datasets import load_dataset from transformers import EarlyStoppingCallback # You can initialize a AbsaModel using one or two SentenceTransformer models, or two ABSA models model = AbsaModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2") # The training/eval dataset must have `text`, `span`, `polarity`, and `ordinal` columns dataset = load_dataset("tomaarsen/setfit-absa-semeval-restaurants") train_dataset = dataset["train"] eval_dataset = dataset["test"] args = TrainingArguments( output_dir="models", use_amp=True, batch_size=256, eval_steps=50, save_steps=50, load_best_model_at_end=True, ) trainer = AbsaTrainer( model, args=args, train_dataset=train_dataset, eval_dataset=eval_dataset, callbacks=[EarlyStoppingCallback(early_stopping_patience=5)], ) trainer.train() metrics = trainer.evaluate(eval_dataset) print(metrics) trainer.push_to_hub("tomaarsen/setfit-absa-restaurants") ``` You can then run inference like so: ```python from setfit import AbsaModel # Download from Hub and run inference model = AbsaModel.from_pretrained( "tomaarsen/setfit-absa-restaurants-aspect", "tomaarsen/setfit-absa-restaurants-polarity", ) # Run inference preds = model([ "The best pizza outside of Italy and really tasty.", "The food here is great but the service is terrible", ]) ``` ### Citation Information ```bibtex @inproceedings{pontiki-etal-2014-semeval, title = "{S}em{E}val-2014 Task 4: Aspect Based Sentiment Analysis", author = "Pontiki, Maria and Galanis, Dimitris and Pavlopoulos, John and Papageorgiou, Harris and Androutsopoulos, Ion and Manandhar, Suresh", editor = "Nakov, Preslav and Zesch, Torsten", booktitle = "Proceedings of the 8th International Workshop on Semantic Evaluation ({S}em{E}val 2014)", month = aug, year = "2014", address = "Dublin, Ireland", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/S14-2004", doi = "10.3115/v1/S14-2004", pages = "27--35", } ```

open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1

--- pretty_name: Evaluation run of mlabonne/GML-Mistral-merged-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mlabonne/GML-Mistral-merged-v1](https://huggingface.co/mlabonne/GML-Mistral-merged-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_mlabonne__GML-Mistral-merged-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T10:46:26.609299](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1/blob/main/results_2023-12-29T10-46-26.609299.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\": 0.6238015653000757,\n\ \ \"acc_stderr\": 0.03193933734157293,\n \"acc_norm\": 0.6367462570659438,\n\ \ \"acc_norm_stderr\": 0.032818108624919226,\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148125,\n \"mc2\": 0.5157810759126963,\n\ \ \"mc2_stderr\": 0.01645251270460575\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.3993174061433447,\n \"acc_stderr\": 0.0143120945579467,\n\ \ \"acc_norm\": 0.4377133105802048,\n \"acc_norm_stderr\": 0.014497573881108294\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.3623780123481378,\n\ \ \"acc_stderr\": 0.0047970481548939665,\n \"acc_norm\": 0.578868751244772,\n\ \ \"acc_norm_stderr\": 0.0049273147294335564\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047423976,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047423976\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119669,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119669\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.61,\n\ \ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7169811320754716,\n \"acc_stderr\": 0.027724236492700918,\n\ \ \"acc_norm\": 0.7169811320754716,\n \"acc_norm_stderr\": 0.027724236492700918\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\ \ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\ \ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|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-college_computer_science|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-college_mathematics|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6589595375722543,\n\ \ \"acc_stderr\": 0.03614665424180826,\n \"acc_norm\": 0.6589595375722543,\n\ \ \"acc_norm_stderr\": 0.03614665424180826\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.048786087144669955,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.048786087144669955\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n\ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.548936170212766,\n \"acc_stderr\": 0.032529096196131965,\n\ \ \"acc_norm\": 0.548936170212766,\n \"acc_norm_stderr\": 0.032529096196131965\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\": 0.5586206896551724,\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\"\ : 0.4312169312169312,\n \"acc_stderr\": 0.02550648169813821,\n \"\ acc_norm\": 0.4312169312169312,\n \"acc_norm_stderr\": 0.02550648169813821\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7774193548387097,\n\ \ \"acc_stderr\": 0.023664216671642518,\n \"acc_norm\": 0.7774193548387097,\n\ \ \"acc_norm_stderr\": 0.023664216671642518\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5172413793103449,\n \"acc_stderr\": 0.035158955511656986,\n\ \ \"acc_norm\": 0.5172413793103449,\n \"acc_norm_stderr\": 0.035158955511656986\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\ : 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\ acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9067357512953368,\n \"acc_stderr\": 0.020986854593289733,\n\ \ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.020986854593289733\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.023901157979402534,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.023901157979402534\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6512605042016807,\n \"acc_stderr\": 0.030956636328566545,\n\ \ \"acc_norm\": 0.6512605042016807,\n \"acc_norm_stderr\": 0.030956636328566545\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33112582781456956,\n \"acc_stderr\": 0.038425817186598696,\n \"\ acc_norm\": 0.33112582781456956,\n \"acc_norm_stderr\": 0.038425817186598696\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8513761467889909,\n \"acc_stderr\": 0.015251253773660836,\n \"\ acc_norm\": 0.8513761467889909,\n \"acc_norm_stderr\": 0.015251253773660836\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.47685185185185186,\n \"acc_stderr\": 0.03406315360711507,\n \"\ acc_norm\": 0.47685185185185186,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078962,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078962\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601446,\n \ \ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601446\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159463,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159463\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8099173553719008,\n \"acc_stderr\": 0.03581796951709282,\n \"\ acc_norm\": 0.8099173553719008,\n \"acc_norm_stderr\": 0.03581796951709282\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8675213675213675,\n\ \ \"acc_stderr\": 0.02220930907316562,\n \"acc_norm\": 0.8675213675213675,\n\ \ \"acc_norm_stderr\": 0.02220930907316562\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8250319284802043,\n\ \ \"acc_stderr\": 0.01358661921990334,\n \"acc_norm\": 0.8250319284802043,\n\ \ \"acc_norm_stderr\": 0.01358661921990334\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3888268156424581,\n\ \ \"acc_stderr\": 0.01630389953079613,\n \"acc_norm\": 0.3888268156424581,\n\ \ \"acc_norm_stderr\": 0.01630389953079613\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7156862745098039,\n \"acc_stderr\": 0.025829163272757482,\n\ \ \"acc_norm\": 0.7156862745098039,\n \"acc_norm_stderr\": 0.025829163272757482\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7170418006430869,\n\ \ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\ \ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\ : 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \"\ acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46740547588005216,\n\ \ \"acc_stderr\": 0.01274307294265335,\n \"acc_norm\": 0.46740547588005216,\n\ \ \"acc_norm_stderr\": 0.01274307294265335\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6801470588235294,\n \"acc_stderr\": 0.02833295951403121,\n\ \ \"acc_norm\": 0.6801470588235294,\n \"acc_norm_stderr\": 0.02833295951403121\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6715686274509803,\n \"acc_stderr\": 0.018999707383162673,\n \ \ \"acc_norm\": 0.6715686274509803,\n \"acc_norm_stderr\": 0.018999707383162673\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7510204081632653,\n \"acc_stderr\": 0.027682979522960234,\n\ \ \"acc_norm\": 0.7510204081632653,\n \"acc_norm_stderr\": 0.027682979522960234\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8557213930348259,\n\ \ \"acc_stderr\": 0.024845753212306046,\n \"acc_norm\": 0.8557213930348259,\n\ \ \"acc_norm_stderr\": 0.024845753212306046\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148125,\n \"mc2\": 0.5157810759126963,\n\ \ \"mc2_stderr\": 0.01645251270460575\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7387529597474349,\n \"acc_stderr\": 0.0123469148634153\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/mlabonne/GML-Mistral-merged-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|arc:challenge|25_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-29T10-46-26.609299.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|gsm8k|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hellaswag|10_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T10-46-26.609299.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T10-46-26.609299.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T10-46-26.609299.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T10_46_26.609299 path: - '**/details_harness|winogrande|5_2023-12-29T10-46-26.609299.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-29T10-46-26.609299.parquet' - config_name: results data_files: - split: 2023_12_29T10_46_26.609299 path: - results_2023-12-29T10-46-26.609299.parquet - split: latest path: - results_2023-12-29T10-46-26.609299.parquet --- # Dataset Card for Evaluation run of mlabonne/GML-Mistral-merged-v1  Dataset automatically created during the evaluation run of model [mlabonne/GML-Mistral-merged-v1](https://huggingface.co/mlabonne/GML-Mistral-merged-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_mlabonne__GML-Mistral-merged-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T10:46:26.609299](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__GML-Mistral-merged-v1/blob/main/results_2023-12-29T10-46-26.609299.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": 0.6238015653000757, "acc_stderr": 0.03193933734157293, "acc_norm": 0.6367462570659438, "acc_norm_stderr": 0.032818108624919226, "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148125, "mc2": 0.5157810759126963, "mc2_stderr": 0.01645251270460575 }, "harness|arc:challenge|25": { "acc": 0.3993174061433447, "acc_stderr": 0.0143120945579467, "acc_norm": 0.4377133105802048, "acc_norm_stderr": 0.014497573881108294 }, "harness|hellaswag|10": { "acc": 0.3623780123481378, "acc_stderr": 0.0047970481548939665, "acc_norm": 0.578868751244772, "acc_norm_stderr": 0.0049273147294335564 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047423976, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047423976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119669, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119669 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7169811320754716, "acc_stderr": 0.027724236492700918, "acc_norm": 0.7169811320754716, "acc_norm_stderr": 0.027724236492700918 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6589595375722543, "acc_stderr": 0.03614665424180826, "acc_norm": 0.6589595375722543, "acc_norm_stderr": 0.03614665424180826 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.548936170212766, "acc_stderr": 0.032529096196131965, "acc_norm": 0.548936170212766, "acc_norm_stderr": 0.032529096196131965 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4312169312169312, "acc_stderr": 0.02550648169813821, "acc_norm": 0.4312169312169312, "acc_norm_stderr": 0.02550648169813821 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7774193548387097, "acc_stderr": 0.023664216671642518, "acc_norm": 0.7774193548387097, "acc_norm_stderr": 0.023664216671642518 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5172413793103449, "acc_stderr": 0.035158955511656986, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.035158955511656986 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586815, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586815 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9067357512953368, "acc_stderr": 0.020986854593289733, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.020986854593289733 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6666666666666666, "acc_stderr": 0.023901157979402534, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.023901157979402534 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340492, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340492 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6512605042016807, "acc_stderr": 0.030956636328566545, "acc_norm": 0.6512605042016807, "acc_norm_stderr": 0.030956636328566545 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33112582781456956, "acc_stderr": 0.038425817186598696, "acc_norm": 0.33112582781456956, "acc_norm_stderr": 0.038425817186598696 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8513761467889909, "acc_stderr": 0.015251253773660836, "acc_norm": 0.8513761467889909, "acc_norm_stderr": 0.015251253773660836 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.47685185185185186, "acc_stderr": 0.03406315360711507, "acc_norm": 0.47685185185185186, "acc_norm_stderr": 0.03406315360711507 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078962, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078962 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7974683544303798, "acc_stderr": 0.026160568246601446, "acc_norm": 0.7974683544303798, "acc_norm_stderr": 0.026160568246601446 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159463, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159463 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8099173553719008, "acc_stderr": 0.03581796951709282, "acc_norm": 0.8099173553719008, "acc_norm_stderr": 0.03581796951709282 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7791411042944786, "acc_stderr": 0.03259177392742178, "acc_norm": 0.7791411042944786, "acc_norm_stderr": 0.03259177392742178 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness|hendrycksTest-management|5": { "acc": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8675213675213675, "acc_stderr": 0.02220930907316562, "acc_norm": 0.8675213675213675, "acc_norm_stderr": 0.02220930907316562 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8250319284802043, "acc_stderr": 0.01358661921990334, "acc_norm": 0.8250319284802043, "acc_norm_stderr": 0.01358661921990334 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3888268156424581, "acc_stderr": 0.01630389953079613, "acc_norm": 0.3888268156424581, "acc_norm_stderr": 0.01630389953079613 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7156862745098039, "acc_stderr": 0.025829163272757482, "acc_norm": 0.7156862745098039, "acc_norm_stderr": 0.025829163272757482 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7170418006430869, "acc_stderr": 0.02558306248998481, "acc_norm": 0.7170418006430869, "acc_norm_stderr": 0.02558306248998481 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46740547588005216, "acc_stderr": 0.01274307294265335, "acc_norm": 0.46740547588005216, "acc_norm_stderr": 0.01274307294265335 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6801470588235294, "acc_stderr": 0.02833295951403121, "acc_norm": 0.6801470588235294, "acc_norm_stderr": 0.02833295951403121 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6715686274509803, "acc_stderr": 0.018999707383162673, "acc_norm": 0.6715686274509803, "acc_norm_stderr": 0.018999707383162673 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7510204081632653, "acc_stderr": 0.027682979522960234, "acc_norm": 0.7510204081632653, "acc_norm_stderr": 0.027682979522960234 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8557213930348259, "acc_stderr": 0.024845753212306046, "acc_norm": 0.8557213930348259, "acc_norm_stderr": 0.024845753212306046 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness|hendrycksTest-virology|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640044, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640044 }, "harness|truthfulqa:mc|0": { "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148125, "mc2": 0.5157810759126963, "mc2_stderr": 0.01645251270460575 }, "harness|winogrande|5": { "acc": 0.7387529597474349, "acc_stderr": 0.0123469148634153 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

CyberHarem/anastasia_hoshin_rezero

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of anastasia_hoshin (Re:Zero Kara Hajimeru Isekai Seikatsu) This is the dataset of anastasia_hoshin (Re:Zero Kara Hajimeru Isekai Seikatsu), containing 56 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).

wefussell/amasum-final-test

--- license: mit ---

thomasavare/waste-classification-audio-deepl

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio dtype: audio - name: speaker dtype: string - name: transcription dtype: string - name: translation dtype: string - name: Class dtype: string - name: Class_index dtype: float64 splits: - name: train num_bytes: 397554225.0 num_examples: 500 download_size: 300753479 dataset_size: 397554225.0 --- # Dataset Card for "waste-classification-audio-deepl" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

marasaki/github-issues

--- dataset_info: features: - name: url dtype: string - name: repository_url dtype: string - name: labels_url dtype: string - name: comments_url dtype: string - name: events_url dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: user struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: labels list: - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: id dtype: int64 - name: name dtype: string - name: node_id dtype: string - name: url dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: assignees list: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: milestone struct: - name: closed_at dtype: string - name: closed_issues dtype: int64 - name: created_at dtype: string - name: creator struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: description dtype: string - name: due_on dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: labels_url dtype: string - name: node_id dtype: string - name: number dtype: int64 - name: open_issues dtype: int64 - name: state dtype: string - name: title dtype: string - name: updated_at dtype: string - name: url dtype: string - name: comments sequence: string - name: created_at dtype: timestamp[ns, tz=UTC] - name: updated_at dtype: timestamp[ns, tz=UTC] - name: closed_at dtype: timestamp[ns, tz=UTC] - name: author_association dtype: string - name: active_lock_reason dtype: float64 - name: draft dtype: float64 - name: pull_request struct: - name: diff_url dtype: string - name: html_url dtype: string - name: merged_at dtype: string - name: patch_url dtype: string - name: url dtype: string - name: body dtype: string - name: reactions struct: - name: '+1' dtype: int64 - name: '-1' dtype: int64 - name: confused dtype: int64 - name: eyes dtype: int64 - name: heart dtype: int64 - name: hooray dtype: int64 - name: laugh dtype: int64 - name: rocket dtype: int64 - name: total_count dtype: int64 - name: url dtype: string - name: timeline_url dtype: string - name: performed_via_github_app dtype: float64 - name: state_reason dtype: string - name: is_pull_request dtype: bool splits: - name: train num_bytes: 17110932 num_examples: 3000 download_size: 5364770 dataset_size: 17110932 configs: - config_name: default data_files: - split: train path: data/train-* license: unknown task_categories: - text-classification - token-classification language: - en pretty_name: GitHub Issues Small size_categories: - 1K<n<10K --- # Dataset Card for "github-issues" [Hugging Face NLP Course 5章5節]https://huggingface.co/learn/nlp-course/chapter5/5?fw=pt)で作ったGitHubのイシューをスクレイピングしたデータセットです。

jlbaker361/wikiart-balanced500

--- dataset_info: features: - name: image dtype: image - name: text dtype: string - name: style dtype: string - name: name dtype: string - name: gen_style dtype: string splits: - name: train num_bytes: 457748372.7 num_examples: 12150 - name: test num_bytes: 51892420.75 num_examples: 1350 download_size: 512269037 dataset_size: 509640793.45 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

TiagoJacobs/lamma2-bigbluebutton

--- license: apache-2.0 ---

DamarJati/GreenLabel-Waste-Types

--- viewer: true task_categories: - text-classification language: - en pretty_name: GreenLabel-Waste-Types size_categories: - 10K<n<100K --- Original Datasets: https://www.kaggle.com/datasets/techsash/waste-classification-data?select=DATASET

Intuit-GenSRF/sexting-nsfw-adultconten-es

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string - name: labels sequence: string - name: processed_text sequence: string - name: text_es dtype: string splits: - name: train num_bytes: 89678 num_examples: 538 download_size: 0 dataset_size: 89678 --- # Dataset Card for "sexting-nsfw-adultconten-es" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Slapping/FlowCharts

--- license: mit ---

TREC-AToMiC/AToMiC-Images-v0.1

--- license: other dataset_info: features: - name: image_id dtype: string - name: image_url dtype: string - name: caption_reference_description sequence: string - name: caption_attribution_description sequence: string - name: caption_alt_text_description sequence: string - name: image dtype: image splits: - name: train num_bytes: 56792080050.0 num_examples: 3723512 - name: validation num_bytes: 458681067.375 num_examples: 30365 - name: test num_bytes: 316081601.5 num_examples: 20732 download_size: 57119923069 dataset_size: 57566842718.875 --- ## Licensing Information In exchange for permission to use the AToMiC database (the "Database") at TREC-AToMiC, Researcher hereby agrees to the following terms and conditions: 1. Researcher shall use the Database only for non-commercial research and educational purposes. 2. TREC-AToMiC makes no representations or warranties regarding the Database, including but not limited to warranties of non-infringement or fitness for a particular purpose. 3. Researcher accepts full responsibility for his or her use of the Database and shall defend and indemnify the TREC-AToMiC team including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Database, including but not limited to Researcher's use of any copies of copyrighted images that he or she may create from the Database. 4. Researcher may provide research associates and colleagues with access to the Database provided that they first agree to be bound by these terms and conditions. 5. TREC-AToMiC reserve the right to terminate Researcher's access to the Database at any time. 6. If Researcher is employed by a for-profit, commercial entity, Researcher's employer shall also be bound by these terms and conditions, and Researcher hereby represents that he or she is fully authorized to enter into this agreement on behalf of such employer.

mikkaelmoura/myllakarvalho1

--- license: openrail ---

CyberHarem/tilty_claret_tenseioujototensaireijounomahoukakumei

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Tilty Claret This is the dataset of Tilty Claret, containing 147 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 147 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 288 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 147 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 147 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 147 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 147 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 147 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 288 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 288 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 288 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |

vilm/viet-pretrained-002

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 4502549932 num_examples: 258823 download_size: 2324002719 dataset_size: 4502549932 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "viet-pretrained-002" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_haoranxu__ALMA-7B

--- pretty_name: Evaluation run of haoranxu/ALMA-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [haoranxu/ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_haoranxu__ALMA-7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-09T14:49:25.025957](https://huggingface.co/datasets/open-llm-leaderboard/details_haoranxu__ALMA-7B/blob/main/results_2023-12-09T14-49-25.025957.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\": 0.3842750602900277,\n\ \ \"acc_stderr\": 0.0337414380010653,\n \"acc_norm\": 0.388832150301939,\n\ \ \"acc_norm_stderr\": 0.03466152745310896,\n \"mc1\": 0.2350061199510404,\n\ \ \"mc1_stderr\": 0.014843061507731613,\n \"mc2\": 0.3564384771875291,\n\ \ \"mc2_stderr\": 0.013567943486529975\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.47013651877133106,\n \"acc_stderr\": 0.0145853058400071,\n\ \ \"acc_norm\": 0.5034129692832765,\n \"acc_norm_stderr\": 0.014611050403244081\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5642302330213105,\n\ \ \"acc_stderr\": 0.004948439229523914,\n \"acc_norm\": 0.7550288787094205,\n\ \ \"acc_norm_stderr\": 0.004291911350430712\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.42962962962962964,\n\ \ \"acc_stderr\": 0.04276349494376599,\n \"acc_norm\": 0.42962962962962964,\n\ \ \"acc_norm_stderr\": 0.04276349494376599\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\": 0.44,\n\ \ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.44,\n \ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.37358490566037733,\n \"acc_stderr\": 0.02977308271331987,\n\ \ \"acc_norm\": 0.37358490566037733,\n \"acc_norm_stderr\": 0.02977308271331987\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3541666666666667,\n\ \ \"acc_stderr\": 0.039994111357535424,\n \"acc_norm\": 0.3541666666666667,\n\ \ \"acc_norm_stderr\": 0.039994111357535424\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816506,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816506\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n\ \ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816508,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816508\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3468208092485549,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.3468208092485549,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.18627450980392157,\n \"acc_stderr\": 0.038739587141493524,\n\ \ \"acc_norm\": 0.18627450980392157,\n \"acc_norm_stderr\": 0.038739587141493524\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.51,\n \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.51,\n\ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.3872340425531915,\n \"acc_stderr\": 0.03184389265339525,\n\ \ \"acc_norm\": 0.3872340425531915,\n \"acc_norm_stderr\": 0.03184389265339525\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2719298245614035,\n\ \ \"acc_stderr\": 0.04185774424022056,\n \"acc_norm\": 0.2719298245614035,\n\ \ \"acc_norm_stderr\": 0.04185774424022056\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04082482904638629,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04082482904638629\n },\n\ \ \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.26455026455026454,\n\ \ \"acc_stderr\": 0.022717467897708617,\n \"acc_norm\": 0.26455026455026454,\n\ \ \"acc_norm_stderr\": 0.022717467897708617\n },\n \"harness|hendrycksTest-formal_logic|5\"\ : {\n \"acc\": 0.19047619047619047,\n \"acc_stderr\": 0.035122074123020514,\n\ \ \"acc_norm\": 0.19047619047619047,\n \"acc_norm_stderr\": 0.035122074123020514\n\ \ },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.37,\n\ \ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.37,\n \ \ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness|hendrycksTest-high_school_biology|5\"\ : {\n \"acc\": 0.36129032258064514,\n \"acc_stderr\": 0.027327548447957543,\n\ \ \"acc_norm\": 0.36129032258064514,\n \"acc_norm_stderr\": 0.027327548447957543\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.33497536945812806,\n \"acc_stderr\": 0.0332085274234831,\n \"\ acc_norm\": 0.33497536945812806,\n \"acc_norm_stderr\": 0.0332085274234831\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\"\ : 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.43636363636363634,\n \"acc_stderr\": 0.03872592983524753,\n\ \ \"acc_norm\": 0.43636363636363634,\n \"acc_norm_stderr\": 0.03872592983524753\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.398989898989899,\n \"acc_stderr\": 0.03488901616852731,\n \"acc_norm\"\ : 0.398989898989899,\n \"acc_norm_stderr\": 0.03488901616852731\n },\n\ \ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \ \ \"acc\": 0.48186528497409326,\n \"acc_stderr\": 0.036060650018329185,\n\ \ \"acc_norm\": 0.48186528497409326,\n \"acc_norm_stderr\": 0.036060650018329185\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.34615384615384615,\n \"acc_stderr\": 0.024121125416941187,\n\ \ \"acc_norm\": 0.34615384615384615,\n \"acc_norm_stderr\": 0.024121125416941187\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2777777777777778,\n \"acc_stderr\": 0.027309140588230186,\n \ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.027309140588230186\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.31512605042016806,\n \"acc_stderr\": 0.03017680828897434,\n\ \ \"acc_norm\": 0.31512605042016806,\n \"acc_norm_stderr\": 0.03017680828897434\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.2582781456953642,\n \"acc_stderr\": 0.035737053147634576,\n \"\ acc_norm\": 0.2582781456953642,\n \"acc_norm_stderr\": 0.035737053147634576\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.48440366972477067,\n \"acc_stderr\": 0.02142689153920805,\n \"\ acc_norm\": 0.48440366972477067,\n \"acc_norm_stderr\": 0.02142689153920805\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.20833333333333334,\n \"acc_stderr\": 0.027696910713093936,\n \"\ acc_norm\": 0.20833333333333334,\n \"acc_norm_stderr\": 0.027696910713093936\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.4362745098039216,\n \"acc_stderr\": 0.03480693138457039,\n \"\ acc_norm\": 0.4362745098039216,\n \"acc_norm_stderr\": 0.03480693138457039\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.48523206751054854,\n \"acc_stderr\": 0.032533028078777386,\n \ \ \"acc_norm\": 0.48523206751054854,\n \"acc_norm_stderr\": 0.032533028078777386\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4798206278026906,\n\ \ \"acc_stderr\": 0.033530461674123,\n \"acc_norm\": 0.4798206278026906,\n\ \ \"acc_norm_stderr\": 0.033530461674123\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.3969465648854962,\n \"acc_stderr\": 0.04291135671009224,\n\ \ \"acc_norm\": 0.3969465648854962,\n \"acc_norm_stderr\": 0.04291135671009224\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5702479338842975,\n \"acc_stderr\": 0.04519082021319772,\n \"\ acc_norm\": 0.5702479338842975,\n \"acc_norm_stderr\": 0.04519082021319772\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.42592592592592593,\n\ \ \"acc_stderr\": 0.0478034362693679,\n \"acc_norm\": 0.42592592592592593,\n\ \ \"acc_norm_stderr\": 0.0478034362693679\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.39263803680981596,\n \"acc_stderr\": 0.03836740907831029,\n\ \ \"acc_norm\": 0.39263803680981596,\n \"acc_norm_stderr\": 0.03836740907831029\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.32142857142857145,\n\ \ \"acc_stderr\": 0.044328040552915185,\n \"acc_norm\": 0.32142857142857145,\n\ \ \"acc_norm_stderr\": 0.044328040552915185\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.42718446601941745,\n \"acc_stderr\": 0.04897957737781168,\n\ \ \"acc_norm\": 0.42718446601941745,\n \"acc_norm_stderr\": 0.04897957737781168\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.5555555555555556,\n\ \ \"acc_stderr\": 0.03255326307272486,\n \"acc_norm\": 0.5555555555555556,\n\ \ \"acc_norm_stderr\": 0.03255326307272486\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.5197956577266922,\n\ \ \"acc_stderr\": 0.017865944827291626,\n \"acc_norm\": 0.5197956577266922,\n\ \ \"acc_norm_stderr\": 0.017865944827291626\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.41040462427745666,\n \"acc_stderr\": 0.02648339204209818,\n\ \ \"acc_norm\": 0.41040462427745666,\n \"acc_norm_stderr\": 0.02648339204209818\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.38562091503267976,\n \"acc_stderr\": 0.027870745278290313,\n\ \ \"acc_norm\": 0.38562091503267976,\n \"acc_norm_stderr\": 0.027870745278290313\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5080385852090032,\n\ \ \"acc_stderr\": 0.02839442137098453,\n \"acc_norm\": 0.5080385852090032,\n\ \ \"acc_norm_stderr\": 0.02839442137098453\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.44753086419753085,\n \"acc_stderr\": 0.027667138569422704,\n\ \ \"acc_norm\": 0.44753086419753085,\n \"acc_norm_stderr\": 0.027667138569422704\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3723404255319149,\n \"acc_stderr\": 0.028838921471251458,\n \ \ \"acc_norm\": 0.3723404255319149,\n \"acc_norm_stderr\": 0.028838921471251458\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.29465449804432853,\n\ \ \"acc_stderr\": 0.011643576764069548,\n \"acc_norm\": 0.29465449804432853,\n\ \ \"acc_norm_stderr\": 0.011643576764069548\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.4007352941176471,\n \"acc_stderr\": 0.029768263528933112,\n\ \ \"acc_norm\": 0.4007352941176471,\n \"acc_norm_stderr\": 0.029768263528933112\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.3937908496732026,\n \"acc_stderr\": 0.019766211991073056,\n \ \ \"acc_norm\": 0.3937908496732026,\n \"acc_norm_stderr\": 0.019766211991073056\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\": 0.30612244897959184,\n \"acc_stderr\": 0.02950489645459596,\n\ \ \"acc_norm\": 0.30612244897959184,\n \"acc_norm_stderr\": 0.02950489645459596\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.4527363184079602,\n\ \ \"acc_stderr\": 0.03519702717576915,\n \"acc_norm\": 0.4527363184079602,\n\ \ \"acc_norm_stderr\": 0.03519702717576915\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.3313253012048193,\n\ \ \"acc_stderr\": 0.03664314777288085,\n \"acc_norm\": 0.3313253012048193,\n\ \ \"acc_norm_stderr\": 0.03664314777288085\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.5847953216374269,\n \"acc_stderr\": 0.037792759455032014,\n\ \ \"acc_norm\": 0.5847953216374269,\n \"acc_norm_stderr\": 0.037792759455032014\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2350061199510404,\n\ \ \"mc1_stderr\": 0.014843061507731613,\n \"mc2\": 0.3564384771875291,\n\ \ \"mc2_stderr\": 0.013567943486529975\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7237569060773481,\n \"acc_stderr\": 0.012566815015698157\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/haoranxu/ALMA-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|arc:challenge|25_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-09T14-49-25.025957.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|gsm8k|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hellaswag|10_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-09T14-49-25.025957.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-management|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-09T14-49-25.025957.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|truthfulqa:mc|0_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-09T14-49-25.025957.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_09T14_49_25.025957 path: - '**/details_harness|winogrande|5_2023-12-09T14-49-25.025957.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-09T14-49-25.025957.parquet' - config_name: results data_files: - split: 2023_12_09T14_49_25.025957 path: - results_2023-12-09T14-49-25.025957.parquet - split: latest path: - results_2023-12-09T14-49-25.025957.parquet --- # Dataset Card for Evaluation run of haoranxu/ALMA-7B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/haoranxu/ALMA-7B - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [haoranxu/ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_haoranxu__ALMA-7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-09T14:49:25.025957](https://huggingface.co/datasets/open-llm-leaderboard/details_haoranxu__ALMA-7B/blob/main/results_2023-12-09T14-49-25.025957.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": 0.3842750602900277, "acc_stderr": 0.0337414380010653, "acc_norm": 0.388832150301939, "acc_norm_stderr": 0.03466152745310896, "mc1": 0.2350061199510404, "mc1_stderr": 0.014843061507731613, "mc2": 0.3564384771875291, "mc2_stderr": 0.013567943486529975 }, "harness|arc:challenge|25": { "acc": 0.47013651877133106, "acc_stderr": 0.0145853058400071, "acc_norm": 0.5034129692832765, "acc_norm_stderr": 0.014611050403244081 }, "harness|hellaswag|10": { "acc": 0.5642302330213105, "acc_stderr": 0.004948439229523914, "acc_norm": 0.7550288787094205, "acc_norm_stderr": 0.004291911350430712 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "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": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.37358490566037733, "acc_stderr": 0.02977308271331987, "acc_norm": 0.37358490566037733, "acc_norm_stderr": 0.02977308271331987 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3541666666666667, "acc_stderr": 0.039994111357535424, "acc_norm": 0.3541666666666667, "acc_norm_stderr": 0.039994111357535424 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.23, "acc_stderr": 0.04229525846816508, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816508 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3468208092485549, "acc_stderr": 0.036291466701596636, "acc_norm": 0.3468208092485549, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3872340425531915, "acc_stderr": 0.03184389265339525, "acc_norm": 0.3872340425531915, "acc_norm_stderr": 0.03184389265339525 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4, "acc_stderr": 0.04082482904638629, "acc_norm": 0.4, "acc_norm_stderr": 0.04082482904638629 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.26455026455026454, "acc_stderr": 0.022717467897708617, "acc_norm": 0.26455026455026454, "acc_norm_stderr": 0.022717467897708617 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.19047619047619047, "acc_stderr": 0.035122074123020514, "acc_norm": 0.19047619047619047, "acc_norm_stderr": 0.035122074123020514 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.36129032258064514, "acc_stderr": 0.027327548447957543, "acc_norm": 0.36129032258064514, "acc_norm_stderr": 0.027327548447957543 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33497536945812806, "acc_stderr": 0.0332085274234831, "acc_norm": 0.33497536945812806, "acc_norm_stderr": 0.0332085274234831 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.43636363636363634, "acc_stderr": 0.03872592983524753, "acc_norm": 0.43636363636363634, "acc_norm_stderr": 0.03872592983524753 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.398989898989899, "acc_stderr": 0.03488901616852731, "acc_norm": 0.398989898989899, "acc_norm_stderr": 0.03488901616852731 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.48186528497409326, "acc_stderr": 0.036060650018329185, "acc_norm": 0.48186528497409326, "acc_norm_stderr": 0.036060650018329185 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.34615384615384615, "acc_stderr": 0.024121125416941187, "acc_norm": 0.34615384615384615, "acc_norm_stderr": 0.024121125416941187 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2777777777777778, "acc_stderr": 0.027309140588230186, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.027309140588230186 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.31512605042016806, "acc_stderr": 0.03017680828897434, "acc_norm": 0.31512605042016806, "acc_norm_stderr": 0.03017680828897434 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.2582781456953642, "acc_stderr": 0.035737053147634576, "acc_norm": 0.2582781456953642, "acc_norm_stderr": 0.035737053147634576 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.48440366972477067, "acc_stderr": 0.02142689153920805, "acc_norm": 0.48440366972477067, "acc_norm_stderr": 0.02142689153920805 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.20833333333333334, "acc_stderr": 0.027696910713093936, "acc_norm": 0.20833333333333334, "acc_norm_stderr": 0.027696910713093936 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.4362745098039216, "acc_stderr": 0.03480693138457039, "acc_norm": 0.4362745098039216, "acc_norm_stderr": 0.03480693138457039 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.48523206751054854, "acc_stderr": 0.032533028078777386, "acc_norm": 0.48523206751054854, "acc_norm_stderr": 0.032533028078777386 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4798206278026906, "acc_stderr": 0.033530461674123, "acc_norm": 0.4798206278026906, "acc_norm_stderr": 0.033530461674123 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.3969465648854962, "acc_stderr": 0.04291135671009224, "acc_norm": 0.3969465648854962, "acc_norm_stderr": 0.04291135671009224 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5702479338842975, "acc_stderr": 0.04519082021319772, "acc_norm": 0.5702479338842975, "acc_norm_stderr": 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"harness|hendrycksTest-prehistory|5": { "acc": 0.44753086419753085, "acc_stderr": 0.027667138569422704, "acc_norm": 0.44753086419753085, "acc_norm_stderr": 0.027667138569422704 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3723404255319149, "acc_stderr": 0.028838921471251458, "acc_norm": 0.3723404255319149, "acc_norm_stderr": 0.028838921471251458 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.29465449804432853, "acc_stderr": 0.011643576764069548, "acc_norm": 0.29465449804432853, "acc_norm_stderr": 0.011643576764069548 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.4007352941176471, "acc_stderr": 0.029768263528933112, "acc_norm": 0.4007352941176471, "acc_norm_stderr": 0.029768263528933112 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.3937908496732026, "acc_stderr": 0.019766211991073056, "acc_norm": 0.3937908496732026, "acc_norm_stderr": 0.019766211991073056 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.44545454545454544, "acc_stderr": 0.047605488214603246, "acc_norm": 0.44545454545454544, "acc_norm_stderr": 0.047605488214603246 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.30612244897959184, "acc_stderr": 0.02950489645459596, "acc_norm": 0.30612244897959184, "acc_norm_stderr": 0.02950489645459596 }, "harness|hendrycksTest-sociology|5": { "acc": 0.4527363184079602, "acc_stderr": 0.03519702717576915, "acc_norm": 0.4527363184079602, "acc_norm_stderr": 0.03519702717576915 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-virology|5": { "acc": 0.3313253012048193, "acc_stderr": 0.03664314777288085, "acc_norm": 0.3313253012048193, "acc_norm_stderr": 0.03664314777288085 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.5847953216374269, "acc_stderr": 0.037792759455032014, "acc_norm": 0.5847953216374269, "acc_norm_stderr": 0.037792759455032014 }, "harness|truthfulqa:mc|0": { "mc1": 0.2350061199510404, "mc1_stderr": 0.014843061507731613, "mc2": 0.3564384771875291, "mc2_stderr": 0.013567943486529975 }, "harness|winogrande|5": { "acc": 0.7237569060773481, "acc_stderr": 0.012566815015698157 }, "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]

AdapterOcean/python-code-instructions-18k-alpaca-standardized_unified

--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 splits: - name: train num_bytes: 11288801 num_examples: 18611 download_size: 5543097 dataset_size: 11288801 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "python-code-instructions-18k-alpaca-standardized_unified" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ppdev/medtext-llama2

--- license: cc-by-4.0 --- Original data from: https://huggingface.co/datasets/BI55/MedText I just reformat it for fine tunning in lamma2 based on this article https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html Another important point related to the data quality is the prompt template. Prompts are comprised of similar elements: system prompt (optional) to guide the model, user prompt (required) to give the instruction, additional inputs (optional) to take into consideration, and the model’s answer (required). In the case of Llama 2, the authors used the following template for the chat models: [INST] User prompt [/INST] Model answer

nsanghi/axterix-obelix

--- license: apache-2.0 task_categories: - image-to-image language: - en tags: - asterix - diffusion - dreambooth size_categories: - n<1K --- This dataset contains 10 images of asterix and Obelix cartoon characters taken from internet

cartesinus/leyzer-fedcsis-translated

--- license: cc-by-4.0 task_categories: - text-classification language: - pl tags: - natural-language-understanding size_categories: - 10K<n<100K --- # Leyzer: A Dataset for Multilingual Virtual Assistants Leyzer is a multilingual text corpus designed to study multilingual and cross-lingual natural language understanding (NLU) models and the strategies of localization of virtual assistants. It consists of 20 domains across three languages: English, Spanish and Polish, with 186 intents and a wide range of samples, ranging from 1 to 672 sentences per intent. For more stats please refer to wiki.

mstz/arhythmia

--- language: - en tags: - arrhythmia - tabular_classification - multiclass_classification - binary_classification - UCI pretty_name: Arhythmia size_categories: - n<1K task_categories: - tabular-classification configs: - arhytmia - has_arhytmia license: cc --- # Arhythmia The [Arrhythmia dataset](https://archive.ics.uci.edu/ml/datasets/Arrhythmia) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets). Does the patient have arhythmia? If so, what type? # Configurations and tasks | **Configuration** | **Task** | Description | |-------------------|---------------------------|---------------------------------------------------------------| | arhytmia | Multiclass classification | What type of arhythmia does the patient have? | | has_arhytmia | Binary classification | Does the patient have arhythmia? | # Usage ```python from datasets import load_dataset dataset = load_dataset("mstz/arhythmia", "arhythmia")["train"] ``` # Features Target feature changes according to the selected configuration and is always in last position in the dataset.

tyzhu/find_sent_before_sent_train_400_eval_40_baseline

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 3760579 num_examples: 1994 - name: validation num_bytes: 386422 num_examples: 200 download_size: 791972 dataset_size: 4147001 --- # Dataset Card for "find_sent_before_sent_train_400_eval_40_baseline" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

andstor/output

--- license: mit task_categories: - text-generation language: - en dataset_info: - config_name: gpt2-xl features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 60221138 num_examples: 22169 download_size: 66419674 dataset_size: 60221138 - config_name: EleutherAI.gpt-j-6B features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 67625587 num_examples: 20665 download_size: 73049509 dataset_size: 67625587 - config_name: NinedayWang.PolyCoder-2.7B features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: andstor.the_pile_github.greedy num_bytes: 58822858 num_examples: 20342 download_size: 63717236 dataset_size: 58822858 - config_name: Salesforce.codegen-16B-multi features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 2509745 num_examples: 820 download_size: 2694784 dataset_size: 2509745 - config_name: openai.gpt-3.5-turbo-0613 features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 958178 num_examples: 820 download_size: 1067958 dataset_size: 958178 - config_name: openai.gpt-4-0613 features: - name: id dtype: string - name: part sequence: int32 - name: prompt dtype: string - name: reference dtype: string - name: prediction dtype: string - name: ended dtype: bool - name: meta struct: - name: subset dtype: string splits: - name: THUDM.humaneval_x.greedy num_bytes: 875401 num_examples: 820 - name: THUDM.humaneval_x.random num_bytes: 906274 num_examples: 820 download_size: 1995455 dataset_size: 1781675 --- # Dataset Card for Output ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://github.com/andstor/lm-output-dataset - **Repository:** https://github.com/andstor/lm-output-dataset - **Paper:** - **Leaderboard:** - **Point of Contact:** [André Storhaug](mailto:andr3.storhaug@gmail.com) ### Dataset Summary This is a dataset of various language model outputs from different datasets. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@andstor](https://github.com/andstor) for adding this dataset.

liangyupu/DoTA_dataset

--- license: mit language: - zh - en - fr - de size_categories: - 100K<n<1M --- # Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling This is the official repository for **DoTA** dataset (**Do**cument image machine **T**ranslation dataset of **A**rXiv articles in markdown format) introduced by the following paper: [***Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling (NAACL 2024 Main)***](https://openreview.net/forum?id=XH2TgKlXWv) In addition to the 126K samples mentioned in the paper, we provide all 139K samples that have not been filtered. Each sample contains original English image, transcripted English mmd file and translated Chinese/French/German mmd file. Samples used in the paper are listed in a json file. Text files can be decompressed as follows: ```bash tar -xzvf zh_mmd.tar.gz -C ./ ``` Image files can be decompressed as follows: ```bash cat imgs.tar.gz.* | tar -xzvf - -C ./ ``` If you want to use our dataset, please cite as follows: ```BibTex @inproceedings{ liang2024document, title={Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling}, author={Yupu Liang and Yaping Zhang and Cong MA and Zhiyang Zhang and Yang Zhao and Lu Xiang and Chengqing Zong and Yu Zhou}, booktitle={2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics}, year={2024}, url={https://openreview.net/forum?id=XH2TgKlXWv} } ```

kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-markdown-88000

--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 1113664 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---

claudios/cubert_ETHPy150Open

--- license: apache-2.0 task_categories: - text-classification pretty_name: CuBERT ETH Py150 Benchmarks arxiv: 2001.00059 dataset_info: - config_name: exception_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 25423003 num_examples: 18480 - name: dev num_bytes: 2845822 num_examples: 2088 - name: test num_bytes: 14064500 num_examples: 10348 download_size: 16935273 dataset_size: 42333325 - config_name: function_docstring_datasets features: - name: function dtype: string - name: docstring dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 261700491 num_examples: 340846 - name: dev num_bytes: 28498757 num_examples: 37592 - name: test num_bytes: 141660242 num_examples: 186698 download_size: 121724722 dataset_size: 431859490 - config_name: swapped_operands_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 271097336 num_examples: 236246 - name: dev num_bytes: 29986397 num_examples: 26118 - name: test num_bytes: 148544957 num_examples: 130972 download_size: 105243573 dataset_size: 449628690 - config_name: variable_misuse_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 474283355 num_examples: 700708 - name: dev num_bytes: 50447683 num_examples: 75478 - name: test num_bytes: 251591448 num_examples: 378440 download_size: 231302039 dataset_size: 776322486 - config_name: variable_misuse_repair_datasets features: - name: function sequence: string - name: target_mask sequence: int64 - name: error_location_mask sequence: int64 - name: candidate_mask sequence: int64 - name: provenance dtype: string splits: - name: train num_bytes: 4417505142 num_examples: 700708 - name: dev num_bytes: 469436314 num_examples: 75478 - name: test num_bytes: 2331355329 num_examples: 378440 download_size: 498300512 dataset_size: 7218296785 - config_name: wrong_binary_operator_datasets features: - name: function dtype: string - name: label dtype: string - name: info dtype: string splits: - name: train num_bytes: 439948844 num_examples: 459400 - name: dev num_bytes: 47620848 num_examples: 49804 - name: test num_bytes: 239409450 num_examples: 251804 download_size: 163088211 dataset_size: 726979142 configs: - config_name: exception_datasets data_files: - split: train path: exception_datasets/train-* - split: dev path: exception_datasets/dev-* - split: test path: exception_datasets/test-* - config_name: function_docstring_datasets data_files: - split: train path: function_docstring_datasets/train-* - split: dev path: function_docstring_datasets/dev-* - split: test path: function_docstring_datasets/test-* - config_name: swapped_operands_datasets data_files: - split: train path: swapped_operands_datasets/train-* - split: dev path: swapped_operands_datasets/dev-* - split: test path: swapped_operands_datasets/test-* - config_name: variable_misuse_datasets data_files: - split: train path: variable_misuse_datasets/train-* - split: dev path: variable_misuse_datasets/dev-* - split: test path: variable_misuse_datasets/test-* - config_name: variable_misuse_repair_datasets data_files: - split: train path: variable_misuse_repair_datasets/train-* - split: dev path: variable_misuse_repair_datasets/dev-* - split: test path: variable_misuse_repair_datasets/test-* - config_name: wrong_binary_operator_datasets data_files: - split: train path: wrong_binary_operator_datasets/train-* - split: dev path: wrong_binary_operator_datasets/dev-* - split: test path: wrong_binary_operator_datasets/test-* tags: - code --- # CuBERT ETH150 Open Benchmarks This is an unofficial HuggingFace upload of the [CuBERT ETH150 Open Benchmarks](https://github.com/google-research/google-research/tree/master/cubert). This dataset was released along with [Learning and Evaluating Contextual Embedding of Source Code](https://arxiv.org/abs/2001.00059). --- ## Benchmarks and Fine-Tuned Models Here we describe the 6 Python benchmarks we created. All 6 benchmarks were derived from [ETH Py150 Open](https://github.com/google-research-datasets/eth_py150_open). All examples are stored as sharded text files. Each text line corresponds to a separate example encoded as a JSON object. For each dataset, we release separate training/validation/testing splits along the same boundaries that ETH Py150 Open splits its files to the corresponding splits. The fine-tuned models are the checkpoints of each model with the highest validation accuracy. 1. **Function-docstring classification**. Combinations of functions with their correct or incorrect documentation string, used to train a classifier that can tell which pairs go together. The JSON fields are: * `function`: string, the source code of a function as text * `docstring`: string, the documentation string for that function. Note that the string is unquoted. To be able to properly tokenize it with the CuBERT tokenizers, you have to wrap it in quotes first. For example, in Python, use `string_to_tokenize = f'"""{docstring}"""'`. * `label`: string, one of (“Incorrect”, “Correct”), the label of the example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function name and, for “Incorrect” examples, the function whose docstring was substituted. 1. **Exception classification**. Combinations of functions where one exception type has been masked, along with a label indicating the masked exception type. The JSON fields are: * `function`: string, the source code of a function as text, in which one exception type has been replaced with the special token “__HOLE__” * `label`: string, one of (`ValueError`, `KeyError`, `AttributeError`, `TypeError`, `OSError`, `IOError`, `ImportError`, `IndexError`, `DoesNotExist`, `KeyboardInterrupt`, `StopIteration`, `AssertionError`, `SystemExit`, `RuntimeError`, `HTTPError`, `UnicodeDecodeError`, `NotImplementedError`, `ValidationError`, `ObjectDoesNotExist`, `NameError`, `None`), the masked exception type. Note that `None` never occurs in the data and will be removed in a future release. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, and the fully-qualified function name. 1. **Variable-misuse classification**. Combinations of functions where one use of a variable may have been replaced with another variable defined in the same context, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Variable misuse”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the variable substitution that has occurred (e.g., “correct_variable” → “incorrect_variable”). 1. **Swapped-operand classification**. Combinations of functions where one use binary operator’s arguments have been swapped, to create a buggy example, or left undisturbed, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Swapped operands”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the operand swap has occurred (e.g., “swapped operands of `not in`”). 1. **Wrong-binary-operator classification**. Combinations of functions where one binary operator has been swapped with another, to create a buggy example, or left undisturbed, along with a label indicating if this bug-injection has occurred. The JSON fields are: * `function`: string, the source code of a function as text. * `label`: string, one of (“Correct”, “Wrong binary operator”) indicating if this is a buggy or bug-free example. * `info`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the operator replacement has occurred (e.g., “`==`-> `!=`”). 1. **Variable-misuse localization and repair**. Combinations of functions where one use of a variable may have been replaced with another variable defined in the same context, along with information that can be used to localize and repair the bug, as well as the location of the bug if such a bug exists. The JSON fields are: * `function`: a list of strings, the source code of a function, tokenized with the vocabulary from item b. Note that, unlike other task datasets, this dataset gives a tokenized function, rather than the code as a single string. * `target_mask`: a list of integers (0 or 1). If the integer at some position is 1, then the token at the corresponding position of the function token list is a correct repair for the introduced bug. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask. If the example is bug-free, all integers are 0. * `error_location_mask`: a list of integers (0 or 1). If the integer at some position is 1, then there is a variable-misuse bug at the corresponding location of the tokenized function. In a bug-free example, the first integer is 1. There is exactly one integer set to 1 for all examples. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask. * `candidate_mask`: a list of integers (0 or 1). If the integer at some position is 1, then the variable starting at that position in the tokenized function is a candidate to consider when repairing a bug. Candidates are all variables defined in the function parameters or via variable declarations in the function. If a variable has been split into multiple tokens, only the first subtoken is marked in this mask, for each candidate. * `provenance`: string, an unformatted description of how the example was constructed, including the source dataset (always “ETHPy150Open”), the repository and filepath, the function, and whether the example is bugfree (marked “original”) or the buggy/repair token positions and variables (e.g., “16/18 `kwargs` → `self`”). 16 is the position of the introduced error, 18 is the location of the repair. ## Citation ```bibtex @inproceedings{cubert, author = {Aditya Kanade and Petros Maniatis and Gogul Balakrishnan and Kensen Shi}, title = {Learning and evaluating contextual embedding of source code}, booktitle = {Proceedings of the 37th International Conference on Machine Learning, {ICML} 2020, 12-18 July 2020}, series = {Proceedings of Machine Learning Research}, publisher = {{PMLR}}, year = {2020}, } ```

thbndi/Mimic4Dataset

--- tags: - medical --- # Dataset Usage ## Description The Mimic-IV dataset generate data by executing the Pipeline available on https://github.com/healthylaife/MIMIC-IV-Data-Pipeline. ## Function Signature ```python load_dataset('thbndi/Mimic4Dataset', task, mimic_path=mimic_data, config_path=config_file, encoding=encod, generate_cohort=gen_cohort, val_size=size, cache_dir=cache) ``` ## Arguments 1. `task` (string) : - Description: Specifies the task you want to perform with the dataset. - Default: "Mortality" - Note: Possible Values : 'Phenotype', 'Length of Stay', 'Readmission', 'Mortality' 2. `mimic_path` (string) : - Description: Complete path to the Mimic-IV raw data on user's machine. - Note: You need to provide the appropriate path where the Mimic-IV data is stored. The path should end with the version of mimic (eg : mimiciv/2.2). Supported version : 2.2 and 1.0 as provided by the authors of the pipeline. 3. `config_path` (string) optionnal : - Description: Path to the configuration file for the cohort generation choices (more infos in '/config/readme.md'). - Default: Configuration file provided in the 'config' folder. 4. `encoding` (string) optionnal : - Description: Data encoding option for the features. - Options: "concat", "aggreg", "tensor", "raw", "text" - Default: "concat" - Note: Choose one of the following options for data encoding: - "concat": Concatenates the one-hot encoded diagnoses, demographic data vector, and dynamic features at each measured time instant, resulting in a high-dimensional feature vector. - "aggreg": Concatenates the one-hot encoded diagnoses, demographic data vector, and dynamic features, where each item_id is replaced by the average of the measured time instants, resulting in a reduced-dimensional feature vector. - "tensor": Represents each feature as an 2D array. There are separate arrays for labels, demographic data ('DEMO'), diagnosis ('COND'), medications ('MEDS'), procedures ('PROC'), chart/lab events ('CHART/LAB'), and output events data ('OUT'). Dynamic features are represented as 2D arrays where each row contains values at a specific time instant. - "raw": Provide cohort from the pipeline without any encoding for custom data processing. - "text": Represents diagnoses as text suitable for BERT or other similar text-based models. - For 'concat' and 'aggreg' the composition of the vector is given in './data/dict/"task"/features_aggreg.csv' or './data/dict/"task"/features_concat.csv' file and in 'features_names' column of the dataset. 5. `generate_cohort` (bool) optionnal : - Description: Determines whether to generate a new cohort from Mimic-IV data. - Default: True - Note: Set it to True to generate a cohort, or False to skip cohort generation. 6. `val_size`, 'test_size' (float) optionnal : - Description: Proportion of the dataset used for validation during training. - Default: 0.1 for validation size and 0.2 for testing size. - Note: Can be set to 0. 7. `cache_dir` (string) optionnal : - Description: Directory where the processed dataset will be cached. - Note: Providing a cache directory for each encoding type can avoid errors when changing the encoding type. ## Example Usage ```python import datasets from datasets import load_dataset # Example 1: Load dataset with default settings dataset = load_dataset('thbndi/Mimic4Dataset', task="Mortality", mimic_path="/path/to/mimic_data") # Example 2: Load dataset with custom settings dataset = load_dataset('thbndi/Mimic4Dataset', task="Phenotype", mimic_path="/path/to/mimic_data", config_path="/path/to/config_file", encoding="aggreg", generate_cohort=False, val_size=0.2, cache_dir="/path/to/cache_dir") ``` Please note that the provided examples are for illustrative purposes only, and you should adjust the paths and settings based on your actual dataset and specific use case.

yuan-sf63/chenyu_mask_32

--- dataset_info: features: - name: feature dtype: string - name: target dtype: string splits: - name: train num_bytes: 4349637.991911224 num_examples: 53852 - name: validation num_bytes: 483329.00808877597 num_examples: 5984 download_size: 0 dataset_size: 4832967.0 --- # Dataset Card for "chenyu_mask_32" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

allegro/klej-nkjp-ner-en

--- license: apache-2.0 task_categories: - text-classification language: - en - pl pretty_name: NKPJ-NER translated to English size_categories: - n<1K --- All instances from the `allegro/klej-nkjp-ner` (train, val, test) translated to English with Google Translate API. Columns: - `source` - text instance in Polish. - `target` - text instance in English.

UnbiasedMoldInspectionsIN/glmra1m4-9

--- license: apache-2.0 ---

communityai/OdiaGenAI___gpt-teacher-roleplay-odia-3k

--- dataset_info: features: - name: source dtype: string - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 6893531.0 num_examples: 3146 download_size: 2480702 dataset_size: 6893531.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

ovior/twitter_dataset_1713094312

--- dataset_info: features: - name: id dtype: string - name: tweet_content dtype: string - name: user_name dtype: string - name: user_id dtype: string - name: created_at dtype: string - name: url dtype: string - name: favourite_count dtype: int64 - name: scraped_at dtype: string - name: image_urls dtype: string splits: - name: train num_bytes: 2391221 num_examples: 7063 download_size: 1380144 dataset_size: 2391221 configs: - config_name: default data_files: - split: train path: data/train-* ---

Maximax67/Words-CEFR-Dataset

--- license: mit task_categories: - token-classification language: - en pretty_name: Words CEFR Dataset size_categories: - 100K<n<1M tags: - CEFR - POS - NLP - SQLite configs: - config_name: sqlite_db data_files: word_cefr_minified.db --- # Words CEFR Dataset This project focuses on analyzing and categorizing English words based on their CEFR levels (from A1 to C2). I computed CEFR levels for every valid English word and its corresponding part of speech by by considering various factors including the average levels of other parts of speech for the same word, lemma levels, stem levels, as well as lemma, stem, and word frequencies. This dataset on GitHub: https://github.com/Maximax67/Words-CEFR-Dataset ## Example of usage To perform a basic word CEFR analysis, execute the **Text-Analizer.ipynb** file. This notebook provides a practical demonstration of how to analyze words and determine their corresponding CEFR levels. ### Demo text (generated by ChatGPT 3.5): ``` In the heart of every forest, a hidden world thrives among the towering trees. Trees, those silent giants, are more than just passive observers of nature's drama; they are active participants in an intricate dance of life. Did you know that trees communicate with each other? It's not through words or gestures like ours, but rather through a complex network of fungi that connect their roots underground. This network, often called the "wood wide web," allows trees to share nutrients, water, and even warnings about potential threats. But trees are not just generous benefactors; they are also masters of adaptation. Take the mighty sequoias, for example, towering giants that have stood the test of time for thousands of years. These giants have evolved thick, fire-resistant bark to withstand the frequent wildfires of their native California. And speaking of longevity, did you know that some trees have been around for centuries, witnessing history unfold? The ancient bristlecone pines of the American West, for instance, can live for over 5,000 years, making them some of the oldest living organisms on Earth. So the next time you find yourself wandering through a forest, take a moment to appreciate the remarkable world of trees. They may seem like silent spectators, but their lives are full of fascinating stories waiting to be discovered. ``` ### Results: ``` NLP: 318 ms CEFR levels: 3 ms ------------------------------ Text length: 1370 Total tokens: 275 ``` ``` CEFR statistic (total words): A1: 136 A2: 37 B1: 27 B2: 11 C1: 2 C2: 7 CEFR statistic (unique words): A1: 69 A2: 34 B1: 23 B2: 11 C1: 2 C2: 7 ``` ``` Not found words: 0 ``` ``` Words with level B2 and higher: 17 mighty JJ 4.00 B2 potential JJ 4.00 B2 bristlecone NN 6.00 C2 living NN 4.00 B2 longevity NN 5.97 C2 california NNP 6.00 C2 benefactors NNS 6.00 C2 fungi NNS 5.19 C1 masters NNS 4.00 B2 observers NNS 4.00 B2 pines NNS 4.00 B2 sequoias NNS 6.00 C2 wildfires NNS 6.00 C2 underground RB 4.00 B2 withstand VB 5.12 C1 evolved VBN 4.00 B2 thrives VBZ 5.86 C2 ``` ## Data Collection Process ### Making English valid words list For this project I created a [valid English words list](https://github.com/Maximax67/English-Valid-Words). It includes word, frequency count and word stems along with their associated probabilities of being valid words. For this project I used [valid_words_sorted_by_frequency.csv](https://github.com/Maximax67/English-Valid-Words/blob/main/valid_words_sorted_by_frequency.csv) file, so all words in words table in SQLite database are sorted by frequency. ### Data Processing Steps The data processing pipeline, implemented in the **Word-CEFR.ipynb** notebook, involves the following steps: 1. **Parsing Google 1-grams Dataset**: Extracting frequency data for valid words part of speech with frequency counts more than 10,000. I used [spaCy](https://spacy.io/) for more accurate part-of-speech (POS) tagging based on the [Penn Treebank Project's list of POS tags](https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html). Additionally, I used [LemmInflect](https://github.com/bjascob/LemmInflect) for obtaining word lemmas. 2. **Parsing CEFR-J Dataset**: I parsed it to get CEFR level for some words based on its POS. In this step I also parsed core usage categories. 3. **Calculation of Average Frequencies for each CEFR level and Interpolation**. 4. **Assigning CEFR Levels**: Determining the CEFR level for each word's POS based on average levels of other POS for the same word, lemma levels, stem levels, as well as lemma, stem and word frequencies. 5. **Database Optimization**: Minimizing database size by consolidating word frequency data from 1900 to 2019 into a single total value. Additionally, calculating the average POS level from all available sources. SQLite database is now optimized and has a reduced size of 20MB. Refer to the **Minify_db.ipynb** file for more details. ## Possible Improvements 1. **Incorporating Additional Datasets**: To obtain more precise data, consider parsing the [Octanove Vocabulary profile](https://github.com/openlanguageprofiles/olp-en-cefrj/blob/master/octanove-vocabulary-profile-c1c2-1.0.csv) dataset, which provides C1 and C2 level vocabulary data. However, please note that this dataset is licensed under the [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/). Also you can parse [World level survey by Zenodo](https://zenodo.org/records/12501) dataset to further enrich the dataset. This dataset, licensed under the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/legalcode). 2. **Filtering Personal Names and Geographical Entities**: you can improve result accuracy by implementing mechanisms to identify and exclude personal names, countries, cities, and other such entities from displaying CEFR levels. This refinement can help ensure that the analysis focuses solely on linguistic content. ## Dataset files included 1. **word_cefr_minified.db**: SQLite3 database. ![Database Model](database_model.png) 2. **csv/words.csv**: * word_id * word * stem_word_id 3. **csv/word_pos.csv**: * word_pos_id * word_id * pos_tag_id * lemma_word_id * frequency_count * level 4. **csv/word_categories**: * word_pos_id * category_id 5. **csv/pos_tags.csv**: * tag_id * tag * description 6. **csv/categories.csv**: * category_id * category_title ## License This project is licensed under the MIT License - see the LICENSE file for details. ## Acknowledgments I would like to acknowledge the contributions of the following resources: - [Spacy](https://spacy.io/) - [CEFR-J](https://cefr-j.org/) - [LemmInflect](https://github.com/bjascob/LemmInflect) - [The Google Books Ngram Viewer (used 1-grams dataset, version 20200217)](https://books.google.com/ngrams/) - [List of pos tags form Penn Treebank Project](https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html) Also I used these resources to create my [valid English words list](https://github.com/Maximax67/English-Valid-Words): - [Word list by infochimps (archived)](https://web.archive.org/web/20131118073324/https://www.infochimps.com/datasets/word-list-350000-simple-english-words-excel-readable) - [English words github repo by dwyl](https://github.com/dwyl/english-words) - [NLTK (Natural Language Toolkit)](https://www.nltk.org/) - [WordNet](https://wordnet.princeton.edu/)

ibranze/araproje_hellaswag_en_f1

--- dataset_info: features: - name: ind dtype: int32 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string splits: - name: validation num_bytes: 149738.0 num_examples: 250 download_size: 0 dataset_size: 149738.0 configs: - config_name: default data_files: - split: validation path: data/validation-* --- # Dataset Card for "araproje_hellaswag_en_f1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

darrel999/java-file-1107

--- dataset_info: features: - name: instruction dtype: string splits: - name: train num_bytes: 5108304 num_examples: 1107 download_size: 1329459 dataset_size: 5108304 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare

--- pretty_name: Evaluation run of louisbrulenaudet/Pearl-7B-0210-dare dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [louisbrulenaudet/Pearl-7B-0210-dare](https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 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_louisbrulenaudet__Pearl-7B-0210-dare\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-11T16:34:01.841503](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare/blob/main/results_2024-02-11T16-34-01.841503.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\": 0.6238865006281977,\n\ \ \"acc_stderr\": 0.03273771754882751,\n \"acc_norm\": 0.6230212223075242,\n\ \ \"acc_norm_stderr\": 0.03342419316334821,\n \"mc1\": 0.5752753977968176,\n\ \ \"mc1_stderr\": 0.017304000957167477,\n \"mc2\": 0.7146460351141442,\n\ \ \"mc2_stderr\": 0.015047159780719415\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6902730375426621,\n \"acc_stderr\": 0.013512058415238361,\n\ \ \"acc_norm\": 0.7090443686006825,\n \"acc_norm_stderr\": 0.013273077865907597\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7264489145588529,\n\ \ \"acc_stderr\": 0.004448701611795089,\n \"acc_norm\": 0.8879705238000398,\n\ \ \"acc_norm_stderr\": 0.003147581209374547\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.046482319871173156\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5851851851851851,\n\ \ \"acc_stderr\": 0.04256193767901408,\n \"acc_norm\": 0.5851851851851851,\n\ \ \"acc_norm_stderr\": 0.04256193767901408\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.037385206761196686,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.037385206761196686\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.56,\n\ \ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n \ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6754716981132075,\n \"acc_stderr\": 0.028815615713432115,\n\ \ \"acc_norm\": 0.6754716981132075,\n \"acc_norm_stderr\": 0.028815615713432115\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness|hendrycksTest-college_chemistry|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-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\": 0.33,\n\ \ \"acc_stderr\": 0.047258156262526045,\n \"acc_norm\": 0.33,\n \ \ \"acc_norm_stderr\": 0.047258156262526045\n },\n \"harness|hendrycksTest-college_medicine|5\"\ : {\n \"acc\": 0.5953757225433526,\n \"acc_stderr\": 0.03742461193887248,\n\ \ \"acc_norm\": 0.5953757225433526,\n \"acc_norm_stderr\": 0.03742461193887248\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\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\":\ \ 0.5531914893617021,\n \"acc_stderr\": 0.032500536843658404,\n \"\ acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.032500536843658404\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3941798941798942,\n \"acc_stderr\": 0.025167982333894143,\n \"\ acc_norm\": 0.3941798941798942,\n \"acc_norm_stderr\": 0.025167982333894143\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4126984126984127,\n\ \ \"acc_stderr\": 0.04403438954768177,\n \"acc_norm\": 0.4126984126984127,\n\ \ \"acc_norm_stderr\": 0.04403438954768177\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7161290322580646,\n\ \ \"acc_stderr\": 0.02564938106302926,\n \"acc_norm\": 0.7161290322580646,\n\ \ \"acc_norm_stderr\": 0.02564938106302926\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4729064039408867,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.4729064039408867,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252607,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479048,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479048\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.023814477086593566,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.023814477086593566\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6461538461538462,\n \"acc_stderr\": 0.024243783994062157,\n\ \ \"acc_norm\": 0.6461538461538462,\n \"acc_norm_stderr\": 0.024243783994062157\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.02840653309060846,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.02840653309060846\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6176470588235294,\n \"acc_stderr\": 0.031566630992154156,\n\ \ \"acc_norm\": 0.6176470588235294,\n \"acc_norm_stderr\": 0.031566630992154156\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8128440366972477,\n \"acc_stderr\": 0.016722684526200154,\n \"\ acc_norm\": 0.8128440366972477,\n \"acc_norm_stderr\": 0.016722684526200154\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4444444444444444,\n \"acc_stderr\": 0.03388857118502326,\n \"\ acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.03388857118502326\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.02862654791243741,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.02862654791243741\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \ \ \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.03149384670994131,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.03149384670994131\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7251908396946565,\n \"acc_stderr\": 0.039153454088478354,\n\ \ \"acc_norm\": 0.7251908396946565,\n \"acc_norm_stderr\": 0.039153454088478354\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.03941897526516301,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.03941897526516301\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.03512385283705048,\n\ \ \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.03512385283705048\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.047268355537191,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.047268355537191\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8504273504273504,\n\ \ \"acc_stderr\": 0.023365051491753715,\n \"acc_norm\": 0.8504273504273504,\n\ \ \"acc_norm_stderr\": 0.023365051491753715\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7969348659003831,\n\ \ \"acc_stderr\": 0.014385525076611578,\n \"acc_norm\": 0.7969348659003831,\n\ \ \"acc_norm_stderr\": 0.014385525076611578\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7109826589595376,\n \"acc_stderr\": 0.02440517393578323,\n\ \ \"acc_norm\": 0.7109826589595376,\n \"acc_norm_stderr\": 0.02440517393578323\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3564245810055866,\n\ \ \"acc_stderr\": 0.016018239710513398,\n \"acc_norm\": 0.3564245810055866,\n\ \ \"acc_norm_stderr\": 0.016018239710513398\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.026992544339297243,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.026992544339297243\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.707395498392283,\n\ \ \"acc_stderr\": 0.02583989833487798,\n \"acc_norm\": 0.707395498392283,\n\ \ \"acc_norm_stderr\": 0.02583989833487798\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6851851851851852,\n \"acc_stderr\": 0.025842248700902164,\n\ \ \"acc_norm\": 0.6851851851851852,\n \"acc_norm_stderr\": 0.025842248700902164\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.42907801418439717,\n \"acc_stderr\": 0.02952591430255856,\n \ \ \"acc_norm\": 0.42907801418439717,\n \"acc_norm_stderr\": 0.02952591430255856\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.44328552803129073,\n\ \ \"acc_stderr\": 0.012687818419599923,\n \"acc_norm\": 0.44328552803129073,\n\ \ \"acc_norm_stderr\": 0.012687818419599923\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6323529411764706,\n \"acc_stderr\": 0.02928941340940319,\n\ \ \"acc_norm\": 0.6323529411764706,\n \"acc_norm_stderr\": 0.02928941340940319\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6241830065359477,\n \"acc_stderr\": 0.01959402113657744,\n \ \ \"acc_norm\": 0.6241830065359477,\n \"acc_norm_stderr\": 0.01959402113657744\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\": 0.6938775510204082,\n \"acc_stderr\": 0.02950489645459596,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.02950489645459596\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8009950248756219,\n\ \ \"acc_stderr\": 0.028231365092758406,\n \"acc_norm\": 0.8009950248756219,\n\ \ \"acc_norm_stderr\": 0.028231365092758406\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.02878210810540171,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.02878210810540171\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5752753977968176,\n\ \ \"mc1_stderr\": 0.017304000957167477,\n \"mc2\": 0.7146460351141442,\n\ \ \"mc2_stderr\": 0.015047159780719415\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8453038674033149,\n \"acc_stderr\": 0.010163172650433542\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6338134950720242,\n \ \ \"acc_stderr\": 0.013270100238748831\n }\n}\n```" repo_url: https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|arc:challenge|25_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-11T16-34-01.841503.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|gsm8k|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hellaswag|10_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-11T16-34-01.841503.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-management|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T16-34-01.841503.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|truthfulqa:mc|0_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-11T16-34-01.841503.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_11T16_34_01.841503 path: - '**/details_harness|winogrande|5_2024-02-11T16-34-01.841503.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-11T16-34-01.841503.parquet' - config_name: results data_files: - split: 2024_02_11T16_34_01.841503 path: - results_2024-02-11T16-34-01.841503.parquet - split: latest path: - results_2024-02-11T16-34-01.841503.parquet --- # Dataset Card for Evaluation run of louisbrulenaudet/Pearl-7B-0210-dare  Dataset automatically created during the evaluation run of model [louisbrulenaudet/Pearl-7B-0210-dare](https://huggingface.co/louisbrulenaudet/Pearl-7B-0210-dare) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 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_louisbrulenaudet__Pearl-7B-0210-dare", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-11T16:34:01.841503](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0210-dare/blob/main/results_2024-02-11T16-34-01.841503.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": 0.6238865006281977, "acc_stderr": 0.03273771754882751, "acc_norm": 0.6230212223075242, "acc_norm_stderr": 0.03342419316334821, "mc1": 0.5752753977968176, "mc1_stderr": 0.017304000957167477, "mc2": 0.7146460351141442, "mc2_stderr": 0.015047159780719415 }, "harness|arc:challenge|25": { "acc": 0.6902730375426621, "acc_stderr": 0.013512058415238361, "acc_norm": 0.7090443686006825, "acc_norm_stderr": 0.013273077865907597 }, "harness|hellaswag|10": { "acc": 0.7264489145588529, "acc_stderr": 0.004448701611795089, "acc_norm": 0.8879705238000398, "acc_norm_stderr": 0.003147581209374547 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901408, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901408 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.037385206761196686, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.037385206761196686 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.028815615713432115, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.028815615713432115 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.037455547914624555, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.037455547914624555 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5531914893617021, "acc_stderr": 0.032500536843658404, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.032500536843658404 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3941798941798942, "acc_stderr": 0.025167982333894143, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.025167982333894143 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4126984126984127, "acc_stderr": 0.04403438954768177, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.04403438954768177 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7161290322580646, "acc_stderr": 0.02564938106302926, "acc_norm": 0.7161290322580646, "acc_norm_stderr": 0.02564938106302926 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4729064039408867, "acc_stderr": 0.03512819077876106, "acc_norm": 0.4729064039408867, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.02962022787479048, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.02962022787479048 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.023814477086593566, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.023814477086593566 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6461538461538462, "acc_stderr": 0.024243783994062157, "acc_norm": 0.6461538461538462, "acc_norm_stderr": 0.024243783994062157 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.02840653309060846, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.02840653309060846 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6176470588235294, "acc_stderr": 0.031566630992154156, "acc_norm": 0.6176470588235294, "acc_norm_stderr": 0.031566630992154156 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8128440366972477, "acc_stderr": 0.016722684526200154, "acc_norm": 0.8128440366972477, "acc_norm_stderr": 0.016722684526200154 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4444444444444444, "acc_stderr": 0.03388857118502326, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.03388857118502326 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7892156862745098, "acc_stderr": 0.02862654791243741, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.02862654791243741 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7805907172995781, "acc_stderr": 0.026939106581553945, "acc_norm": 0.7805907172995781, "acc_norm_stderr": 0.026939106581553945 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.672645739910314, "acc_stderr": 0.03149384670994131, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.03149384670994131 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7251908396946565, "acc_stderr": 0.039153454088478354, "acc_norm": 0.7251908396946565, "acc_norm_stderr": 0.039153454088478354 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7520661157024794, "acc_stderr": 0.03941897526516301, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.03941897526516301 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7239263803680982, "acc_stderr": 0.03512385283705048, "acc_norm": 0.7239263803680982, "acc_norm_stderr": 0.03512385283705048 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.45535714285714285, "acc_stderr": 0.047268355537191, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.047268355537191 }, "harness|hendrycksTest-management|5": { "acc": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8504273504273504, "acc_stderr": 0.023365051491753715, "acc_norm": 0.8504273504273504, "acc_norm_stderr": 0.023365051491753715 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7969348659003831, "acc_stderr": 0.014385525076611578, "acc_norm": 0.7969348659003831, "acc_norm_stderr": 0.014385525076611578 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7109826589595376, "acc_stderr": 0.02440517393578323, "acc_norm": 0.7109826589595376, "acc_norm_stderr": 0.02440517393578323 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3564245810055866, "acc_stderr": 0.016018239710513398, "acc_norm": 0.3564245810055866, "acc_norm_stderr": 0.016018239710513398 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6666666666666666, "acc_stderr": 0.026992544339297243, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.026992544339297243 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.707395498392283, "acc_stderr": 0.02583989833487798, "acc_norm": 0.707395498392283, "acc_norm_stderr": 0.02583989833487798 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6851851851851852, "acc_stderr": 0.025842248700902164, "acc_norm": 0.6851851851851852, "acc_norm_stderr": 0.025842248700902164 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.42907801418439717, "acc_stderr": 0.02952591430255856, "acc_norm": 0.42907801418439717, "acc_norm_stderr": 0.02952591430255856 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.44328552803129073, "acc_stderr": 0.012687818419599923, "acc_norm": 0.44328552803129073, "acc_norm_stderr": 0.012687818419599923 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6323529411764706, "acc_stderr": 0.02928941340940319, "acc_norm": 0.6323529411764706, "acc_norm_stderr": 0.02928941340940319 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6241830065359477, "acc_stderr": 0.01959402113657744, "acc_norm": 0.6241830065359477, "acc_norm_stderr": 0.01959402113657744 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6938775510204082, "acc_stderr": 0.02950489645459596, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.02950489645459596 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8009950248756219, "acc_stderr": 0.028231365092758406, "acc_norm": 0.8009950248756219, "acc_norm_stderr": 0.028231365092758406 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-virology|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8304093567251462, "acc_stderr": 0.02878210810540171, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.02878210810540171 }, "harness|truthfulqa:mc|0": { "mc1": 0.5752753977968176, "mc1_stderr": 0.017304000957167477, "mc2": 0.7146460351141442, "mc2_stderr": 0.015047159780719415 }, "harness|winogrande|5": { "acc": 0.8453038674033149, "acc_stderr": 0.010163172650433542 }, "harness|gsm8k|5": { "acc": 0.6338134950720242, "acc_stderr": 0.013270100238748831 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

DavronSherbaev/uzbekvoice

--- license: apache-2.0 task_categories: - automatic-speech-recognition language: - uz size_categories: - 100K<n<1M ---

urialon/converted_narrative_qa

--- dataset_info: features: - name: id dtype: string - name: pid dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 18019445085 num_examples: 55003 - name: validation num_bytes: 1900648400 num_examples: 5878 - name: test num_bytes: 3228274423 num_examples: 10306 download_size: 8524652529 dataset_size: 23148367908 --- # Dataset Card for "converted_narrative_qa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

kraykzzz/Voz

--- license: openrail ---

bdsaglam/musique-answerable-2hop-subset-jerx-reward

--- dataset_info: features: - name: id dtype: string - name: jerx.input dtype: string - name: jerx.output dtype: string - name: reward dtype: int64 splits: - name: train num_bytes: 86982 num_examples: 110 download_size: 0 dataset_size: 86982 configs: - config_name: default data_files: - split: train path: data/train-* ---

Nicolas-BZRD/uld_loss_Llama-2-7b-chat-hf-qed

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: context dtype: string - name: question dtype: string - name: answers list: - name: end dtype: int64 - name: start dtype: int64 - name: string dtype: string - name: answers_generated dtype: string splits: - name: train num_bytes: 5124485 num_examples: 7007 - name: validation num_bytes: 449998 num_examples: 610 download_size: 3652432 dataset_size: 5574483 --- # Dataset Card for "uld_loss_Llama-2-7b-chat-hf-qed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)