davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
d0rj/conala-mined-ru	--- dataset_info: features: - name: question_id dtype: int64 - name: parent_answer_post_id dtype: int64 - name: prob dtype: float64 - name: snippet dtype: string - name: intent dtype: string - name: id dtype: string splits: - name: train num_bytes: 115298717.0 num_examples: 593891 download_size: 78541384 dataset_size: 115298717.0 --- # Dataset Card for "conala-mined-ru" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
autoevaluate/autoeval-eval-samsum-samsum-ec1044-95879146522	--- type: predictions tags: - autotrain - evaluation datasets: - samsum eval_info: task: summarization model: Joemgu/mlong-t5-large-sumstew metrics: [] dataset_name: samsum dataset_config: samsum dataset_split: test col_mapping: text: dialogue target: summary --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: Joemgu/mlong-t5-large-sumstew * Dataset: samsum * Config: samsum * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@baohuynhbk14](https://huggingface.co/baohuynhbk14) for evaluating this model.
CyberHarem/mutsu_kantaicollection	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of mutsu/陸奥 (Kantai Collection) This is the dataset of mutsu/陸奥 (Kantai Collection), containing 500 images and their tags. The core tags of this character are `brown_hair, short_hair, green_eyes, breasts, large_breasts, headgear, hair_between_eyes`, 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 \| 608.09 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 500 \| 377.33 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 1228 \| 781.47 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 500 \| 551.65 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1228 \| 1.02 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/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/mutsu_kantaicollection', 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 \| 11 \| ![](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, chain, looking_at_viewer, pleated_skirt, solo, white_gloves, black_skirt, smile, midriff, miniskirt, red_thighhighs, radio_antenna, simple_background, turret, cleavage, navel, rigging, white_background, blush, cannon \| \| 1 \| 39 \| ![](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) \| midriff, solo, 1girl, looking_at_viewer, white_gloves, bare_shoulders, miniskirt, hairband, navel, chain, red_thighhighs, smile \| \| 2 \| 14 \| ![](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, collarbone, looking_at_viewer, solo, smile, blush, simple_background, white_background, closed_mouth, cleavage, upper_body, alternate_costume \| \| 3 \| 8 \| ![](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, cloud, day, looking_at_viewer, outdoors, solo, blush, collarbone, cowboy_shot, navel, smile, beach, black_bikini, cleavage, ocean, side-tie_bikini_bottom, closed_mouth, flipped_hair, blue_sky, open_mouth \| \| 4 \| 15 \| ![](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, huge_breasts, looking_at_viewer, solo, thick_thighs, curvy, thighhighs, navel, cleavage, wide_hips, bikini, gloves, smile, tan, collar \| \| 5 \| 23 \| ![](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, solo, alternate_costume, looking_at_viewer, smile, obi, wide_sleeves, blush, long_sleeves, yukata, floral_print, hair_flower, striped, upper_body \| \| 6 \| 15 \| ![](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, fake_animal_ears, playboy_bunny, rabbit_ears, solo, detached_collar, wrist_cuffs, black_leotard, looking_at_viewer, bowtie, cleavage, pantyhose, simple_background, smile, strapless_leotard, blush, rabbit_tail, white_background, collarbone, cowboy_shot \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| chain \| looking_at_viewer \| pleated_skirt \| solo \| white_gloves \| black_skirt \| smile \| midriff \| miniskirt \| red_thighhighs \| radio_antenna \| simple_background \| turret \| cleavage \| navel \| rigging \| white_background \| blush \| cannon \| bare_shoulders \| hairband \| collarbone \| closed_mouth \| upper_body \| alternate_costume \| cloud \| day \| outdoors \| cowboy_shot \| beach \| black_bikini \| ocean \| side-tie_bikini_bottom \| flipped_hair \| blue_sky \| open_mouth \| huge_breasts \| thick_thighs \| curvy \| thighhighs \| wide_hips \| bikini \| gloves \| tan \| collar \| obi \| wide_sleeves \| long_sleeves \| yukata \| floral_print \| hair_flower \| striped \| fake_animal_ears \| playboy_bunny \| rabbit_ears \| detached_collar \| wrist_cuffs \| black_leotard \| bowtie \| pantyhose \| strapless_leotard \| rabbit_tail \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------\|:--------------------\|:----------------\|:-------\|:---------------\|:--------------\|:--------\|:----------\|:------------\|:-----------------\|:----------------\|:--------------------\|:---------\|:-----------\|:--------\|:----------\|:-------------------\|:--------\|:---------\|:-----------------\|:-----------\|:-------------\|:---------------\|:-------------\|:--------------------\|:--------\|:------\|:-----------\|:--------------\|:--------\|:---------------\|:--------\|:-------------------------\|:---------------\|:-----------\|:-------------\|:---------------\|:---------------\|:--------\|:-------------\|:------------\|:---------\|:---------\|:------\|:---------\|:------\|:---------------\|:---------------\|:---------\|:---------------\|:--------------\|:----------\|:-------------------\|:----------------\|:--------------\|:------------------\|:--------------\|:----------------\|:---------\|:------------\|:--------------------\|:--------------\| \| 0 \| 11 \| ![](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 \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 39 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 14 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 8 \| ![](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 \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 15 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 23 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 15 \| ![](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 \|
fformosa/LSUN_bedroom_VQA_v2	--- dataset_info: features: - name: image dtype: image - name: size sequence: int64 - name: proportion dtype: float64 - name: new_image_id dtype: int64 - name: new_attributes sequence: string splits: - name: train num_bytes: 836782860 num_examples: 58266 download_size: 815988446 dataset_size: 836782860 configs: - config_name: default data_files: - split: train path: data/train-* license: mit task_categories: - question-answering - zero-shot-classification - feature-extraction - visual-question-answering - image-classification language: - en size_categories: - 10K<n<100K --- # Dataset Card for "CSUN_bedroom_VQA_feliu_v2" ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63e128c64d82d6230587e5ee/9-vsm9GttCzxpZI6hrIJW.png)
open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser	--- pretty_name: Evaluation run of Kquant03/NeuralTrix-7B-dpo-laser dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser)\ \ 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_Kquant03__NeuralTrix-7B-dpo-laser\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-14T14:37:51.781058](https://huggingface.co/datasets/open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser/blob/main/results_2024-02-14T14-37-51.781058.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\": 0.645893629951843,\n\ \ \"acc_stderr\": 0.03226186920457953,\n \"acc_norm\": 0.6452717180915718,\n\ \ \"acc_norm_stderr\": 0.03293869736005958,\n \"mc1\": 0.6291309669522643,\n\ \ \"mc1_stderr\": 0.01690969358024884,\n \"mc2\": 0.7814534342142354,\n\ \ \"mc2_stderr\": 0.013720660446321574\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6911262798634812,\n \"acc_stderr\": 0.013501770929344003,\n\ \ \"acc_norm\": 0.7133105802047781,\n \"acc_norm_stderr\": 0.013214986329274772\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7005576578370842,\n\ \ \"acc_stderr\": 0.004570777326263903,\n \"acc_norm\": 0.8850826528579964,\n\ \ \"acc_norm_stderr\": 0.00318270383035113\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\ \ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.63,\n\ \ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6981132075471698,\n \"acc_stderr\": 0.028254200344438662,\n\ \ \"acc_norm\": 0.6981132075471698,\n \"acc_norm_stderr\": 0.028254200344438662\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7638888888888888,\n\ \ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.7638888888888888,\n\ \ \"acc_norm_stderr\": 0.03551446610810826\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\"\ : 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n\ \ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.31,\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\": 0.6416184971098265,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107224,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107224\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5087719298245614,\n\ \ \"acc_stderr\": 0.047028804320496165,\n \"acc_norm\": 0.5087719298245614,\n\ \ \"acc_norm_stderr\": 0.047028804320496165\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555498,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555498\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.42328042328042326,\n \"acc_stderr\": 0.025446365634406762,\n \"\ acc_norm\": 0.42328042328042326,\n \"acc_norm_stderr\": 0.025446365634406762\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.31,\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\": 0.7580645161290323,\n\ \ \"acc_stderr\": 0.024362599693031086,\n \"acc_norm\": 0.7580645161290323,\n\ \ \"acc_norm_stderr\": 0.024362599693031086\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\": 0.71,\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\": 0.7818181818181819,\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\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.02247325333276877,\n\ \ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.02247325333276877\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\": 0.3148148148148148,\n \"acc_stderr\": 0.02831753349606649,\n \ \ \"acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.02831753349606649\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.030778057422931673,\n\ \ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.030778057422931673\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.39072847682119205,\n \"acc_stderr\": 0.039837983066598075,\n \"\ acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.039837983066598075\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8422018348623853,\n \"acc_stderr\": 0.015630022970092427,\n \"\ acc_norm\": 0.8422018348623853,\n \"acc_norm_stderr\": 0.015630022970092427\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8333333333333334,\n \"acc_stderr\": 0.026156867523931048,\n \"\ acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.026156867523931048\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.810126582278481,\n \"acc_stderr\": 0.02553010046023349,\n \ \ \"acc_norm\": 0.810126582278481,\n \"acc_norm_stderr\": 0.02553010046023349\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.036412970813137296,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.036412970813137296\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4107142857142857,\n\ \ \"acc_stderr\": 0.046695106638751906,\n \"acc_norm\": 0.4107142857142857,\n\ \ \"acc_norm_stderr\": 0.046695106638751906\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406974,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406974\n },\n \"harness\|hendrycksTest-medical_genetics\|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-miscellaneous\|5\": {\n \"acc\": 0.8263090676883781,\n\ \ \"acc_stderr\": 0.01354741565866226,\n \"acc_norm\": 0.8263090676883781,\n\ \ \"acc_norm_stderr\": 0.01354741565866226\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7138728323699421,\n \"acc_stderr\": 0.02433214677913413,\n\ \ \"acc_norm\": 0.7138728323699421,\n \"acc_norm_stderr\": 0.02433214677913413\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4424581005586592,\n\ \ \"acc_stderr\": 0.01661139368726858,\n \"acc_norm\": 0.4424581005586592,\n\ \ \"acc_norm_stderr\": 0.01661139368726858\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7124183006535948,\n \"acc_stderr\": 0.02591780611714716,\n\ \ \"acc_norm\": 0.7124183006535948,\n \"acc_norm_stderr\": 0.02591780611714716\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6752411575562701,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7407407407407407,\n \"acc_stderr\": 0.024383665531035454,\n\ \ \"acc_norm\": 0.7407407407407407,\n \"acc_norm_stderr\": 0.024383665531035454\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\": 0.470013037809648,\n\ \ \"acc_stderr\": 0.012747248967079072,\n \"acc_norm\": 0.470013037809648,\n\ \ \"acc_norm_stderr\": 0.012747248967079072\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6691176470588235,\n \"acc_stderr\": 0.028582709753898445,\n\ \ \"acc_norm\": 0.6691176470588235,\n \"acc_norm_stderr\": 0.028582709753898445\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6748366013071896,\n \"acc_stderr\": 0.01895088677080632,\n \ \ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.01895088677080632\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7224489795918367,\n \"acc_stderr\": 0.028666857790274648,\n\ \ \"acc_norm\": 0.7224489795918367,\n \"acc_norm_stderr\": 0.028666857790274648\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.845771144278607,\n\ \ \"acc_stderr\": 0.025538433368578337,\n \"acc_norm\": 0.845771144278607,\n\ \ \"acc_norm_stderr\": 0.025538433368578337\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5602409638554217,\n\ \ \"acc_stderr\": 0.03864139923699122,\n \"acc_norm\": 0.5602409638554217,\n\ \ \"acc_norm_stderr\": 0.03864139923699122\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\": 0.6291309669522643,\n\ \ \"mc1_stderr\": 0.01690969358024884,\n \"mc2\": 0.7814534342142354,\n\ \ \"mc2_stderr\": 0.013720660446321574\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8445146014206788,\n \"acc_stderr\": 0.010184308214775777\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.690674753601213,\n \ \ \"acc_stderr\": 0.012731710925078134\n }\n}\n```" repo_url: https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser 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_14T14_37_51.781058 path: - '/details_harness\|arc:challenge\|25_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-14T14-37-51.781058.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|gsm8k\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hellaswag\|10_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-14T14-37-51.781058.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-14T14-37-51.781058.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '/details_harness\|winogrande\|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-14T14-37-51.781058.parquet' - config_name: results data_files: - split: 2024_02_14T14_37_51.781058 path: - results_2024-02-14T14-37-51.781058.parquet - split: latest path: - results_2024-02-14T14-37-51.781058.parquet --- # Dataset Card for Evaluation run of Kquant03/NeuralTrix-7B-dpo-laser <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser) 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_Kquant03__NeuralTrix-7B-dpo-laser", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-14T14:37:51.781058](https://huggingface.co/datasets/open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser/blob/main/results_2024-02-14T14-37-51.781058.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": 0.645893629951843, "acc_stderr": 0.03226186920457953, "acc_norm": 0.6452717180915718, "acc_norm_stderr": 0.03293869736005958, "mc1": 0.6291309669522643, "mc1_stderr": 0.01690969358024884, "mc2": 0.7814534342142354, "mc2_stderr": 0.013720660446321574 }, "harness\|arc:challenge\|25": { "acc": 0.6911262798634812, "acc_stderr": 0.013501770929344003, "acc_norm": 0.7133105802047781, "acc_norm_stderr": 0.013214986329274772 }, "harness\|hellaswag\|10": { "acc": 0.7005576578370842, "acc_stderr": 0.004570777326263903, "acc_norm": 0.8850826528579964, "acc_norm_stderr": 0.00318270383035113 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595853, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595853 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6981132075471698, "acc_stderr": 0.028254200344438662, "acc_norm": 0.6981132075471698, "acc_norm_stderr": 0.028254200344438662 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "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": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "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": 0.6416184971098265, "acc_stderr": 0.036563436533531585, "acc_norm": 0.6416184971098265, "acc_norm_stderr": 0.036563436533531585 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107224, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107224 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5087719298245614, "acc_stderr": 0.047028804320496165, "acc_norm": 0.5087719298245614, "acc_norm_stderr": 0.047028804320496165 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555498, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555498 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.42328042328042326, "acc_stderr": 0.025446365634406762, "acc_norm": 0.42328042328042326, "acc_norm_stderr": 0.025446365634406762 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7580645161290323, "acc_stderr": 0.024362599693031086, "acc_norm": 0.7580645161290323, "acc_norm_stderr": 0.024362599693031086 }, "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": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "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": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8911917098445595, "acc_stderr": 0.02247325333276877, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.02247325333276877 }, "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": 0.3148148148148148, "acc_stderr": 0.02831753349606649, "acc_norm": 0.3148148148148148, "acc_norm_stderr": 0.02831753349606649 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6596638655462185, "acc_stderr": 0.030778057422931673, "acc_norm": 0.6596638655462185, "acc_norm_stderr": 0.030778057422931673 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.39072847682119205, "acc_stderr": 0.039837983066598075, "acc_norm": 0.39072847682119205, "acc_norm_stderr": 0.039837983066598075 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8422018348623853, "acc_stderr": 0.015630022970092427, "acc_norm": 0.8422018348623853, "acc_norm_stderr": 0.015630022970092427 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.026156867523931048, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.026156867523931048 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.810126582278481, "acc_stderr": 0.02553010046023349, "acc_norm": 0.810126582278481, "acc_norm_stderr": 0.02553010046023349 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6905829596412556, "acc_stderr": 0.03102441174057221, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.03102441174057221 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7786259541984732, "acc_stderr": 0.036412970813137296, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.036412970813137296 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070416, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070416 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7484662576687117, "acc_stderr": 0.03408997886857529, "acc_norm": 0.7484662576687117, "acc_norm_stderr": 0.03408997886857529 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4107142857142857, "acc_stderr": 0.046695106638751906, "acc_norm": 0.4107142857142857, "acc_norm_stderr": 0.046695106638751906 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406974, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406974 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8263090676883781, "acc_stderr": 0.01354741565866226, "acc_norm": 0.8263090676883781, "acc_norm_stderr": 0.01354741565866226 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7138728323699421, "acc_stderr": 0.02433214677913413, "acc_norm": 0.7138728323699421, "acc_norm_stderr": 0.02433214677913413 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4424581005586592, "acc_stderr": 0.01661139368726858, "acc_norm": 0.4424581005586592, "acc_norm_stderr": 0.01661139368726858 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7124183006535948, "acc_stderr": 0.02591780611714716, "acc_norm": 0.7124183006535948, "acc_norm_stderr": 0.02591780611714716 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6752411575562701, "acc_stderr": 0.026596782287697043, "acc_norm": 0.6752411575562701, "acc_norm_stderr": 0.026596782287697043 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.024383665531035454, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.024383665531035454 }, "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": 0.470013037809648, "acc_stderr": 0.012747248967079072, "acc_norm": 0.470013037809648, "acc_norm_stderr": 0.012747248967079072 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6691176470588235, "acc_stderr": 0.028582709753898445, "acc_norm": 0.6691176470588235, "acc_norm_stderr": 0.028582709753898445 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6748366013071896, "acc_stderr": 0.01895088677080632, "acc_norm": 0.6748366013071896, "acc_norm_stderr": 0.01895088677080632 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7224489795918367, "acc_stderr": 0.028666857790274648, "acc_norm": 0.7224489795918367, "acc_norm_stderr": 0.028666857790274648 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.845771144278607, "acc_stderr": 0.025538433368578337, "acc_norm": 0.845771144278607, "acc_norm_stderr": 0.025538433368578337 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.03588702812826371, "acc_norm": 0.85, "acc_norm_stderr": 0.03588702812826371 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5602409638554217, "acc_stderr": 0.03864139923699122, "acc_norm": 0.5602409638554217, "acc_norm_stderr": 0.03864139923699122 }, "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": 0.6291309669522643, "mc1_stderr": 0.01690969358024884, "mc2": 0.7814534342142354, "mc2_stderr": 0.013720660446321574 }, "harness\|winogrande\|5": { "acc": 0.8445146014206788, "acc_stderr": 0.010184308214775777 }, "harness\|gsm8k\|5": { "acc": 0.690674753601213, "acc_stderr": 0.012731710925078134 } } ``` ## 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]
syeda-raisa/paraphrase_final	--- license: apache-2.0 --- #idiom paraphrase
socius/VADER_2014	--- license: cc-by-nc-sa-4.0 language: - en tags: - sentiment - social media size_categories: - 1K<n<10K ---
open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M	--- pretty_name: Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M)\ \ 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_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-12T07:34:24.161560](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M/blob/main/results_2023-12-12T07-34-24.161560.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\": 0.2574568669647554,\n\ \ \"acc_stderr\": 0.03077370055460631,\n \"acc_norm\": 0.258555233951132,\n\ \ \"acc_norm_stderr\": 0.031529415596877046,\n \"mc1\": 0.25091799265605874,\n\ \ \"mc1_stderr\": 0.015176985027707687,\n \"mc2\": 0.38841425251899087,\n\ \ \"mc2_stderr\": 0.014859033830490542\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.1945392491467577,\n \"acc_stderr\": 0.011567709174648728,\n\ \ \"acc_norm\": 0.24573378839590443,\n \"acc_norm_stderr\": 0.012581033453730113\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.2842063333997212,\n\ \ \"acc_stderr\": 0.004501137895230712,\n \"acc_norm\": 0.29426409081856203,\n\ \ \"acc_norm_stderr\": 0.00454779896412667\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909283\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2518518518518518,\n\ \ \"acc_stderr\": 0.037498507091740234,\n \"acc_norm\": 0.2518518518518518,\n\ \ \"acc_norm_stderr\": 0.037498507091740234\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\": 0.22,\n\ \ \"acc_stderr\": 0.0416333199893227,\n \"acc_norm\": 0.22,\n \ \ \"acc_norm_stderr\": 0.0416333199893227\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.02461829819586651,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.02461829819586651\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\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\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\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.26011560693641617,\n\ \ \"acc_stderr\": 0.03345036916788992,\n \"acc_norm\": 0.26011560693641617,\n\ \ \"acc_norm_stderr\": 0.03345036916788992\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.23529411764705882,\n \"acc_stderr\": 0.04220773659171453,\n\ \ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.04220773659171453\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.15,\n \"acc_stderr\": 0.035887028128263734,\n \"acc_norm\": 0.15,\n\ \ \"acc_norm_stderr\": 0.035887028128263734\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.2765957446808511,\n \"acc_stderr\": 0.0292418838696288,\n\ \ \"acc_norm\": 0.2765957446808511,\n \"acc_norm_stderr\": 0.0292418838696288\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\": 0.33793103448275863,\n \"acc_stderr\": 0.039417076320648906,\n\ \ \"acc_norm\": 0.33793103448275863,\n \"acc_norm_stderr\": 0.039417076320648906\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24867724867724866,\n \"acc_stderr\": 0.02226181769240019,\n \"\ acc_norm\": 0.24867724867724866,\n \"acc_norm_stderr\": 0.02226181769240019\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.18253968253968253,\n\ \ \"acc_stderr\": 0.03455071019102146,\n \"acc_norm\": 0.18253968253968253,\n\ \ \"acc_norm_stderr\": 0.03455071019102146\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.19,\n \"acc_stderr\": 0.039427724440366234,\n \ \ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.039427724440366234\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.3064516129032258,\n \"acc_stderr\": 0.026226485652553883,\n \"\ acc_norm\": 0.3064516129032258,\n \"acc_norm_stderr\": 0.026226485652553883\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.2561576354679803,\n \"acc_stderr\": 0.030712730070982592,\n \"\ acc_norm\": 0.2561576354679803,\n \"acc_norm_stderr\": 0.030712730070982592\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.21818181818181817,\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\"\ : 0.3434343434343434,\n \"acc_stderr\": 0.033832012232444426,\n \"\ acc_norm\": 0.3434343434343434,\n \"acc_norm_stderr\": 0.033832012232444426\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.37823834196891193,\n \"acc_stderr\": 0.034998072761933396,\n\ \ \"acc_norm\": 0.37823834196891193,\n \"acc_norm_stderr\": 0.034998072761933396\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.35128205128205126,\n \"acc_stderr\": 0.024203665177902803,\n\ \ \"acc_norm\": 0.35128205128205126,\n \"acc_norm_stderr\": 0.024203665177902803\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2518518518518518,\n \"acc_stderr\": 0.02646611753895991,\n \ \ \"acc_norm\": 0.2518518518518518,\n \"acc_norm_stderr\": 0.02646611753895991\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.24369747899159663,\n \"acc_stderr\": 0.027886828078380565,\n\ \ \"acc_norm\": 0.24369747899159663,\n \"acc_norm_stderr\": 0.027886828078380565\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.037345356767871984,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.037345356767871984\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.3211009174311927,\n \"acc_stderr\": 0.020018149772733744,\n \"\ acc_norm\": 0.3211009174311927,\n \"acc_norm_stderr\": 0.020018149772733744\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4675925925925926,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.4675925925925926,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.2647058823529412,\n \"acc_stderr\": 0.03096451792692341,\n \"\ acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.03096451792692341\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.2320675105485232,\n \"acc_stderr\": 0.027479744550808514,\n \ \ \"acc_norm\": 0.2320675105485232,\n \"acc_norm_stderr\": 0.027479744550808514\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.23766816143497757,\n\ \ \"acc_stderr\": 0.02856807946471428,\n \"acc_norm\": 0.23766816143497757,\n\ \ \"acc_norm_stderr\": 0.02856807946471428\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.1984732824427481,\n \"acc_stderr\": 0.03498149385462472,\n\ \ \"acc_norm\": 0.1984732824427481,\n \"acc_norm_stderr\": 0.03498149385462472\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2892561983471074,\n \"acc_stderr\": 0.04139112727635464,\n \"\ acc_norm\": 0.2892561983471074,\n \"acc_norm_stderr\": 0.04139112727635464\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.26993865030674846,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.26993865030674846,\n \"acc_norm_stderr\": 0.034878251684978906\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.23214285714285715,\n\ \ \"acc_stderr\": 0.04007341809755806,\n \"acc_norm\": 0.23214285714285715,\n\ \ \"acc_norm_stderr\": 0.04007341809755806\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.23300970873786409,\n \"acc_stderr\": 0.041858325989283136,\n\ \ \"acc_norm\": 0.23300970873786409,\n \"acc_norm_stderr\": 0.041858325989283136\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.19230769230769232,\n\ \ \"acc_stderr\": 0.0258192332564837,\n \"acc_norm\": 0.19230769230769232,\n\ \ \"acc_norm_stderr\": 0.0258192332564837\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\": 0.2796934865900383,\n\ \ \"acc_stderr\": 0.016050792148036546,\n \"acc_norm\": 0.2796934865900383,\n\ \ \"acc_norm_stderr\": 0.016050792148036546\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.23410404624277456,\n \"acc_stderr\": 0.02279711027807114,\n\ \ \"acc_norm\": 0.23410404624277456,\n \"acc_norm_stderr\": 0.02279711027807114\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.24183006535947713,\n \"acc_stderr\": 0.024518195641879334,\n\ \ \"acc_norm\": 0.24183006535947713,\n \"acc_norm_stderr\": 0.024518195641879334\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.26366559485530544,\n\ \ \"acc_stderr\": 0.02502553850053234,\n \"acc_norm\": 0.26366559485530544,\n\ \ \"acc_norm_stderr\": 0.02502553850053234\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.023132376234543332,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.023132376234543332\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.2801418439716312,\n \"acc_stderr\": 0.026789172351140245,\n \ \ \"acc_norm\": 0.2801418439716312,\n \"acc_norm_stderr\": 0.026789172351140245\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.23663624511082137,\n\ \ \"acc_stderr\": 0.010855137351572735,\n \"acc_norm\": 0.23663624511082137,\n\ \ \"acc_norm_stderr\": 0.010855137351572735\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4338235294117647,\n \"acc_stderr\": 0.030105636570016643,\n\ \ \"acc_norm\": 0.4338235294117647,\n \"acc_norm_stderr\": 0.030105636570016643\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.2647058823529412,\n \"acc_stderr\": 0.017848089574913226,\n \ \ \"acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.017848089574913226\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.17272727272727273,\n\ \ \"acc_stderr\": 0.0362069183392922,\n \"acc_norm\": 0.17272727272727273,\n\ \ \"acc_norm_stderr\": 0.0362069183392922\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.2163265306122449,\n \"acc_stderr\": 0.026358916334904035,\n\ \ \"acc_norm\": 0.2163265306122449,\n \"acc_norm_stderr\": 0.026358916334904035\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.23880597014925373,\n\ \ \"acc_stderr\": 0.030147775935409217,\n \"acc_norm\": 0.23880597014925373,\n\ \ \"acc_norm_stderr\": 0.030147775935409217\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909281,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909281\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.1927710843373494,\n\ \ \"acc_stderr\": 0.03070982405056527,\n \"acc_norm\": 0.1927710843373494,\n\ \ \"acc_norm_stderr\": 0.03070982405056527\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.23976608187134502,\n \"acc_stderr\": 0.03274485211946956,\n\ \ \"acc_norm\": 0.23976608187134502,\n \"acc_norm_stderr\": 0.03274485211946956\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.25091799265605874,\n\ \ \"mc1_stderr\": 0.015176985027707687,\n \"mc2\": 0.38841425251899087,\n\ \ \"mc2_stderr\": 0.014859033830490542\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.49013417521704816,\n \"acc_stderr\": 0.014049749833367589\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.02122820318423048,\n \ \ \"acc_stderr\": 0.003970449129848635\n }\n}\n```" repo_url: https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M 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_12T07_34_24.161560 path: - '/details_harness\|arc:challenge\|25_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-12T07-34-24.161560.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|gsm8k\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hellaswag\|10_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-12T07-34-24.161560.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-12T07-34-24.161560.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '/details_harness\|winogrande\|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-12T07-34-24.161560.parquet' - config_name: results data_files: - split: 2023_12_12T07_34_24.161560 path: - results_2023-12-12T07-34-24.161560.parquet - split: latest path: - results_2023-12-12T07-34-24.161560.parquet --- # Dataset Card for Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M) 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_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-12T07:34:24.161560](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M/blob/main/results_2023-12-12T07-34-24.161560.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": 0.2574568669647554, "acc_stderr": 0.03077370055460631, "acc_norm": 0.258555233951132, "acc_norm_stderr": 0.031529415596877046, "mc1": 0.25091799265605874, "mc1_stderr": 0.015176985027707687, "mc2": 0.38841425251899087, "mc2_stderr": 0.014859033830490542 }, "harness\|arc:challenge\|25": { "acc": 0.1945392491467577, "acc_stderr": 0.011567709174648728, "acc_norm": 0.24573378839590443, "acc_norm_stderr": 0.012581033453730113 }, "harness\|hellaswag\|10": { "acc": 0.2842063333997212, "acc_stderr": 0.004501137895230712, "acc_norm": 0.29426409081856203, "acc_norm_stderr": 0.00454779896412667 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2518518518518518, "acc_stderr": 0.037498507091740234, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.037498507091740234 }, "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": 0.22, "acc_stderr": 0.0416333199893227, "acc_norm": 0.22, "acc_norm_stderr": 0.0416333199893227 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.2, "acc_stderr": 0.02461829819586651, "acc_norm": 0.2, "acc_norm_stderr": 0.02461829819586651 }, "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": 0.23, "acc_stderr": 0.04229525846816505, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816505 }, "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": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.26011560693641617, "acc_stderr": 0.03345036916788992, "acc_norm": 0.26011560693641617, "acc_norm_stderr": 0.03345036916788992 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.23529411764705882, "acc_stderr": 0.04220773659171453, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.04220773659171453 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.15, "acc_stderr": 0.035887028128263734, "acc_norm": 0.15, "acc_norm_stderr": 0.035887028128263734 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.2765957446808511, "acc_stderr": 0.0292418838696288, "acc_norm": 0.2765957446808511, "acc_norm_stderr": 0.0292418838696288 }, "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": 0.33793103448275863, "acc_stderr": 0.039417076320648906, "acc_norm": 0.33793103448275863, "acc_norm_stderr": 0.039417076320648906 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24867724867724866, "acc_stderr": 0.02226181769240019, "acc_norm": 0.24867724867724866, "acc_norm_stderr": 0.02226181769240019 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.18253968253968253, "acc_stderr": 0.03455071019102146, "acc_norm": 0.18253968253968253, "acc_norm_stderr": 0.03455071019102146 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.19, "acc_stderr": 0.039427724440366234, "acc_norm": 0.19, "acc_norm_stderr": 0.039427724440366234 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.3064516129032258, "acc_stderr": 0.026226485652553883, "acc_norm": 0.3064516129032258, "acc_norm_stderr": 0.026226485652553883 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.2561576354679803, "acc_stderr": 0.030712730070982592, "acc_norm": 0.2561576354679803, "acc_norm_stderr": 0.030712730070982592 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.3434343434343434, "acc_stderr": 0.033832012232444426, "acc_norm": 0.3434343434343434, "acc_norm_stderr": 0.033832012232444426 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.37823834196891193, "acc_stderr": 0.034998072761933396, "acc_norm": 0.37823834196891193, "acc_norm_stderr": 0.034998072761933396 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.35128205128205126, "acc_stderr": 0.024203665177902803, "acc_norm": 0.35128205128205126, "acc_norm_stderr": 0.024203665177902803 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2518518518518518, "acc_stderr": 0.02646611753895991, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.02646611753895991 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.24369747899159663, "acc_stderr": 0.027886828078380565, "acc_norm": 0.24369747899159663, "acc_norm_stderr": 0.027886828078380565 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2980132450331126, "acc_stderr": 0.037345356767871984, "acc_norm": 0.2980132450331126, "acc_norm_stderr": 0.037345356767871984 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.3211009174311927, "acc_stderr": 0.020018149772733744, "acc_norm": 0.3211009174311927, "acc_norm_stderr": 0.020018149772733744 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4675925925925926, "acc_stderr": 0.03402801581358966, "acc_norm": 0.4675925925925926, "acc_norm_stderr": 0.03402801581358966 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.2647058823529412, "acc_stderr": 0.03096451792692341, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.03096451792692341 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.2320675105485232, "acc_stderr": 0.027479744550808514, "acc_norm": 0.2320675105485232, "acc_norm_stderr": 0.027479744550808514 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.23766816143497757, "acc_stderr": 0.02856807946471428, "acc_norm": 0.23766816143497757, "acc_norm_stderr": 0.02856807946471428 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.1984732824427481, "acc_stderr": 0.03498149385462472, "acc_norm": 0.1984732824427481, "acc_norm_stderr": 0.03498149385462472 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.2892561983471074, "acc_stderr": 0.04139112727635464, "acc_norm": 0.2892561983471074, "acc_norm_stderr": 0.04139112727635464 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.26993865030674846, "acc_stderr": 0.034878251684978906, "acc_norm": 0.26993865030674846, "acc_norm_stderr": 0.034878251684978906 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.23214285714285715, "acc_stderr": 0.04007341809755806, "acc_norm": 0.23214285714285715, "acc_norm_stderr": 0.04007341809755806 }, "harness\|hendrycksTest-management\|5": { "acc": 0.23300970873786409, "acc_stderr": 0.041858325989283136, "acc_norm": 0.23300970873786409, "acc_norm_stderr": 0.041858325989283136 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.19230769230769232, "acc_stderr": 0.0258192332564837, "acc_norm": 0.19230769230769232, "acc_norm_stderr": 0.0258192332564837 }, "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": 0.2796934865900383, "acc_stderr": 0.016050792148036546, "acc_norm": 0.2796934865900383, "acc_norm_stderr": 0.016050792148036546 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.23410404624277456, "acc_stderr": 0.02279711027807114, "acc_norm": 0.23410404624277456, "acc_norm_stderr": 0.02279711027807114 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.24183006535947713, "acc_stderr": 0.024518195641879334, "acc_norm": 0.24183006535947713, "acc_norm_stderr": 0.024518195641879334 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.26366559485530544, "acc_stderr": 0.02502553850053234, "acc_norm": 0.26366559485530544, "acc_norm_stderr": 0.02502553850053234 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.023132376234543332, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.023132376234543332 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.2801418439716312, "acc_stderr": 0.026789172351140245, "acc_norm": 0.2801418439716312, "acc_norm_stderr": 0.026789172351140245 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.23663624511082137, "acc_stderr": 0.010855137351572735, "acc_norm": 0.23663624511082137, "acc_norm_stderr": 0.010855137351572735 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4338235294117647, "acc_stderr": 0.030105636570016643, "acc_norm": 0.4338235294117647, "acc_norm_stderr": 0.030105636570016643 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.2647058823529412, "acc_stderr": 0.017848089574913226, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.017848089574913226 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.17272727272727273, "acc_stderr": 0.0362069183392922, "acc_norm": 0.17272727272727273, "acc_norm_stderr": 0.0362069183392922 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.2163265306122449, "acc_stderr": 0.026358916334904035, "acc_norm": 0.2163265306122449, "acc_norm_stderr": 0.026358916334904035 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.23880597014925373, "acc_stderr": 0.030147775935409217, "acc_norm": 0.23880597014925373, "acc_norm_stderr": 0.030147775935409217 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909281, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909281 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.1927710843373494, "acc_stderr": 0.03070982405056527, "acc_norm": 0.1927710843373494, "acc_norm_stderr": 0.03070982405056527 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.23976608187134502, "acc_stderr": 0.03274485211946956, "acc_norm": 0.23976608187134502, "acc_norm_stderr": 0.03274485211946956 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.25091799265605874, "mc1_stderr": 0.015176985027707687, "mc2": 0.38841425251899087, "mc2_stderr": 0.014859033830490542 }, "harness\|winogrande\|5": { "acc": 0.49013417521704816, "acc_stderr": 0.014049749833367589 }, "harness\|gsm8k\|5": { "acc": 0.02122820318423048, "acc_stderr": 0.003970449129848635 } } ``` ## 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]
bys2058/mydataset_bai	--- dataset_info: features: - name: image dtype: image - name: image_caption dtype: string splits: - name: train num_bytes: 672992285.125 num_examples: 1375 download_size: 672547372 dataset_size: 672992285.125 --- # Dataset Card for "mydataset_bai" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
deivsu/2ne1CL	--- license: openrail ---
joey234/mmlu-human_sexuality-original-neg	--- 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 splits: - name: test num_bytes: 3185.297709923664 num_examples: 13 download_size: 6364 dataset_size: 3185.297709923664 --- # Dataset Card for "mmlu-human_sexuality-original-neg" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ciempiess/voxforge_spanish	--- license: gpl-3.0 ---
wmt/wmt16	--- annotations_creators: - no-annotation language_creators: - found language: - cs - de - en - fi - ro - ru - tr license: - unknown multilinguality: - translation size_categories: - 10M<n<100M source_datasets: - extended\|europarl_bilingual - extended\|news_commentary - extended\|setimes - extended\|un_multi task_categories: - translation task_ids: [] paperswithcode_id: wmt-2016 pretty_name: WMT16 dataset_info: - config_name: cs-en features: - name: translation dtype: translation: languages: - cs - en splits: - name: train num_bytes: 295995226 num_examples: 997240 - name: validation num_bytes: 572195 num_examples: 2656 - name: test num_bytes: 707862 num_examples: 2999 download_size: 178250444 dataset_size: 297275283 - config_name: de-en features: - name: translation dtype: translation: languages: - de - en splits: - name: train num_bytes: 1373099816 num_examples: 4548885 - name: validation num_bytes: 522981 num_examples: 2169 - name: test num_bytes: 735508 num_examples: 2999 download_size: 827152589 dataset_size: 1374358305 - config_name: fi-en features: - name: translation dtype: translation: languages: - fi - en splits: - name: train num_bytes: 605145153 num_examples: 2073394 - name: validation num_bytes: 306327 num_examples: 1370 - name: test num_bytes: 1410507 num_examples: 6000 download_size: 348306427 dataset_size: 606861987 - config_name: ro-en features: - name: translation dtype: translation: languages: - ro - en splits: - name: train num_bytes: 188287711 num_examples: 610320 - name: validation num_bytes: 561791 num_examples: 1999 - name: test num_bytes: 539208 num_examples: 1999 download_size: 108584039 dataset_size: 189388710 - config_name: ru-en features: - name: translation dtype: translation: languages: - ru - en splits: - name: train num_bytes: 448322024 num_examples: 1516162 - name: validation num_bytes: 955964 num_examples: 2818 - name: test num_bytes: 1050669 num_examples: 2998 download_size: 231557371 dataset_size: 450328657 - config_name: tr-en features: - name: translation dtype: translation: languages: - tr - en splits: - name: train num_bytes: 60416449 num_examples: 205756 - name: validation num_bytes: 240642 num_examples: 1001 - name: test num_bytes: 732428 num_examples: 3000 download_size: 37389436 dataset_size: 61389519 configs: - config_name: cs-en data_files: - split: train path: cs-en/train-* - split: validation path: cs-en/validation-* - split: test path: cs-en/test-* - config_name: de-en data_files: - split: train path: de-en/train-* - split: validation path: de-en/validation-* - split: test path: de-en/test-* - config_name: fi-en data_files: - split: train path: fi-en/train-* - split: validation path: fi-en/validation-* - split: test path: fi-en/test-* - config_name: ro-en data_files: - split: train path: ro-en/train-* - split: validation path: ro-en/validation-* - split: test path: ro-en/test-* - config_name: ru-en data_files: - split: train path: ru-en/train-* - split: validation path: ru-en/validation-* - split: test path: ru-en/test-* - config_name: tr-en data_files: - split: train path: tr-en/train-* - split: validation path: tr-en/validation-* - split: test path: tr-en/test-* --- # Dataset Card for "wmt16" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: [http://www.statmt.org/wmt16/translation-task.html](http://www.statmt.org/wmt16/translation-task.html) - Repository: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of downloaded dataset files: 1.69 GB - Size of the generated dataset: 297.28 MB - Total amount of disk used: 1.99 GB ### Dataset Summary <div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400"> <p><b>Warning:</b> There are issues with the Common Crawl corpus data (<a href="https://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz">training-parallel-commoncrawl.tgz</a>):</p> <ul> <li>Non-English files contain many English sentences.</li> <li>Their "parallel" sentences in English are not aligned: they are uncorrelated with their counterpart.</li> </ul> <p>We have contacted the WMT organizers, and in response, they have indicated that they do not have plans to update the Common Crawl corpus data. Their rationale pertains to the expectation that such data has been superseded, primarily by CCMatrix, and to some extent, by ParaCrawl datasets.</p> </div> Translation dataset based on the data from statmt.org. Versions exist for different years using a combination of data sources. The base `wmt` allows you to create a custom dataset by choosing your own data/language pair. This can be done as follows: ```python from datasets import inspect_dataset, load_dataset_builder inspect_dataset("wmt16", "path/to/scripts") builder = load_dataset_builder( "path/to/scripts/wmt_utils.py", language_pair=("fr", "de"), subsets={ datasets.Split.TRAIN: ["commoncrawl_frde"], datasets.Split.VALIDATION: ["euelections_dev2019"], }, ) # Standard version builder.download_and_prepare() ds = builder.as_dataset() # Streamable version ds = builder.as_streaming_dataset() ``` ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### cs-en - Size of downloaded dataset files: 1.69 GB - Size of the generated dataset: 297.28 MB - Total amount of disk used: 1.99 GB An example of 'validation' looks as follows. ``` ``` ### Data Fields The data fields are the same among all splits. #### cs-en - `translation`: a multilingual `string` variable, with possible languages including `cs`, `en`. ### Data Splits \|name \|train \|validation\|test\| \|-----\|-----:\|---------:\|---:\| \|cs-en\|997240\| 2656\|2999\| ## 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{bojar-EtAl:2016:WMT1, author = {Bojar, Ond {r}ej and Chatterjee, Rajen and Federmann, Christian and Graham, Yvette and Haddow, Barry and Huck, Matthias and Jimeno Yepes, Antonio and Koehn, Philipp and Logacheva, Varvara and Monz, Christof and Negri, Matteo and Neveol, Aurelie and Neves, Mariana and Popel, Martin and Post, Matt and Rubino, Raphael and Scarton, Carolina and Specia, Lucia and Turchi, Marco and Verspoor, Karin and Zampieri, Marcos}, title = {Findings of the 2016 Conference on Machine Translation}, booktitle = {Proceedings of the First Conference on Machine Translation}, month = {August}, year = {2016}, address = {Berlin, Germany}, publisher = {Association for Computational Linguistics}, pages = {131--198}, url = {http://www.aclweb.org/anthology/W/W16/W16-2301} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.
TinyPixel/lima_2	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 2960580 num_examples: 1030 download_size: 1703604 dataset_size: 2960580 --- # Dataset Card for "lima_2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kbharat7/DogChestXrayDatasetNew	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 444263783.625 num_examples: 1395 download_size: 444252328 dataset_size: 444263783.625 --- # Dataset Card for "DogChestXrayDatasetNew" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
autoevaluate/autoeval-staging-eval-squad_v2-squad_v2-76c05b-14906070	--- type: predictions tags: - autotrain - evaluation datasets: - squad_v2 eval_info: task: extractive_question_answering model: deepset/roberta-base-squad2-covid metrics: ['bertscore'] dataset_name: squad_v2 dataset_config: squad_v2 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: deepset/roberta-base-squad2-covid * Dataset: squad_v2 * Config: squad_v2 * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@nonchalant-nagavalli](https://huggingface.co/nonchalant-nagavalli) for evaluating this model.
UsmanMalikLearn/Pak-Legal-Llama2	--- dataset_info: features: - name: transformed_text dtype: string splits: - name: train num_bytes: 857655 num_examples: 2229 download_size: 369985 dataset_size: 857655 configs: - config_name: default data_files: - split: train path: data/train-* ---
youlive789/sales	--- dataset_info: features: - name: original_image dtype: image - name: edited_image dtype: image - name: edit_promt dtype: string splits: - name: train num_bytes: 111237824.0 num_examples: 140 download_size: 111236059 dataset_size: 111237824.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
Techatach/mini-platypus	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 4186564 num_examples: 1000 download_size: 2245921 dataset_size: 4186564 configs: - config_name: default data_files: - split: train path: data/train-* ---
tyzhu/squad_qa_context_v5_full_recite_full_passage_random_permute_rerun_8	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 6222942.0 num_examples: 2385 - name: validation num_bytes: 808532 num_examples: 300 download_size: 1374285 dataset_size: 7031474.0 --- # Dataset Card for "squad_qa_context_v5_full_recite_full_passage_random_permute_rerun_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Xokito/datasethevelyn	--- license: openrail ---
CyberHarem/le_malin_azurlane	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of le_malin/ル・マラン/恶毒 (Azur Lane) This is the dataset of le_malin/ル・マラン/恶毒 (Azur Lane), containing 500 images and their tags. The core tags of this character are `long_hair, blue_eyes, white_hair, very_long_hair, bangs, breasts, small_breasts, animal_ears, rabbit_ears, braid, twin_braids, fake_animal_ears, hair_bun, double_bun, animal_ear_fluff`, 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 \| 933.07 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 500 \| 419.25 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 1378 \| 988.88 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 500 \| 767.52 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1378 \| 1.52 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/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/le_malin_azurlane', 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 \| 7 \| ![](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, choker, criss-cross_halter, solo, white_dress, white_rose, bare_shoulders, blush, hair_between_eyes, looking_at_viewer, sleeveless_dress, collarbone, sidelocks, bare_arms, parted_lips, barefoot, grey_hair, hand_up, on_back \| \| 1 \| 17 \| ![](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, solo, white_pantyhose, sidelocks, white_dress, hair_between_eyes, looking_at_viewer, long_sleeves, symbol-shaped_pupils, blush, navel, detached_sleeves, parted_lips, sitting, tutu \| \| 2 \| 13 \| ![](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, solo, white_dress, white_pantyhose, hair_between_eyes, long_sleeves, sidelocks, holding_sword, looking_at_viewer, thighband_pantyhose, closed_mouth, rapier, simple_background, underboob_cutout, blush, white_background, cape, hair_bow, full_body, pocket_watch, ribbon \| \| 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, looking_at_viewer, navel, nipples, nude, simple_background, solo, +_+, hair_between_eyes, blush, collarbone, hair_ribbon, loli, open_mouth, white_background, anus, clitoris, closed_mouth, spread_pussy, standing, symbol-shaped_pupils, uncensored \| \| 4 \| 18 \| ![](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, bare_shoulders, solo, looking_at_viewer, white_bikini, symbol-shaped_pupils, sidelocks, barefoot, blush, bare_legs, headphones_around_neck, hammock, arm_garter, on_back, hair_between_eyes, navel, ass, feet, thighs, purple_flower, stomach \| \| 5 \| 9 \| ![](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, looking_at_viewer, official_alternate_costume, playboy_bunny, solo, white_leotard, white_pantyhose, wrist_cuffs, blush, simple_background, white_background, choker, sitting, +_+, closed_mouth, thigh_strap, twintails, hairband, rabbit_tail \| \| 6 \| 10 \| ![](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, ass, looking_at_viewer, official_alternate_costume, playboy_bunny, rabbit_tail, solo, white_leotard, white_pantyhose, from_behind, hairband, looking_back, +_+, simple_background, thigh_strap, white_background, wrist_cuffs, blush, parted_lips, sideboob, thighs \| \| 7 \| 7 \| ![](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, covered_navel, looking_at_viewer, official_alternate_costume, playboy_bunny, simple_background, solo, white_leotard, white_pantyhose, blush, thigh_strap, white_background, wrist_cuffs, choker, closed_mouth, highleg_leotard, +_+, thighs, twintails \| \| 8 \| 5 \| ![](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, looking_at_viewer, official_alternate_costume, playboy_bunny, rabbit_tail, solo, white_leotard, white_pantyhose, +_+, ass, from_behind, looking_back, no_shoes, wrist_cuffs, couch, blush, full_body, low_twin_braids, sideboob, thigh_strap, wariza, white_hairband \| \| 9 \| 16 \| ![](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, hetero, solo_focus, penis, sex, 1boy, blush, censored, nipples, +_+, pussy, vaginal, open_mouth, pantyhose, official_alternate_costume, straddling, loli, looking_at_viewer, playboy_bunny, simple_background, spread_legs, clothed_female_nude_male, girl_on_top, white_leotard, crotchless, dark-skinned_male, interracial, navel, wrist_cuffs \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| +_+ \| 1girl \| choker \| criss-cross_halter \| solo \| white_dress \| white_rose \| bare_shoulders \| blush \| hair_between_eyes \| looking_at_viewer \| sleeveless_dress \| collarbone \| sidelocks \| bare_arms \| parted_lips \| barefoot \| grey_hair \| hand_up \| on_back \| white_pantyhose \| long_sleeves \| symbol-shaped_pupils \| navel \| detached_sleeves \| sitting \| tutu \| holding_sword \| thighband_pantyhose \| closed_mouth \| rapier \| simple_background \| underboob_cutout \| white_background \| cape \| hair_bow \| full_body \| pocket_watch \| ribbon \| nipples \| nude \| hair_ribbon \| loli \| open_mouth \| anus \| clitoris \| spread_pussy \| standing \| uncensored \| white_bikini \| bare_legs \| headphones_around_neck \| hammock \| arm_garter \| ass \| feet \| thighs \| purple_flower \| stomach \| official_alternate_costume \| playboy_bunny \| white_leotard \| wrist_cuffs \| thigh_strap \| twintails \| hairband \| rabbit_tail \| from_behind \| looking_back \| sideboob \| covered_navel \| highleg_leotard \| no_shoes \| couch \| low_twin_braids \| wariza \| white_hairband \| hetero \| solo_focus \| penis \| sex \| 1boy \| censored \| pussy \| vaginal \| pantyhose \| straddling \| spread_legs \| clothed_female_nude_male \| girl_on_top \| crotchless \| dark-skinned_male \| interracial \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:------\|:--------\|:---------\|:---------------------\|:-------\|:--------------\|:-------------\|:-----------------\|:--------\|:--------------------\|:--------------------\|:-------------------\|:-------------\|:------------\|:------------\|:--------------\|:-----------\|:------------\|:----------\|:----------\|:------------------\|:---------------\|:-----------------------\|:--------\|:-------------------\|:----------\|:-------\|:----------------\|:----------------------\|:---------------\|:---------\|:--------------------\|:-------------------\|:-------------------\|:-------\|:-----------\|:------------\|:---------------\|:---------\|:----------\|:-------\|:--------------\|:-------\|:-------------\|:-------\|:-----------\|:---------------\|:-----------\|:-------------\|:---------------\|:------------\|:-------------------------\|:----------\|:-------------\|:------\|:-------\|:---------\|:----------------\|:----------\|:-----------------------------\|:----------------\|:----------------\|:--------------\|:--------------\|:------------\|:-----------\|:--------------\|:--------------\|:---------------\|:-----------\|:----------------\|:------------------\|:-----------\|:--------\|:------------------\|:---------\|:-----------------\|:---------\|:-------------\|:--------\|:------\|:-------\|:-----------\|:--------\|:----------\|:------------\|:-------------\|:--------------\|:---------------------------\|:--------------\|:-------------\|:--------------------\|:--------------\| \| 0 \| 7 \| ![](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 \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 17 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 13 \| ![](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 \| 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 \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 18 \| ![](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 \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 9 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 10 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 7 \| 7 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 8 \| 5 \| ![](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 \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 9 \| 16 \| ![](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 \| X \| X \| X \| X \| X \| X \|
davisonye/cg_pad_mai_dav_1	--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': maize '1': paddy_rice '2': unknown splits: - name: train num_bytes: 5026074267.1 num_examples: 1683 - name: validation num_bytes: 308905569.0 num_examples: 89 - name: test num_bytes: 330351357.0 num_examples: 96 download_size: 6239113776 dataset_size: 5665331193.1 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
autoevaluate/autoeval-eval-futin__guess-en-6f8c6a-2012266598	--- type: predictions tags: - autotrain - evaluation datasets: - futin/guess eval_info: task: text_zero_shot_classification model: facebook/opt-2.7b metrics: [] dataset_name: futin/guess dataset_config: en dataset_split: test col_mapping: text: text classes: classes target: target --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Zero-Shot Text Classification * Model: facebook/opt-2.7b * Dataset: futin/guess * Config: en * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@futin](https://huggingface.co/futin) for evaluating this model.
ctang/1k_deontology_train_llama2	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 679786 num_examples: 1000 download_size: 84465 dataset_size: 679786 configs: - config_name: default data_files: - split: train path: data/train-* ---
HuggingFaceH4/ifeval	--- license: apache-2.0 --- # Dataset Card for IFEval <!-- Provide a quick summary of the dataset. --> This dataset contains the prompts used in Google's [Instruction-Following Evaluation for Large Language Models](https://arxiv.org/abs/2311.07911). You can find the original source data and evaluation code [here](https://github.com/google-research/google-research/tree/master/instruction_following_eval). ## 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]
open-llm-leaderboard/details_porkorbeef__Llama-2-13b-sf	--- pretty_name: Evaluation run of porkorbeef/Llama-2-13b-sf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [porkorbeef/Llama-2-13b-sf](https://huggingface.co/porkorbeef/Llama-2-13b-sf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the 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_porkorbeef__Llama-2-13b-sf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-19T10:54:43.878914](https://huggingface.co/datasets/open-llm-leaderboard/details_porkorbeef__Llama-2-13b-sf/blob/main/results_2023-10-19T10-54-43.878914.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\": 0.0,\n \"\ em_stderr\": 0.0,\n \"f1\": 2.3070469798657717e-05,\n \"f1_stderr\"\ : 1.0056123859027576e-05,\n \"acc\": 0.2517758484609313,\n \"acc_stderr\"\ : 0.0070260655734579345\n },\n \"harness\|drop\|3\": {\n \"em\": 0.0,\n\ \ \"em_stderr\": 0.0,\n \"f1\": 2.3070469798657717e-05,\n \"\ f1_stderr\": 1.0056123859027576e-05\n },\n \"harness\|gsm8k\|5\": {\n \ \ \"acc\": 0.0,\n \"acc_stderr\": 0.0\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5035516969218626,\n \"acc_stderr\": 0.014052131146915869\n\ \ }\n}\n```" repo_url: https://huggingface.co/porkorbeef/Llama-2-13b-sf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_drop_3 data_files: - split: 2023_10_19T10_54_43.878914 path: - '/details_harness\|drop\|3_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-19T10-54-43.878914.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_19T10_54_43.878914 path: - '/details_harness\|gsm8k\|5_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-19T10-54-43.878914.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_19T10_54_43.878914 path: - '/details_harness\|winogrande\|5_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-19T10-54-43.878914.parquet' - config_name: results data_files: - split: 2023_10_19T10_54_43.878914 path: - results_2023-10-19T10-54-43.878914.parquet - split: latest path: - results_2023-10-19T10-54-43.878914.parquet --- # Dataset Card for Evaluation run of porkorbeef/Llama-2-13b-sf ## Dataset Description - Homepage: - Repository: https://huggingface.co/porkorbeef/Llama-2-13b-sf - 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 [porkorbeef/Llama-2-13b-sf](https://huggingface.co/porkorbeef/Llama-2-13b-sf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the 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_porkorbeef__Llama-2-13b-sf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-19T10:54:43.878914](https://huggingface.co/datasets/open-llm-leaderboard/details_porkorbeef__Llama-2-13b-sf/blob/main/results_2023-10-19T10-54-43.878914.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": 0.0, "em_stderr": 0.0, "f1": 2.3070469798657717e-05, "f1_stderr": 1.0056123859027576e-05, "acc": 0.2517758484609313, "acc_stderr": 0.0070260655734579345 }, "harness\|drop\|3": { "em": 0.0, "em_stderr": 0.0, "f1": 2.3070469798657717e-05, "f1_stderr": 1.0056123859027576e-05 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5035516969218626, "acc_stderr": 0.014052131146915869 } } ``` ### 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]
kkcosmos/instagram-images-with-captions	--- license: unknown dataset_info: features: - name: image dtype: image - name: item_id dtype: int64 - name: image_path dtype: string - name: caption dtype: string splits: - name: train num_bytes: 3516512787.609302 num_examples: 28360 - name: test num_bytes: 391305063.2386981 num_examples: 3152 download_size: 0 dataset_size: 3907817850.848 ---
bhjhk/samino11	--- license: bigscience-bloom-rail-1.0 ---
AdapterOcean/med_alpaca_standardized_cluster_68_std	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 16970130 num_examples: 24531 download_size: 8602932 dataset_size: 16970130 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_68_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ivanfdzm/Arq-Style	--- license: afl-3.0 ---
Seanxh/twitter_dataset_1713173437	--- 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: 25981 num_examples: 64 download_size: 15681 dataset_size: 25981 configs: - config_name: default data_files: - split: train path: data/train-* ---
chirp-watai/audio_dataset	--- task_categories: - zero-shot-classification tags: - audio - sound pretty_name: audio size_categories: - 1K<n<10K --- # Audio Dataset This dataset consists of audio data for the following categories: * Coughing * Running water * Toilet flush * Other sounds Although this data is unbalanced, data augmentations can be added to process the data for audio classification. The file structure looks as follows: \- audio/        \- coughing/        \- toilet_flush/        \- running_water/        \- other_1/        \- other_2/
AdapterOcean/med_alpaca_standardized_cluster_10_std	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 18079246 num_examples: 25458 download_size: 9399571 dataset_size: 18079246 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_10_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Capsekai/Badge_crafts	--- license: creativeml-openrail-m task_categories: - text-to-image - image-classification language: - en tags: - badges - crafts pretty_name: Badge Craft Dataset size_categories: - 1K<n<10K --- # Do what you will with the data this is old photos of crafts I used to make - just abide by the liscence above and you good to go!
dlwh/Multi_Legal_Pile	--- license: cc-by-4.0 ---
luckeciano/hermes-features-ultrafeedback	--- configs: - config_name: default data_files: - split: train path: "train.csv" - split: valid path: "eval.csv" - split: test path: "test.csv" --- --- license: apache-2.0 ---
AIGym/TextbookChapters	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1013875541 num_examples: 77932 download_size: 504483603 dataset_size: 1013875541 configs: - config_name: default data_files: - split: train path: data/train-* ---
lshowway/wikipedia.reorder.svo.de	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 2385745587 num_examples: 1137317 download_size: 1063402086 dataset_size: 2385745587 --- # Dataset Card for "wikipedia.reorder.svo.de" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
pvduy/exp_dpo_1	--- 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 splits: - name: train num_bytes: 120210099 num_examples: 14313 - name: test num_bytes: 4538037 num_examples: 750 download_size: 64945705 dataset_size: 124748136 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
GVJahnavi/Crops_set	--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot '1': Corn_(maize)___Common_rust_ '2': Corn_(maize)___Northern_Leaf_Blight '3': Corn_(maize)___healthy '4': Pepper,_bell___Bacterial_spot '5': Pepper,_bell___healthy '6': Potato___Early_blight '7': Potato___Late_blight '8': Potato___healthy '9': Soybean___healthy '10': Tomato___Bacterial_spot '11': Tomato___Early_blight '12': Tomato___Late_blight '13': Tomato___Leaf_Mold '14': Tomato___Septoria_leaf_spot '15': Tomato___Spider_mites Two-spotted_spider_mite '16': Tomato___Target_Spot '17': Tomato___Tomato_Yellow_Leaf_Curl_Virus '18': Tomato___Tomato_mosaic_virus '19': Tomato___healthy splits: - name: train num_bytes: 381142501.808 num_examples: 25384 - name: test num_bytes: 93073910.262 num_examples: 6346 download_size: 514893426 dataset_size: 474216412.07000005 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
benayas/sst2_llm_v0	--- dataset_info: features: - name: sentence dtype: string - name: label dtype: class_label: names: '0': negative '1': positive - name: idx dtype: int32 - name: eval_text dtype: string - name: text dtype: string splits: - name: train num_bytes: 67924009 num_examples: 67349 - name: validation num_bytes: 1016356 num_examples: 872 - name: test num_bytes: 2104899 num_examples: 1821 download_size: 13965924 dataset_size: 71045264 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
seidouz/Diabetes	--- license: openrail --- Simulated dataset for the project https://github.com/bitDalei/Diabetes-Classification-with-Heterogeneous-Data Explanation - column 0: label - column 1-576: FGM data - column 576-587: Biomarkers data You might notice some of consecutive rows have same biomarkers, this means that these few rows are contributed by the same patient. There are also some missing value in biomarkers, presented as '0'.
Aashi/Science_Q_and_A_dataset	--- license: mit --- This dataset has been extracted from the class 9 CBSE science book for finetuning an LLM for a chatbot application.
notjoemartinez/Mozart	--- license: apache-2.0 ---
prathap-reddy/autotrain-data-climate-text-classification	--- language: - en task_categories: - text-classification --- # AutoTrain Dataset for project: climate-text-classification ## Dataset Descritpion This dataset has been automatically processed by AutoTrain for project climate-text-classification. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "text": "So the way our model has currently been built, we would look to pay down debt with our free cash flow generation that we're planning on generating this year, which is around $20 million to $30 million.", "target": 0 }, { "text": "So we don't see any big drama on the long-term FMPs as a result of this.", "target": 0 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "text": "Value(dtype='string', id=None)", "target": "ClassLabel(num_classes=2, names=['0', '1'], id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 1919 \| \| valid \| 481 \|
ofir408/try2	--- license: apache-2.0 ---
mfidabel/common_voice_16_1_semisupervised	--- dataset_info: features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string - name: predicted_sentence dtype: string splits: - name: whisper.medium num_bytes: 8271758359.625 num_examples: 18779 - name: whisper.small num_bytes: 2763174559.625 num_examples: 18779 - name: whisper.large.v3 num_bytes: 8271776000.625 num_examples: 18779 - name: whisper.tiny num_bytes: 8271831240.625 num_examples: 18779 download_size: 23466393916 dataset_size: 27578540160.5 configs: - config_name: default data_files: - split: whisper.medium path: data/whisper.medium-* - split: whisper.small path: data/whisper.small-* - split: whisper.large.v3 path: data/whisper.large.v3-* - split: whisper.tiny path: data/whisper.tiny-* ---
PS-123/LungNodule	--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 132655580.844 num_examples: 1723 download_size: 157049632 dataset_size: 132655580.844 --- # Dataset Card for "LungNodule" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
quibblerquery/youTubeData	--- license: mit ---
open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca	--- pretty_name: Evaluation run of TFLai/gpt-neo-1.3B-4bit-alpaca dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TFLai/gpt-neo-1.3B-4bit-alpaca](https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T17:57:15.784929](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca/blob/main/results_2023-09-23T17-57-15.784929.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0009437919463087249,\n\ \ \"em_stderr\": 0.00031446531194133983,\n \"f1\": 0.05118708053691287,\n\ \ \"f1_stderr\": 0.001257884278930374,\n \"acc\": 0.2821159149890526,\n\ \ \"acc_stderr\": 0.007628169555669113\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0009437919463087249,\n \"em_stderr\": 0.00031446531194133983,\n\ \ \"f1\": 0.05118708053691287,\n \"f1_stderr\": 0.001257884278930374\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.002274450341167551,\n \ \ \"acc_stderr\": 0.0013121578148674233\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5619573796369376,\n \"acc_stderr\": 0.013944181296470803\n\ \ }\n}\n```" repo_url: https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca 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_08_18T13_07_16.687815 path: - '/details_harness\|arc:challenge\|25_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-18T13:07:16.687815.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T17_57_15.784929 path: - '/details_harness\|drop\|3_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-23T17-57-15.784929.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T17_57_15.784929 path: - '/details_harness\|gsm8k\|5_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-23T17-57-15.784929.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hellaswag\|10_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T13:07:16.687815.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_18T13_07_16.687815 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-18T13:07:16.687815.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T17_57_15.784929 path: - '/details_harness\|winogrande\|5_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-23T17-57-15.784929.parquet' - config_name: results data_files: - split: 2023_08_18T13_07_16.687815 path: - results_2023-08-18T13:07:16.687815.parquet - split: 2023_09_23T17_57_15.784929 path: - results_2023-09-23T17-57-15.784929.parquet - split: latest path: - results_2023-09-23T17-57-15.784929.parquet --- # Dataset Card for Evaluation run of TFLai/gpt-neo-1.3B-4bit-alpaca ## Dataset Description - Homepage: - Repository: https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca - 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 [TFLai/gpt-neo-1.3B-4bit-alpaca](https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T17:57:15.784929](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca/blob/main/results_2023-09-23T17-57-15.784929.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0009437919463087249, "em_stderr": 0.00031446531194133983, "f1": 0.05118708053691287, "f1_stderr": 0.001257884278930374, "acc": 0.2821159149890526, "acc_stderr": 0.007628169555669113 }, "harness\|drop\|3": { "em": 0.0009437919463087249, "em_stderr": 0.00031446531194133983, "f1": 0.05118708053691287, "f1_stderr": 0.001257884278930374 }, "harness\|gsm8k\|5": { "acc": 0.002274450341167551, "acc_stderr": 0.0013121578148674233 }, "harness\|winogrande\|5": { "acc": 0.5619573796369376, "acc_stderr": 0.013944181296470803 } } ``` ### 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]
devjirawat8/Air_Vehicle	--- license: mit ---
CyberHarem/glasgow_azurlane	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of glasgow/グラスゴー/格拉斯哥 (Azur Lane) This is the dataset of glasgow/グラスゴー/格拉斯哥 (Azur Lane), containing 68 images and their tags. The core tags of this character are `long_hair, twintails, bangs, breasts, black_hair, maid_headdress, ribbon, blue_eyes, bow, low_twintails, large_breasts, brown_hair, green_eyes`, 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 \| 68 \| 76.60 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 68 \| 44.66 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 167 \| 96.49 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 68 \| 68.16 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 167 \| 132.74 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/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/glasgow_azurlane', 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 \| 46 \| ![](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, maid, solo, blush, looking_at_viewer, frills, simple_background, wrist_cuffs, white_background, black_dress, puffy_short_sleeves, choker, cleavage, white_apron \| \| 1 \| 18 \| ![](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, blush, looking_at_viewer, white_shirt, school_uniform, plaid_skirt, red_necktie, solo, long_sleeves, pleated_skirt, collared_shirt, black_jacket, hairclip, red_skirt, blazer, hair_between_eyes, open_jacket, hair_ribbon, open_mouth, very_long_hair \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| maid \| solo \| blush \| looking_at_viewer \| frills \| simple_background \| wrist_cuffs \| white_background \| black_dress \| puffy_short_sleeves \| choker \| cleavage \| white_apron \| white_shirt \| school_uniform \| plaid_skirt \| red_necktie \| long_sleeves \| pleated_skirt \| collared_shirt \| black_jacket \| hairclip \| red_skirt \| blazer \| hair_between_eyes \| open_jacket \| hair_ribbon \| open_mouth \| very_long_hair \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:-------\|:--------\|:--------------------\|:---------\|:--------------------\|:--------------\|:-------------------\|:--------------\|:----------------------\|:---------\|:-----------\|:--------------\|:--------------\|:-----------------\|:--------------\|:--------------\|:---------------\|:----------------\|:-----------------\|:---------------\|:-----------\|:------------\|:---------\|:--------------------\|:--------------\|:--------------\|:-------------\|:-----------------\| \| 0 \| 46 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 18 \| ![](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 \|
NathanRoll/TalkBank_CA_CABNC_1	--- dataset_info: features: - name: audio sequence: float32 - name: __index_level_0__ dtype: string splits: - name: train num_bytes: 17080612876 num_examples: 100 download_size: 17100223923 dataset_size: 17080612876 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "TalkBank_CA_CABNC_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
datasciathlete/open-ner-english	--- dataset_info: features: - name: entities list: - name: entity_mentions sequence: string - name: entity_type dtype: string - name: spans sequence: sequence: int64 - name: text dtype: string splits: - name: train num_bytes: 72484875.50541525 num_examples: 36711 - name: validation num_bytes: 18121712.494584758 num_examples: 9178 download_size: 90106463 dataset_size: 90606588.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
cimadure/snow_removal_transactions_in_montreal	--- license: cc-by-4.0 ---
open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused	--- pretty_name: Evaluation run of stanford-oval/Llama-2-7b-WikiChat-fused dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [stanford-oval/Llama-2-7b-WikiChat-fused](https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused)\ \ 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_stanford-oval__Llama-2-7b-WikiChat-fused\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-16T05:29:49.524111](https://huggingface.co/datasets/open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused/blob/main/results_2024-01-16T05-29-49.524111.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\": 0.3993615462452277,\n\ \ \"acc_stderr\": 0.03426948672248777,\n \"acc_norm\": 0.4047541011703342,\n\ \ \"acc_norm_stderr\": 0.035187845841979204,\n \"mc1\": 0.30966952264381886,\n\ \ \"mc1_stderr\": 0.01618574435514492,\n \"mc2\": 0.46362057203759177,\n\ \ \"mc2_stderr\": 0.015792473170958256\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.47696245733788395,\n \"acc_stderr\": 0.014595873205358262,\n\ \ \"acc_norm\": 0.5068259385665529,\n \"acc_norm_stderr\": 0.014610029151379813\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5690101573391755,\n\ \ \"acc_stderr\": 0.00494202620027959,\n \"acc_norm\": 0.7499502091216889,\n\ \ \"acc_norm_stderr\": 0.004321564303822422\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\": 0.37777777777777777,\n\ \ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.37777777777777777,\n\ \ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.32894736842105265,\n \"acc_stderr\": 0.038234289699266046,\n\ \ \"acc_norm\": 0.32894736842105265,\n \"acc_norm_stderr\": 0.038234289699266046\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.46,\n\ \ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.46,\n \ \ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.4188679245283019,\n \"acc_stderr\": 0.030365050829115208,\n\ \ \"acc_norm\": 0.4188679245283019,\n \"acc_norm_stderr\": 0.030365050829115208\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.4652777777777778,\n\ \ \"acc_stderr\": 0.04171115858181618,\n \"acc_norm\": 0.4652777777777778,\n\ \ \"acc_norm_stderr\": 0.04171115858181618\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952344,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952344\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3179190751445087,\n\ \ \"acc_stderr\": 0.0355068398916558,\n \"acc_norm\": 0.3179190751445087,\n\ \ \"acc_norm_stderr\": 0.0355068398916558\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.41,\n\ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.37446808510638296,\n \"acc_stderr\": 0.03163910665367291,\n\ \ \"acc_norm\": 0.37446808510638296,\n \"acc_norm_stderr\": 0.03163910665367291\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3157894736842105,\n\ \ \"acc_stderr\": 0.043727482902780064,\n \"acc_norm\": 0.3157894736842105,\n\ \ \"acc_norm_stderr\": 0.043727482902780064\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.38620689655172413,\n \"acc_stderr\": 0.04057324734419035,\n\ \ \"acc_norm\": 0.38620689655172413,\n \"acc_norm_stderr\": 0.04057324734419035\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2724867724867725,\n \"acc_stderr\": 0.022930973071633356,\n \"\ acc_norm\": 0.2724867724867725,\n \"acc_norm_stderr\": 0.022930973071633356\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.040061680838488774,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.040061680838488774\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.4290322580645161,\n\ \ \"acc_stderr\": 0.028156036538233217,\n \"acc_norm\": 0.4290322580645161,\n\ \ \"acc_norm_stderr\": 0.028156036538233217\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.24630541871921183,\n \"acc_stderr\": 0.030315099285617715,\n\ \ \"acc_norm\": 0.24630541871921183,\n \"acc_norm_stderr\": 0.030315099285617715\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\"\ : 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.41818181818181815,\n \"acc_stderr\": 0.03851716319398393,\n\ \ \"acc_norm\": 0.41818181818181815,\n \"acc_norm_stderr\": 0.03851716319398393\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.4898989898989899,\n \"acc_stderr\": 0.035616254886737454,\n \"\ acc_norm\": 0.4898989898989899,\n \"acc_norm_stderr\": 0.035616254886737454\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.5492227979274611,\n \"acc_stderr\": 0.03590910952235524,\n\ \ \"acc_norm\": 0.5492227979274611,\n \"acc_norm_stderr\": 0.03590910952235524\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4153846153846154,\n \"acc_stderr\": 0.02498535492310234,\n \ \ \"acc_norm\": 0.4153846153846154,\n \"acc_norm_stderr\": 0.02498535492310234\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.23333333333333334,\n \"acc_stderr\": 0.025787874220959316,\n \ \ \"acc_norm\": 0.23333333333333334,\n \"acc_norm_stderr\": 0.025787874220959316\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.42436974789915966,\n \"acc_stderr\": 0.032104790510157764,\n\ \ \"acc_norm\": 0.42436974789915966,\n \"acc_norm_stderr\": 0.032104790510157764\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969654,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969654\n },\n\ \ \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\": 0.5247706422018349,\n\ \ \"acc_stderr\": 0.021410999753635914,\n \"acc_norm\": 0.5247706422018349,\n\ \ \"acc_norm_stderr\": 0.021410999753635914\n },\n \"harness\|hendrycksTest-high_school_statistics\|5\"\ : {\n \"acc\": 0.3888888888888889,\n \"acc_stderr\": 0.033247089118091176,\n\ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.033247089118091176\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.45098039215686275,\n \"acc_stderr\": 0.03492406104163613,\n \"\ acc_norm\": 0.45098039215686275,\n \"acc_norm_stderr\": 0.03492406104163613\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.4388185654008439,\n \"acc_stderr\": 0.032302649315470375,\n \ \ \"acc_norm\": 0.4388185654008439,\n \"acc_norm_stderr\": 0.032302649315470375\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.4618834080717489,\n\ \ \"acc_stderr\": 0.03346015011973228,\n \"acc_norm\": 0.4618834080717489,\n\ \ \"acc_norm_stderr\": 0.03346015011973228\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.4198473282442748,\n \"acc_stderr\": 0.04328577215262971,\n\ \ \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.04328577215262971\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.4462809917355372,\n \"acc_stderr\": 0.0453793517794788,\n \"acc_norm\"\ : 0.4462809917355372,\n \"acc_norm_stderr\": 0.0453793517794788\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.4351851851851852,\n\ \ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.4351851851851852,\n\ \ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.4233128834355828,\n \"acc_stderr\": 0.038818912133343826,\n\ \ \"acc_norm\": 0.4233128834355828,\n \"acc_norm_stderr\": 0.038818912133343826\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.38392857142857145,\n\ \ \"acc_stderr\": 0.04616143075028547,\n \"acc_norm\": 0.38392857142857145,\n\ \ \"acc_norm_stderr\": 0.04616143075028547\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.5145631067961165,\n \"acc_stderr\": 0.049486373240266356,\n\ \ \"acc_norm\": 0.5145631067961165,\n \"acc_norm_stderr\": 0.049486373240266356\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.5811965811965812,\n\ \ \"acc_stderr\": 0.03232128912157792,\n \"acc_norm\": 0.5811965811965812,\n\ \ \"acc_norm_stderr\": 0.03232128912157792\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.5759897828863346,\n\ \ \"acc_stderr\": 0.017672263329084222,\n \"acc_norm\": 0.5759897828863346,\n\ \ \"acc_norm_stderr\": 0.017672263329084222\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.3699421965317919,\n \"acc_stderr\": 0.025992472029306376,\n\ \ \"acc_norm\": 0.3699421965317919,\n \"acc_norm_stderr\": 0.025992472029306376\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.28044692737430166,\n\ \ \"acc_stderr\": 0.01502408388332289,\n \"acc_norm\": 0.28044692737430166,\n\ \ \"acc_norm_stderr\": 0.01502408388332289\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.4150326797385621,\n \"acc_stderr\": 0.028213504177824103,\n\ \ \"acc_norm\": 0.4150326797385621,\n \"acc_norm_stderr\": 0.028213504177824103\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.44694533762057875,\n\ \ \"acc_stderr\": 0.028237769422085335,\n \"acc_norm\": 0.44694533762057875,\n\ \ \"acc_norm_stderr\": 0.028237769422085335\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.3487654320987654,\n \"acc_stderr\": 0.02651759772446501,\n\ \ \"acc_norm\": 0.3487654320987654,\n \"acc_norm_stderr\": 0.02651759772446501\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.29432624113475175,\n \"acc_stderr\": 0.027187127011503786,\n \ \ \"acc_norm\": 0.29432624113475175,\n \"acc_norm_stderr\": 0.027187127011503786\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3200782268578879,\n\ \ \"acc_stderr\": 0.011914791947638519,\n \"acc_norm\": 0.3200782268578879,\n\ \ \"acc_norm_stderr\": 0.011914791947638519\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4411764705882353,\n \"acc_stderr\": 0.030161911930767102,\n\ \ \"acc_norm\": 0.4411764705882353,\n \"acc_norm_stderr\": 0.030161911930767102\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.34967320261437906,\n \"acc_stderr\": 0.019291961895066365,\n \ \ \"acc_norm\": 0.34967320261437906,\n \"acc_norm_stderr\": 0.019291961895066365\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.45454545454545453,\n\ \ \"acc_stderr\": 0.04769300568972744,\n \"acc_norm\": 0.45454545454545453,\n\ \ \"acc_norm_stderr\": 0.04769300568972744\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.3469387755102041,\n \"acc_stderr\": 0.030472526026726496,\n\ \ \"acc_norm\": 0.3469387755102041,\n \"acc_norm_stderr\": 0.030472526026726496\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.5422885572139303,\n\ \ \"acc_stderr\": 0.035228658640995975,\n \"acc_norm\": 0.5422885572139303,\n\ \ \"acc_norm_stderr\": 0.035228658640995975\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.04999999999999999,\n \ \ \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.04999999999999999\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.3493975903614458,\n\ \ \"acc_stderr\": 0.0371172519074075,\n \"acc_norm\": 0.3493975903614458,\n\ \ \"acc_norm_stderr\": 0.0371172519074075\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.5906432748538012,\n \"acc_stderr\": 0.03771283107626544,\n\ \ \"acc_norm\": 0.5906432748538012,\n \"acc_norm_stderr\": 0.03771283107626544\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.30966952264381886,\n\ \ \"mc1_stderr\": 0.01618574435514492,\n \"mc2\": 0.46362057203759177,\n\ \ \"mc2_stderr\": 0.015792473170958256\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6906077348066298,\n \"acc_stderr\": 0.012991329330822999\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.000758150113722517,\n \ \ \"acc_stderr\": 0.0007581501137225212\n }\n}\n```" repo_url: https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused 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_16T05_29_49.524111 path: - '/details_harness\|arc:challenge\|25_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-16T05-29-49.524111.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|gsm8k\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hellaswag\|10_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-16T05-29-49.524111.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-16T05-29-49.524111.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '/details_harness\|winogrande\|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-16T05-29-49.524111.parquet' - config_name: results data_files: - split: 2024_01_16T05_29_49.524111 path: - results_2024-01-16T05-29-49.524111.parquet - split: latest path: - results_2024-01-16T05-29-49.524111.parquet --- # Dataset Card for Evaluation run of stanford-oval/Llama-2-7b-WikiChat-fused <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [stanford-oval/Llama-2-7b-WikiChat-fused](https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused) 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_stanford-oval__Llama-2-7b-WikiChat-fused", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-16T05:29:49.524111](https://huggingface.co/datasets/open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused/blob/main/results_2024-01-16T05-29-49.524111.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": 0.3993615462452277, "acc_stderr": 0.03426948672248777, "acc_norm": 0.4047541011703342, "acc_norm_stderr": 0.035187845841979204, "mc1": 0.30966952264381886, "mc1_stderr": 0.01618574435514492, "mc2": 0.46362057203759177, "mc2_stderr": 0.015792473170958256 }, "harness\|arc:challenge\|25": { "acc": 0.47696245733788395, "acc_stderr": 0.014595873205358262, "acc_norm": 0.5068259385665529, "acc_norm_stderr": 0.014610029151379813 }, "harness\|hellaswag\|10": { "acc": 0.5690101573391755, "acc_stderr": 0.00494202620027959, "acc_norm": 0.7499502091216889, "acc_norm_stderr": 0.004321564303822422 }, "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": 0.37777777777777777, "acc_stderr": 0.04188307537595853, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.04188307537595853 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.32894736842105265, "acc_stderr": 0.038234289699266046, "acc_norm": 0.32894736842105265, "acc_norm_stderr": 0.038234289699266046 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.4188679245283019, "acc_stderr": 0.030365050829115208, "acc_norm": 0.4188679245283019, "acc_norm_stderr": 0.030365050829115208 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.4652777777777778, "acc_stderr": 0.04171115858181618, "acc_norm": 0.4652777777777778, "acc_norm_stderr": 0.04171115858181618 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.34, "acc_stderr": 0.047609522856952344, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952344 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3179190751445087, "acc_stderr": 0.0355068398916558, "acc_norm": 0.3179190751445087, "acc_norm_stderr": 0.0355068398916558 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.37446808510638296, "acc_stderr": 0.03163910665367291, "acc_norm": 0.37446808510638296, "acc_norm_stderr": 0.03163910665367291 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.3157894736842105, "acc_stderr": 0.043727482902780064, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.043727482902780064 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.38620689655172413, "acc_stderr": 0.04057324734419035, "acc_norm": 0.38620689655172413, "acc_norm_stderr": 0.04057324734419035 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2724867724867725, "acc_stderr": 0.022930973071633356, "acc_norm": 0.2724867724867725, "acc_norm_stderr": 0.022930973071633356 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.040061680838488774, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.040061680838488774 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.4290322580645161, "acc_stderr": 0.028156036538233217, "acc_norm": 0.4290322580645161, "acc_norm_stderr": 0.028156036538233217 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.24630541871921183, "acc_stderr": 0.030315099285617715, "acc_norm": 0.24630541871921183, "acc_norm_stderr": 0.030315099285617715 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.41818181818181815, "acc_stderr": 0.03851716319398393, "acc_norm": 0.41818181818181815, "acc_norm_stderr": 0.03851716319398393 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.4898989898989899, "acc_stderr": 0.035616254886737454, "acc_norm": 0.4898989898989899, "acc_norm_stderr": 0.035616254886737454 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.5492227979274611, "acc_stderr": 0.03590910952235524, "acc_norm": 0.5492227979274611, "acc_norm_stderr": 0.03590910952235524 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.4153846153846154, "acc_stderr": 0.02498535492310234, "acc_norm": 0.4153846153846154, "acc_norm_stderr": 0.02498535492310234 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.23333333333333334, "acc_stderr": 0.025787874220959316, "acc_norm": 0.23333333333333334, "acc_norm_stderr": 0.025787874220959316 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.42436974789915966, "acc_stderr": 0.032104790510157764, "acc_norm": 0.42436974789915966, "acc_norm_stderr": 0.032104790510157764 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969654, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969654 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5247706422018349, "acc_stderr": 0.021410999753635914, "acc_norm": 0.5247706422018349, "acc_norm_stderr": 0.021410999753635914 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.033247089118091176, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.033247089118091176 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.45098039215686275, "acc_stderr": 0.03492406104163613, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.03492406104163613 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.4388185654008439, "acc_stderr": 0.032302649315470375, "acc_norm": 0.4388185654008439, "acc_norm_stderr": 0.032302649315470375 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.4618834080717489, "acc_stderr": 0.03346015011973228, "acc_norm": 0.4618834080717489, "acc_norm_stderr": 0.03346015011973228 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.4198473282442748, "acc_stderr": 0.04328577215262971, "acc_norm": 0.4198473282442748, "acc_norm_stderr": 0.04328577215262971 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.4462809917355372, "acc_stderr": 0.0453793517794788, "acc_norm": 0.4462809917355372, "acc_norm_stderr": 0.0453793517794788 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.4351851851851852, "acc_stderr": 0.04792898170907061, "acc_norm": 0.4351851851851852, "acc_norm_stderr": 0.04792898170907061 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.4233128834355828, "acc_stderr": 0.038818912133343826, "acc_norm": 0.4233128834355828, "acc_norm_stderr": 0.038818912133343826 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.38392857142857145, "acc_stderr": 0.04616143075028547, "acc_norm": 0.38392857142857145, "acc_norm_stderr": 0.04616143075028547 }, "harness\|hendrycksTest-management\|5": { "acc": 0.5145631067961165, "acc_stderr": 0.049486373240266356, "acc_norm": 0.5145631067961165, "acc_norm_stderr": 0.049486373240266356 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.5811965811965812, "acc_stderr": 0.03232128912157792, "acc_norm": 0.5811965811965812, "acc_norm_stderr": 0.03232128912157792 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.5759897828863346, "acc_stderr": 0.017672263329084222, "acc_norm": 0.5759897828863346, "acc_norm_stderr": 0.017672263329084222 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.3699421965317919, "acc_stderr": 0.025992472029306376, "acc_norm": 0.3699421965317919, "acc_norm_stderr": 0.025992472029306376 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.28044692737430166, "acc_stderr": 0.01502408388332289, "acc_norm": 0.28044692737430166, "acc_norm_stderr": 0.01502408388332289 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.4150326797385621, "acc_stderr": 0.028213504177824103, "acc_norm": 0.4150326797385621, "acc_norm_stderr": 0.028213504177824103 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.44694533762057875, "acc_stderr": 0.028237769422085335, "acc_norm": 0.44694533762057875, "acc_norm_stderr": 0.028237769422085335 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.3487654320987654, "acc_stderr": 0.02651759772446501, "acc_norm": 0.3487654320987654, "acc_norm_stderr": 0.02651759772446501 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.29432624113475175, "acc_stderr": 0.027187127011503786, "acc_norm": 0.29432624113475175, "acc_norm_stderr": 0.027187127011503786 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3200782268578879, "acc_stderr": 0.011914791947638519, "acc_norm": 0.3200782268578879, "acc_norm_stderr": 0.011914791947638519 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4411764705882353, "acc_stderr": 0.030161911930767102, "acc_norm": 0.4411764705882353, "acc_norm_stderr": 0.030161911930767102 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.34967320261437906, "acc_stderr": 0.019291961895066365, "acc_norm": 0.34967320261437906, "acc_norm_stderr": 0.019291961895066365 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.45454545454545453, "acc_stderr": 0.04769300568972744, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.04769300568972744 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.3469387755102041, "acc_stderr": 0.030472526026726496, "acc_norm": 0.3469387755102041, "acc_norm_stderr": 0.030472526026726496 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.5422885572139303, "acc_stderr": 0.035228658640995975, "acc_norm": 0.5422885572139303, "acc_norm_stderr": 0.035228658640995975 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.45, "acc_stderr": 0.04999999999999999, "acc_norm": 0.45, "acc_norm_stderr": 0.04999999999999999 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.3493975903614458, "acc_stderr": 0.0371172519074075, "acc_norm": 0.3493975903614458, "acc_norm_stderr": 0.0371172519074075 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.5906432748538012, "acc_stderr": 0.03771283107626544, "acc_norm": 0.5906432748538012, "acc_norm_stderr": 0.03771283107626544 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.30966952264381886, "mc1_stderr": 0.01618574435514492, "mc2": 0.46362057203759177, "mc2_stderr": 0.015792473170958256 }, "harness\|winogrande\|5": { "acc": 0.6906077348066298, "acc_stderr": 0.012991329330822999 }, "harness\|gsm8k\|5": { "acc": 0.000758150113722517, "acc_stderr": 0.0007581501137225212 } } ``` ## 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]
distilled-one-sec-cv12-each-chunk-uniq/chunk_54	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1332826588.0 num_examples: 259709 download_size: 1366988795 dataset_size: 1332826588.0 --- # Dataset Card for "chunk_54" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
julia-wenkmann/TennisSegmentation	--- dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 1159771633.0 num_examples: 197 download_size: 77225573 dataset_size: 1159771633.0 configs: - config_name: default data_files: - split: train path: data/train-* --- - Category Name: `object` - ID: `1` - Color: RGB(0, 113, 188) - Category Name: `ball` - ID: `2` - Color: RGB(216, 82, 24) - Category Name: `playerTop` - ID: `3` - Color: RGB(236, 176, 31) - Category Name: `playerBottom` - ID: `4` - Color: RGB(125, 46, 141) - Category Name: `court` - ID: `5` - Color: RGB(118, 171, 47)
Birchlabs/openai-prm800k-phase2_test-stepwise-critique	--- license: mit ---
n3rd0/VSI_biology_QA	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1341870 num_examples: 4500 - name: test num_bytes: 242060 num_examples: 794 download_size: 518043 dataset_size: 1583930 --- # Dataset Card for "VSI_biology_QA" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AshanGimhana/testing001	--- license: mit ---
germank/hh-generated_flan_t5_large_with_features2_flan_t5_large	--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string - name: 'biased:' dtype: int64 - name: easy-to-understand dtype: int64 - name: enough-detail dtype: int64 - name: factuality dtype: int64 - name: fail-to-consider-context dtype: int64 - name: fail-to-consider-individual-preferences dtype: int64 - name: helpfulness dtype: int64 - name: intent dtype: int64 - name: readability dtype: int64 - name: relevance dtype: int64 - name: repetetive dtype: int64 - name: specificity dtype: int64 - name: too-long dtype: int64 - name: log_score dtype: float64 splits: - name: train num_bytes: 408123 num_examples: 1600 download_size: 87285 dataset_size: 408123 --- # Dataset Card for "hh-generated_flan_t5_large_with_features2_flan_t5_large" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
reza-alipour/discofuse_1percent	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: connective_string dtype: string - name: discourse_type dtype: string - name: coherent_second_sentence dtype: string - name: has_coref_type_pronoun dtype: float32 - name: incoherent_first_sentence dtype: string - name: incoherent_second_sentence dtype: string - name: has_coref_type_nominal dtype: float32 - name: coherent_first_sentence dtype: string splits: - name: train num_bytes: 63778517.906742156 num_examples: 163105 download_size: 42876638 dataset_size: 63778517.906742156 --- # Dataset Card for "discofuse_1percent" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AdapterOcean/med_alpaca_standardized_cluster_39_std	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 8221814 num_examples: 19165 download_size: 4380540 dataset_size: 8221814 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_39_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tdh87/STORYTELLERV100	--- license: apache-2.0 ---
Glavin001/startup-interviews	--- license: cc-by-nc-2.0 task_categories: - question-answering - text-generation language: - en size_categories: - n<1K ---
zelalt/great_papers_augmentation	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 2663516.5807451624 num_examples: 1731 download_size: 1670568 dataset_size: 2663516.5807451624 configs: - config_name: default data_files: - split: train path: data/train-* ---
psroy/mini-platypus-guanaco-one-400	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 543862 num_examples: 400 download_size: 328169 dataset_size: 543862 configs: - config_name: default data_files: - split: train path: data/train-* ---
BitBasher/mini-dataset-978	--- dataset_info: features: - name: expected_output dtype: string - name: instruction dtype: string - name: input_content dtype: string splits: - name: train num_bytes: 825340 num_examples: 978 download_size: 229603 dataset_size: 825340 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_YeungNLP__firefly-llama-13b	--- pretty_name: Evaluation run of YeungNLP/firefly-llama-13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [YeungNLP/firefly-llama-13b](https://huggingface.co/YeungNLP/firefly-llama-13b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_YeungNLP__firefly-llama-13b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-15T14:09:32.562166](https://huggingface.co/datasets/open-llm-leaderboard/details_YeungNLP__firefly-llama-13b/blob/main/results_2023-10-15T14-09-32.562166.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\": 0.12720218120805368,\n\ \ \"em_stderr\": 0.003412272897129365,\n \"f1\": 0.22689702181208146,\n\ \ \"f1_stderr\": 0.003654793246945971,\n \"acc\": 0.418998511823731,\n\ \ \"acc_stderr\": 0.009810630903312568\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.12720218120805368,\n \"em_stderr\": 0.003412272897129365,\n\ \ \"f1\": 0.22689702181208146,\n \"f1_stderr\": 0.003654793246945971\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.08188021228203184,\n \ \ \"acc_stderr\": 0.0075523385277169374\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7561168113654302,\n \"acc_stderr\": 0.012068923278908197\n\ \ }\n}\n```" repo_url: https://huggingface.co/YeungNLP/firefly-llama-13b 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_19T18_51_43.691477 path: - '/details_harness\|arc:challenge\|25_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-07-19T18:51:43.691477.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_15T14_09_32.562166 path: - '/details_harness\|drop\|3_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-15T14-09-32.562166.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_15T14_09_32.562166 path: - '/details_harness\|gsm8k\|5_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-15T14-09-32.562166.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hellaswag\|10_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T18:51:43.691477.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T18_51_43.691477 path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-07-19T18:51:43.691477.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_15T14_09_32.562166 path: - '/details_harness\|winogrande\|5_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-15T14-09-32.562166.parquet' - config_name: results data_files: - split: 2023_07_19T18_51_43.691477 path: - results_2023-07-19T18:51:43.691477.parquet - split: 2023_10_15T14_09_32.562166 path: - results_2023-10-15T14-09-32.562166.parquet - split: latest path: - results_2023-10-15T14-09-32.562166.parquet --- # Dataset Card for Evaluation run of YeungNLP/firefly-llama-13b ## Dataset Description - Homepage: - Repository: https://huggingface.co/YeungNLP/firefly-llama-13b - 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 [YeungNLP/firefly-llama-13b](https://huggingface.co/YeungNLP/firefly-llama-13b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_YeungNLP__firefly-llama-13b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-15T14:09:32.562166](https://huggingface.co/datasets/open-llm-leaderboard/details_YeungNLP__firefly-llama-13b/blob/main/results_2023-10-15T14-09-32.562166.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": 0.12720218120805368, "em_stderr": 0.003412272897129365, "f1": 0.22689702181208146, "f1_stderr": 0.003654793246945971, "acc": 0.418998511823731, "acc_stderr": 0.009810630903312568 }, "harness\|drop\|3": { "em": 0.12720218120805368, "em_stderr": 0.003412272897129365, "f1": 0.22689702181208146, "f1_stderr": 0.003654793246945971 }, "harness\|gsm8k\|5": { "acc": 0.08188021228203184, "acc_stderr": 0.0075523385277169374 }, "harness\|winogrande\|5": { "acc": 0.7561168113654302, "acc_stderr": 0.012068923278908197 } } ``` ### 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]
tejas21private/ai2d_dataset	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 238194265 num_examples: 4900 download_size: 238194265 dataset_size: 238194265 --- # Dataset Card for "ai2d dataset"
candelaz/Kevin	--- license: apache-2.0 ---
harpreetsahota/five_shot_comparison	--- dataset_info: features: - name: source dtype: string - name: target dtype: string - name: rationale dtype: string - name: task dtype: string - name: type dtype: string - name: decilm_generation dtype: string - name: mistral_generation dtype: string - name: falcon_generation dtype: string splits: - name: train num_bytes: 120687 num_examples: 30 download_size: 60550 dataset_size: 120687 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "five_shot_comparison" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
distilabel-internal-testing/Capybara-Preferences-Remaining	--- size_categories: n<1K tags: - synthetic - distilabel - rlaif dataset_info: config_name: keep_columns features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: generations sequence: string - name: generation_models sequence: string - name: ratings sequence: int64 - name: rationales sequence: string - name: ultrafeedback_model dtype: string splits: - name: train num_bytes: 54020454 num_examples: 8375 download_size: 27568892 dataset_size: 54020454 configs: - config_name: keep_columns data_files: - split: train path: keep_columns/train-* --- <p align="left"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> # Dataset Card for Capybara-Preferences-Remaining This dataset has been created with [Distilabel](https://distilabel.argilla.io/). ## Dataset Summary This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI: ```console distilabel pipeline run --config "https://huggingface.co/datasets/distilabel-internal-testing/Capybara-Preferences-Remaining/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/Capybara-Preferences-Remaining/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration: <details><summary> Configuration: keep_columns </summary><hr> ```json { "generation_models": [ "teknium/OpenHermes-2.5-Mistral-7B", "argilla/notus-7b-v1", "mlabonne/NeuralBeagle14-7B", "ask_ldj" ], "generations": [ "Certainly, there are several strategies that can help prevent the creation of a hostile environment during a debate or discussion:\n\n1. Encourage Respectful Communication: Set a tone of respect and promote civil discourse by emphasizing the importance of listening, asking questions, and acknowledging different perspectives.\n\n2. Establish Clear Rules: Clearly outline the ground rules for the discussion or debate, emphasizing that personal attacks or ad hominem remarks will not be tolerated.\n\n3. Promote Active Listening: Encourage participants to actively listen to each other, rather than just waiting for", "Certainly! Here are some strategies that can help prevent the creation of a hostile environment during a debate or discussion:\n\n1. Encourage a Safe and Respectful Space: Create an environment that makes participants feel safe and respected by reminding everyone to avoid ad hominem attacks, to listen to each other, and to respect each other\u0027s viewpoints. Establishing clear ground rules can help everyone focus on the topic at hand and avoid distractions. 2. Encourage Active Listening: Encourage participants to listen actively to each other by letting everyone know that they have been heard,", "Here are some strategies to prevent the creation of a hostile environment during a debate or discussion:\n\n1. Establish ground rules: At the beginning of a debate or discussion, establish clear ground rules or guidelines that promote civility and respect among participants. This may include prohibiting personal attacks, ad hominem arguments, interruptions, or negative body language.\n\n2. Encourage active listening: Encourage all participants to listen actively and attentively to each other\u0027s perspectives. This promotes understanding and can help reduce misunderstandings or emotional escalation.\n\n3. Focus on the issue", "Absolutely, here are some strategies to prevent the creation of a hostile environment during a debate or discussion:\n\n1. Establish Ground Rules: Before starting the discussion, set clear expectations for respectful and constructive dialogue. This might include rules against personal attacks, interruptions, or disrespectful language.\n\n2. Encourage Active Listening: Participants should be encouraged to listen to others\u0027 viewpoints with an open mind, rather than formulating their own responses while others are speaking.\n\n3. Promote Empathy: Encourage participants to try to understand the perspectives and feelings of others, even if they disagree. This can help to foster a sense of mutual respect and understanding.\n\n4. Focus on the Issue, Not the Person: Remind participants to focus on the topic at hand, rather than resorting to personal attacks or criticisms. \n\n5. Use Neutral Language: Avoid inflammatory or loaded language that could escalate tensions. Instead, use neutral, objective language to express your points.\n\n6. Facilitate Fairness: If you\u0027re leading the discussion, ensure that all participants have an equal opportunity to speak and that their viewpoints are given fair consideration.\n\n7. Encourage Questions: Encourage participants to ask clarifying questions if they don\u0027t understand a point, rather than making assumptions or jumping to conclusions.\n\n8. Model Respectful Behavior: If you\u0027re leading the discussion, model the kind of behavior you want to see from participants. This includes listening attentively, responding respectfully, and admitting when you\u0027re wrong.\n\n9. Manage Conflict: If tensions do arise, address them directly and calmly. This might involve taking a short break, reminding participants of the ground rules, or facilitating a resolution between conflicting parties.\n\n10. Provide Positive Feedback: Recognize and reinforce positive behaviors, such as when participants express their points respectfully, listen attentively, or show empathy towards others. This can help to create a more positive and collaborative environment." ], "messages": [ { "content": "Identify the type of logical fallacy in this argument: \u0027You can\u0027t trust Peter because he didn\u0027t go to college.\u0027\n", "role": "user" }, { "content": "The logical fallacy in this argument is ad hominem, because it attacks Peter\u0027s personal characteristics or circumstances (not going to college) rather than addressing the merits of his arguments or ideas.", "role": "assistant" }, { "content": "Given that ad hominem is a type of logical fallacy, how might this bias affect the quality of a debate or discussion?", "role": "user" }, { "content": "Ad hominem fallacies can significantly lower the quality of a debate or discussion. Instead of focusing on the merits of the arguments, ideas, or evidence at hand, participants might get distracted by personal attacks or irrelevant criticisms. This can lead to a hostile environment, where the focus is on winning the argument rather than seeking truth or understanding. Furthermore, it can prevent a fair and balanced evaluation of the actual topic being discussed, as it diverts attention away from the substantive issues.", "role": "assistant" }, { "content": "Discuss the potential consequences of a hostile environment in a debate or discussion.", "role": "user" }, { "content": "A hostile environment in a debate or discussion can have several negative consequences:\n\n1. Deterioration of Communication: When the environment becomes hostile, it can lead to breakdowns in communication. Participants may become defensive or aggressive, which can hinder effective exchange of ideas.\n\n2. Reduced Participation: Some individuals may feel intimidated or uncomfortable in a hostile environment, leading them to withdraw or refrain from contributing their ideas or perspectives.\n\n3. Bias and Prejudice: Hostility can exacerbate biases and prejudices, as participants may resort to stereotypes or discriminatory remarks, further escalating the conflict.\n\n4. Loss of Objectivity: In a hostile environment, participants may lose sight of the objective of the discussion or debate. Instead of seeking to understand different viewpoints or find common ground, they may focus on winning the argument at all costs.\n\n5. Damage to Relationships: If the debate or discussion involves individuals who have ongoing relationships (like colleagues, friends, or family members), a hostile environment can cause long-term damage to these relationships.\n\n6. Misinformation: In a hostile debate, the focus often shifts from facts and logical reasoning to personal attacks. This can lead to the spread of misinformation, as participants may overlook or dismiss valid points or evidence.\n\nOverall, a hostile environment in a debate or discussion can inhibit productive dialogue, discourage participation, and potentially lead to misinformation or misunderstanding.", "role": "assistant" }, { "content": "Could you elaborate on strategies to prevent the creation of a hostile environment during a debate or discussion?", "role": "user" } ], "ratings": [ 4, 4 ], "rationales": [ "The text provides correct and informative strategies to prevent hostility, expressing a clear understanding of the set topics. It does not appear to include any dishonesty, uncertainty, or hallucination; however, the response is cut off, hence not fully complete. This affects the instruction following slightly as the list of strategies is incomplete.", "This text also offers valuable strategies for maintaining a non-hostile environment, aligning well with the user\u0027s request. The strategies are articulated clearly and confidently. However, the output" ], "ultrafeedback_model": "gpt-4-1106-preview" } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("distilabel-internal-testing/Capybara-Preferences-Remaining", "keep_columns") ``` </details>
spdenisov/processed	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 548644785 num_examples: 191025 download_size: 80309791 dataset_size: 548644785 --- # Dataset Card for "processed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
alisson40889/HOLK	--- license: openrail ---
Mitsuki-Sakamoto/alpaca_farm-reward-model-deberta-v3-large-v2-re-preference-64-nsample-2_random	--- dataset_info: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25669546 num_examples: 20001 download_size: 12196543 dataset_size: 25669546 - config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25645562 num_examples: 20001 download_size: 12148697 dataset_size: 25645562 - config_name: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25489159 num_examples: 20001 download_size: 11795765 dataset_size: 25489159 configs: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 data_files: - split: preference path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/preference-* - config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 data_files: - split: preference path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/preference-* - config_name: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1 data_files: - split: preference path: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1/preference-* ---
FarmerlineML/igbo_dataset_2	--- dataset_info: features: - name: transcription dtype: string - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 162930082.12 num_examples: 4892 - name: test num_bytes: 28447287.0 num_examples: 802 download_size: 185263836 dataset_size: 191377369.12 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
nz/ulma_anthropic_hh_golden	--- dataset_info: features: - name: chosen dtype: string - name: rejected dtype: string - name: prompt dtype: string splits: - name: train num_bytes: 37152501 num_examples: 42537 - name: test num_bytes: 2071585 num_examples: 2312 download_size: 22809621 dataset_size: 39224086 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
Damoniano/Agent1	--- license: creativeml-openrail-m ---
davidfant/natural-questions-chunk-11	--- dataset_info: features: - name: id dtype: string - name: document struct: - name: html dtype: string - name: title dtype: string - name: tokens sequence: - name: end_byte dtype: int64 - name: is_html dtype: bool - name: start_byte dtype: int64 - name: token dtype: string - name: url dtype: string - name: question struct: - name: text dtype: string - name: tokens sequence: string - name: long_answer_candidates sequence: - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: top_level dtype: bool - name: annotations sequence: - name: id dtype: string - name: long_answer struct: - name: candidate_index dtype: int64 - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: short_answers sequence: - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: text dtype: string - name: yes_no_answer dtype: class_label: names: '0': 'NO' '1': 'YES' splits: - name: train num_bytes: 4676417206 num_examples: 10000 download_size: 1813929282 dataset_size: 4676417206 --- # Dataset Card for "natural-questions-chunk-11" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
rafasds/Alannovo	--- license: openrail ---
eduardem/parrot_en_es_sample	--- license: openrail --- # Parrot_en_es Fine-Tuning Dataset ## Introduction This dataset serves as a sample for fine-tuning the `parrot_en_es` translation model. The data is structured in the OpenOrca format and is designed to train the model to perform specific tasks related to translation. ## Objective The primary aim of this dataset is to achieve alignment in the model so that it acts strictly as a translator. The model should output solely the translation, avoiding any additional comments, considerations, extra content, fixes, or refusals. ## Format ### OpenOrca The dataset employs the OpenOrca format and maintains a consistent system prompt across all samples. This uniformity in system prompts is intended to guide the model towards the desired behavior, which is to produce only the translation. ## Usage This dataset can be used to: - Fine-tune the `parrot_en_es` translation model - Validate the model's ability to output clean translations without any superfluous content - Assess the effectiveness of using a consistent system prompt to guide model behavior ## Contributing For suggestions to improve or expand the dataset, feel free to open an issue or submit a pull request.
irds/mr-tydi_ja	--- pretty_name: '`mr-tydi/ja`' viewer: false source_datasets: [] task_categories: - text-retrieval --- # Dataset Card for `mr-tydi/ja` The `mr-tydi/ja` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/mr-tydi#mr-tydi/ja). # Data This dataset provides: - `docs` (documents, i.e., the corpus); count=7,000,027 - `queries` (i.e., topics); count=5,353 - `qrels`: (relevance assessments); count=5,548 This dataset is used by: [`mr-tydi_ja_dev`](https://huggingface.co/datasets/irds/mr-tydi_ja_dev), [`mr-tydi_ja_test`](https://huggingface.co/datasets/irds/mr-tydi_ja_test), [`mr-tydi_ja_train`](https://huggingface.co/datasets/irds/mr-tydi_ja_train) ## Usage ```python from datasets import load_dataset docs = load_dataset('irds/mr-tydi_ja', 'docs') for record in docs: record # {'doc_id': ..., 'text': ...} queries = load_dataset('irds/mr-tydi_ja', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/mr-tydi_ja', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @article{Zhang2021MrTyDi, title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin}, year={2021}, journal={arXiv:2108.08787}, } @article{Clark2020TyDiQa, title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}, year={2020}, journal={Transactions of the Association for Computational Linguistics} } ```
hungsmoie/khoaiphim	--- license: unlicense ---
Farisya/usermanual-dataset	--- dataset_info: features: - name: example dtype: string splits: - name: train num_bytes: 18543 num_examples: 22 - name: test num_bytes: 8671 num_examples: 9 download_size: 20134 dataset_size: 27214 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k	--- pretty_name: Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2927085297989137,\n\ \ \"acc_stderr\": 0.03275517148401362,\n \"acc_norm\": 0.29622047886660385,\n\ \ \"acc_norm_stderr\": 0.032746678820457335,\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.46928327645051193,\n \"acc_stderr\": 0.014583792546304038,\n\ \ \"acc_norm\": 0.4974402730375427,\n \"acc_norm_stderr\": 0.014611199329843777\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5497908783110934,\n\ \ \"acc_stderr\": 0.004964979120927565,\n \"acc_norm\": 0.7288388767177854,\n\ \ \"acc_norm_stderr\": 0.004436505187567003\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2222222222222222,\n\ \ \"acc_stderr\": 0.035914440841969694,\n \"acc_norm\": 0.2222222222222222,\n\ \ \"acc_norm_stderr\": 0.035914440841969694\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.2894736842105263,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.2894736842105263,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.25660377358490566,\n \"acc_stderr\": 0.02688064788905197,\n\ \ \"acc_norm\": 0.25660377358490566,\n \"acc_norm_stderr\": 0.02688064788905197\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.24305555555555555,\n\ \ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.24305555555555555,\n\ \ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165085,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165085\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.20809248554913296,\n\ \ \"acc_stderr\": 0.030952890217749895,\n \"acc_norm\": 0.20809248554913296,\n\ \ \"acc_norm_stderr\": 0.030952890217749895\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.37,\n\ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.029513196625539355,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.029513196625539355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.03999423879281336,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.03999423879281336\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2689655172413793,\n \"acc_stderr\": 0.03695183311650232,\n\ \ \"acc_norm\": 0.2689655172413793,\n \"acc_norm_stderr\": 0.03695183311650232\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948365,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948365\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.20634920634920634,\n\ \ \"acc_stderr\": 0.0361960452412425,\n \"acc_norm\": 0.20634920634920634,\n\ \ \"acc_norm_stderr\": 0.0361960452412425\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.04093601807403326,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.04093601807403326\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.24838709677419354,\n\ \ \"acc_stderr\": 0.02458002892148101,\n \"acc_norm\": 0.24838709677419354,\n\ \ \"acc_norm_stderr\": 0.02458002892148101\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.1921182266009852,\n \"acc_stderr\": 0.02771931570961478,\n\ \ \"acc_norm\": 0.1921182266009852,\n \"acc_norm_stderr\": 0.02771931570961478\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206824,\n \"acc_norm\"\ : 0.29,\n \"acc_norm_stderr\": 0.045604802157206824\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.36363636363636365,\n \"acc_stderr\": 0.03756335775187896,\n\ \ \"acc_norm\": 0.36363636363636365,\n \"acc_norm_stderr\": 0.03756335775187896\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.2676767676767677,\n \"acc_stderr\": 0.03154449888270285,\n \"\ acc_norm\": 0.2676767676767677,\n \"acc_norm_stderr\": 0.03154449888270285\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.2538860103626943,\n \"acc_stderr\": 0.03141024780565319,\n\ \ \"acc_norm\": 0.2538860103626943,\n \"acc_norm_stderr\": 0.03141024780565319\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.24358974358974358,\n \"acc_stderr\": 0.02176373368417392,\n\ \ \"acc_norm\": 0.24358974358974358,\n \"acc_norm_stderr\": 0.02176373368417392\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.23333333333333334,\n \"acc_stderr\": 0.02578787422095932,\n \ \ \"acc_norm\": 0.23333333333333334,\n \"acc_norm_stderr\": 0.02578787422095932\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.23109243697478993,\n \"acc_stderr\": 0.027381406927868956,\n\ \ \"acc_norm\": 0.23109243697478993,\n \"acc_norm_stderr\": 0.027381406927868956\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.3155963302752294,\n \"acc_stderr\": 0.019926117513869662,\n \"\ acc_norm\": 0.3155963302752294,\n \"acc_norm_stderr\": 0.019926117513869662\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.2962962962962963,\n \"acc_stderr\": 0.031141447823536023,\n \"\ acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.031141447823536023\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.3333333333333333,\n \"acc_stderr\": 0.03308611113236435,\n \"\ acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.03308611113236435\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.3881856540084388,\n \"acc_stderr\": 0.0317229500433233,\n \ \ \"acc_norm\": 0.3881856540084388,\n \"acc_norm_stderr\": 0.0317229500433233\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.273542600896861,\n\ \ \"acc_stderr\": 0.029918586707798824,\n \"acc_norm\": 0.273542600896861,\n\ \ \"acc_norm_stderr\": 0.029918586707798824\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2748091603053435,\n \"acc_stderr\": 0.039153454088478354,\n\ \ \"acc_norm\": 0.2748091603053435,\n \"acc_norm_stderr\": 0.039153454088478354\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.4132231404958678,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.4132231404958678,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04557239513497751,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04557239513497751\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.2147239263803681,\n \"acc_stderr\": 0.03226219377286774,\n\ \ \"acc_norm\": 0.2147239263803681,\n \"acc_norm_stderr\": 0.03226219377286774\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.29464285714285715,\n\ \ \"acc_stderr\": 0.04327040932578729,\n \"acc_norm\": 0.29464285714285715,\n\ \ \"acc_norm_stderr\": 0.04327040932578729\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690878,\n\ \ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690878\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.3504273504273504,\n\ \ \"acc_stderr\": 0.03125610824421881,\n \"acc_norm\": 0.3504273504273504,\n\ \ \"acc_norm_stderr\": 0.03125610824421881\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.2988505747126437,\n\ \ \"acc_stderr\": 0.01636925681509314,\n \"acc_norm\": 0.2988505747126437,\n\ \ \"acc_norm_stderr\": 0.01636925681509314\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.30057803468208094,\n \"acc_stderr\": 0.024685316867257796,\n\ \ \"acc_norm\": 0.30057803468208094,\n \"acc_norm_stderr\": 0.024685316867257796\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.3300653594771242,\n \"acc_stderr\": 0.026925654653615686,\n\ \ \"acc_norm\": 0.3300653594771242,\n \"acc_norm_stderr\": 0.026925654653615686\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2733118971061093,\n\ \ \"acc_stderr\": 0.02531176597542612,\n \"acc_norm\": 0.2733118971061093,\n\ \ \"acc_norm_stderr\": 0.02531176597542612\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.3055555555555556,\n \"acc_stderr\": 0.025630824975621344,\n\ \ \"acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.025630824975621344\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.28368794326241137,\n \"acc_stderr\": 0.02689170942834396,\n \ \ \"acc_norm\": 0.28368794326241137,\n \"acc_norm_stderr\": 0.02689170942834396\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.28748370273794005,\n\ \ \"acc_stderr\": 0.011559337355708502,\n \"acc_norm\": 0.28748370273794005,\n\ \ \"acc_norm_stderr\": 0.011559337355708502\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.28104575163398693,\n \"acc_stderr\": 0.018185218954318075,\n \ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.018185218954318075\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.4163265306122449,\n \"acc_stderr\": 0.03155782816556165,\n\ \ \"acc_norm\": 0.4163265306122449,\n \"acc_norm_stderr\": 0.03155782816556165\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.34328358208955223,\n\ \ \"acc_stderr\": 0.03357379665433431,\n \"acc_norm\": 0.34328358208955223,\n\ \ \"acc_norm_stderr\": 0.03357379665433431\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.2710843373493976,\n\ \ \"acc_stderr\": 0.034605799075530276,\n \"acc_norm\": 0.2710843373493976,\n\ \ \"acc_norm_stderr\": 0.034605799075530276\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.39766081871345027,\n \"acc_stderr\": 0.0375363895576169,\n\ \ \"acc_norm\": 0.39766081871345027,\n \"acc_norm_stderr\": 0.0375363895576169\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n }\n}\n```" repo_url: https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|arc:challenge\|25_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hellaswag\|10_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_13T10_12_42.075501 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-13T10-12-42.075501.parquet' - config_name: results data_files: - split: 2023_09_13T10_12_42.075501 path: - results_2023-09-13T10-12-42.075501.parquet - split: latest path: - results_2023-09-13T10-12-42.075501.parquet --- # Dataset Card for Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k ## Dataset Description - Homepage: - Repository: https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2927085297989137, "acc_stderr": 0.03275517148401362, "acc_norm": 0.29622047886660385, "acc_norm_stderr": 0.032746678820457335, "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 }, "harness\|arc:challenge\|25": { "acc": 0.46928327645051193, "acc_stderr": 0.014583792546304038, "acc_norm": 0.4974402730375427, "acc_norm_stderr": 0.014611199329843777 }, "harness\|hellaswag\|10": { "acc": 0.5497908783110934, "acc_stderr": 0.004964979120927565, "acc_norm": 0.7288388767177854, "acc_norm_stderr": 0.004436505187567003 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.035914440841969694, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.035914440841969694 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.2894736842105263, "acc_stderr": 0.03690677986137283, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.25660377358490566, "acc_stderr": 0.02688064788905197, "acc_norm": 0.25660377358490566, "acc_norm_stderr": 0.02688064788905197 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.24305555555555555, "acc_stderr": 0.0358687928008034, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.0358687928008034 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.23, "acc_stderr": 0.042295258468165085, "acc_norm": 0.23, "acc_norm_stderr": 0.042295258468165085 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749895, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749895 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.2851063829787234, "acc_stderr": 0.029513196625539355, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.029513196625539355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.03999423879281336, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.03999423879281336 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2689655172413793, "acc_stderr": 0.03695183311650232, "acc_norm": 0.2689655172413793, "acc_norm_stderr": 0.03695183311650232 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.20634920634920634, "acc_stderr": 0.0361960452412425, "acc_norm": 0.20634920634920634, "acc_norm_stderr": 0.0361960452412425 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.24838709677419354, "acc_stderr": 0.02458002892148101, "acc_norm": 0.24838709677419354, "acc_norm_stderr": 0.02458002892148101 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.1921182266009852, "acc_stderr": 0.02771931570961478, "acc_norm": 0.1921182266009852, "acc_norm_stderr": 0.02771931570961478 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206824, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206824 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.36363636363636365, "acc_stderr": 0.03756335775187896, "acc_norm": 0.36363636363636365, "acc_norm_stderr": 0.03756335775187896 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.2676767676767677, "acc_stderr": 0.03154449888270285, "acc_norm": 0.2676767676767677, "acc_norm_stderr": 0.03154449888270285 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.2538860103626943, "acc_stderr": 0.03141024780565319, "acc_norm": 0.2538860103626943, "acc_norm_stderr": 0.03141024780565319 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.24358974358974358, "acc_stderr": 0.02176373368417392, "acc_norm": 0.24358974358974358, "acc_norm_stderr": 0.02176373368417392 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.23333333333333334, "acc_stderr": 0.02578787422095932, "acc_norm": 0.23333333333333334, "acc_norm_stderr": 0.02578787422095932 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.23109243697478993, "acc_stderr": 0.027381406927868956, "acc_norm": 0.23109243697478993, "acc_norm_stderr": 0.027381406927868956 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.3155963302752294, "acc_stderr": 0.019926117513869662, "acc_norm": 0.3155963302752294, "acc_norm_stderr": 0.019926117513869662 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.2962962962962963, "acc_stderr": 0.031141447823536023, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.031141447823536023 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.03308611113236435, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.03308611113236435 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.3881856540084388, "acc_stderr": 0.0317229500433233, "acc_norm": 0.3881856540084388, "acc_norm_stderr": 0.0317229500433233 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.273542600896861, "acc_stderr": 0.029918586707798824, "acc_norm": 0.273542600896861, "acc_norm_stderr": 0.029918586707798824 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2748091603053435, "acc_stderr": 0.039153454088478354, "acc_norm": 0.2748091603053435, "acc_norm_stderr": 0.039153454088478354 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.4132231404958678, "acc_stderr": 0.04495087843548408, "acc_norm": 0.4132231404958678, "acc_norm_stderr": 0.04495087843548408 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04557239513497751, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04557239513497751 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.2147239263803681, "acc_stderr": 0.03226219377286774, "acc_norm": 0.2147239263803681, "acc_norm_stderr": 0.03226219377286774 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.29464285714285715, "acc_stderr": 0.04327040932578729, "acc_norm": 0.29464285714285715, "acc_norm_stderr": 0.04327040932578729 }, "harness\|hendrycksTest-management\|5": { "acc": 0.2524271844660194, "acc_stderr": 0.04301250399690878, "acc_norm": 0.2524271844660194, "acc_norm_stderr": 0.04301250399690878 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.3504273504273504, "acc_stderr": 0.03125610824421881, "acc_norm": 0.3504273504273504, "acc_norm_stderr": 0.03125610824421881 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.2988505747126437, "acc_stderr": 0.01636925681509314, "acc_norm": 0.2988505747126437, "acc_norm_stderr": 0.01636925681509314 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.30057803468208094, "acc_stderr": 0.024685316867257796, "acc_norm": 0.30057803468208094, "acc_norm_stderr": 0.024685316867257796 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.3300653594771242, "acc_stderr": 0.026925654653615686, "acc_norm": 0.3300653594771242, "acc_norm_stderr": 0.026925654653615686 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.2733118971061093, "acc_stderr": 0.02531176597542612, "acc_norm": 0.2733118971061093, "acc_norm_stderr": 0.02531176597542612 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.3055555555555556, "acc_stderr": 0.025630824975621344, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.025630824975621344 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.28368794326241137, "acc_stderr": 0.02689170942834396, "acc_norm": 0.28368794326241137, "acc_norm_stderr": 0.02689170942834396 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.28748370273794005, "acc_stderr": 0.011559337355708502, "acc_norm": 0.28748370273794005, "acc_norm_stderr": 0.011559337355708502 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.28104575163398693, "acc_stderr": 0.018185218954318075, "acc_norm": 0.28104575163398693, "acc_norm_stderr": 0.018185218954318075 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.3, "acc_stderr": 0.04389311454644286, "acc_norm": 0.3, "acc_norm_stderr": 0.04389311454644286 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.4163265306122449, "acc_stderr": 0.03155782816556165, "acc_norm": 0.4163265306122449, "acc_norm_stderr": 0.03155782816556165 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.34328358208955223, "acc_stderr": 0.03357379665433431, "acc_norm": 0.34328358208955223, "acc_norm_stderr": 0.03357379665433431 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.2710843373493976, "acc_stderr": 0.034605799075530276, "acc_norm": 0.2710843373493976, "acc_norm_stderr": 0.034605799075530276 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.39766081871345027, "acc_stderr": 0.0375363895576169, "acc_norm": 0.39766081871345027, "acc_norm_stderr": 0.0375363895576169 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B	--- pretty_name: Evaluation run of klyang/MentaLLaMA-chat-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [klyang/MentaLLaMA-chat-7B](https://huggingface.co/klyang/MentaLLaMA-chat-7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 1 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_klyang__MentaLLaMA-chat-7B\"\ ,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\ \ are the [latest results from run 2023-12-02T22:04:51.845916](https://huggingface.co/datasets/open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B/blob/main/results_2023-12-02T22-04-51.845916.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\": 0.16148597422289612,\n\ \ \"acc_stderr\": 0.010135959452134306\n },\n \"harness\|gsm8k\|5\":\ \ {\n \"acc\": 0.16148597422289612,\n \"acc_stderr\": 0.010135959452134306\n\ \ }\n}\n```" repo_url: https://huggingface.co/klyang/MentaLLaMA-chat-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_gsm8k_5 data_files: - split: 2023_12_02T22_04_51.845916 path: - '/details_harness\|gsm8k\|5_2023-12-02T22-04-51.845916.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-02T22-04-51.845916.parquet' - config_name: results data_files: - split: 2023_12_02T22_04_51.845916 path: - results_2023-12-02T22-04-51.845916.parquet - split: latest path: - results_2023-12-02T22-04-51.845916.parquet --- # Dataset Card for Evaluation run of klyang/MentaLLaMA-chat-7B ## Dataset Description - Homepage: - Repository: https://huggingface.co/klyang/MentaLLaMA-chat-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 [klyang/MentaLLaMA-chat-7B](https://huggingface.co/klyang/MentaLLaMA-chat-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 1 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_klyang__MentaLLaMA-chat-7B", "harness_gsm8k_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-02T22:04:51.845916](https://huggingface.co/datasets/open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B/blob/main/results_2023-12-02T22-04-51.845916.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": 0.16148597422289612, "acc_stderr": 0.010135959452134306 }, "harness\|gsm8k\|5": { "acc": 0.16148597422289612, "acc_stderr": 0.010135959452134306 } } ``` ### 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]
edouard-rolland/volcanic-plumes	--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Volcanoes - Plumes - UAVs - Drone dataset_info: features: - name: image_id dtype: int64 - name: image dtype: image - name: width dtype: int32 - name: height dtype: int32 - name: objects sequence: - name: id dtype: int64 - name: area dtype: int64 - name: bbox sequence: float32 length: 4 - name: category dtype: class_label: names: '0': plume '1': summit splits: - name: train num_bytes: 29846342.127 num_examples: 1211 - name: validation num_bytes: 7311174 num_examples: 294 - name: test num_bytes: 12048406 num_examples: 456 download_size: 49324639 dataset_size: 49205922.127000004 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* license: mit language: - en --- <div align="center"> <img width=100% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/thumbnail.png"> </div> # Dataset Description The dataset presents labelled pictures of plumes and of the Fuego Summit in Guatemala. The data was collected by the University of Bristol Flight Lab in Guatemala from March 22 to April 3, 2019. The drone used for this purpose was a Skywalker X8, equipped with a Pixhawk onboard computer running ArduPlane 3.7.1 and a Raspberry Pi 3B+ for mission management and communication with the ground station. The drone was also equipped of a GoPro Hero 9. # Citation ``` @inproceedings{rolland2024volcanic, author = {Edouard G. A. Rolland and Kasper A. R. Grøntved and Anders Lyhne Christensen and Matthew Watson and Tom Richardson}, title = { Autonomous {UAV} Volcanic Plume Sampling Based on Machine Vision and Path Planning}, year = { 2024 }, note = {Under review}, } ``` # Acknowledgement This work is supported by the WildDrone MSCA Doctoral Network funded by EU Horizon Europe under grant agreement no. 101071224, the Innovation Fund Denmark for the project DIREC (9142-00001B), and by the Engineering & Physical Sciences Research Council (UK) through the CASCADE (Complex Autonomous aircraft Systems Configuration, Analysis and Design Exploratory) programme grant (EP/R009953/1). # Dataset Labels ``` ['plume', 'summit'] ``` # Example of Labelled Images <div align="center"> <<img width=50% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/val_batch0_labels.jpg"> </div> # Number of Images ```json {'valid': 294, 'test': 456, 'train': 1211} ``` # Example of Application The dataset was used to train a YOLOv8 neural network. More details can be found in the paper mentioned in the citation section. The following <a href="https://www.youtube.com/watch?v=pSGYUPancfA">video</a> presents the model output for an entire flight. # How to Use - Install [datasets](https://pypi.org/project/datasets/): ```bash pip install datasets ``` - Load the dataset: ```python from datasets import load_dataset ds = load_dataset("edouard-rolland/volcanic-plumes", name="full") example = ds['train'][0] ``` # License MIT
Cohere/miracl-sw-queries-22-12	--- annotations_creators: - expert-generated language: - sw multilinguality: - multilingual size_categories: [] source_datasets: [] tags: [] task_categories: - text-retrieval license: - apache-2.0 task_ids: - document-retrieval --- # MIRACL (sw) embedded with cohere.ai `multilingual-22-12` encoder We encoded the [MIRACL dataset](https://huggingface.co/miracl) using the [cohere.ai](https://txt.cohere.ai/multilingual/) `multilingual-22-12` embedding model. The query embeddings can be found in [Cohere/miracl-sw-queries-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-queries-22-12) and the corpus embeddings can be found in [Cohere/miracl-sw-corpus-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-corpus-22-12). For the orginal datasets, see [miracl/miracl](https://huggingface.co/datasets/miracl/miracl) and [miracl/miracl-corpus](https://huggingface.co/datasets/miracl/miracl-corpus). Dataset info: > MIRACL 🌍🙌🌏 (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual retrieval dataset that focuses on search across 18 different languages, which collectively encompass over three billion native speakers around the world. > > The corpus for each language is prepared from a Wikipedia dump, where we keep only the plain text and discard images, tables, etc. Each article is segmented into multiple passages using WikiExtractor based on natural discourse units (e.g., `\n\n` in the wiki markup). Each of these passages comprises a "document" or unit of retrieval. We preserve the Wikipedia article title of each passage. ## Embeddings We compute for `title+" "+text` the embeddings using our `multilingual-22-12` embedding model, a state-of-the-art model that works for semantic search in 100 languages. If you want to learn more about this model, have a look at [cohere.ai multilingual embedding model](https://txt.cohere.ai/multilingual/). ## Loading the dataset In [miracl-sw-corpus-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-corpus-22-12) we provide the corpus embeddings. Note, depending on the selected split, the respective files can be quite large. You can either load the dataset like this: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train") ``` Or you can also stream it without downloading it before: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train", streaming=True) for doc in docs: docid = doc['docid'] title = doc['title'] text = doc['text'] emb = doc['emb'] ``` ## Search Have a look at [miracl-sw-queries-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-queries-22-12) where we provide the query embeddings for the MIRACL dataset. To search in the documents, you must use dot-product. And then compare this query embeddings either with a vector database (recommended) or directly computing the dot product. A full search example: ```python # Attention! For large datasets, this requires a lot of memory to store # all document embeddings and to compute the dot product scores. # Only use this for smaller datasets. For large datasets, use a vector DB from datasets import load_dataset import torch #Load documents + embeddings docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train") doc_embeddings = torch.tensor(docs['emb']) # Load queries queries = load_dataset(f"Cohere/miracl-sw-queries-22-12", split="dev") # Select the first query as example qid = 0 query = queries[qid] query_embedding = torch.tensor(queries['emb']) # Compute dot score between query embedding and document embeddings dot_scores = torch.mm(query_embedding, doc_embeddings.transpose(0, 1)) top_k = torch.topk(dot_scores, k=3) # Print results print("Query:", query['query']) for doc_id in top_k.indices[0].tolist(): print(docs[doc_id]['title']) print(docs[doc_id]['text']) ``` You can get embeddings for new queries using our API: ```python #Run: pip install cohere import cohere co = cohere.Client(f"{api_key}") # You should add your cohere API Key here :)) texts = ['my search query'] response = co.embed(texts=texts, model='multilingual-22-12') query_embedding = response.embeddings[0] # Get the embedding for the first text ``` ## Performance In the following table we compare the cohere multilingual-22-12 model with Elasticsearch version 8.6.0 lexical search (title and passage indexed as independent fields). Note that Elasticsearch doesn't support all languages that are part of the MIRACL dataset. We compute nDCG@10 (a ranking based loss), as well as hit@3: Is at least one relevant document in the top-3 results. We find that hit@3 is easier to interpret, as it presents the number of queries for which a relevant document is found among the top-3 results. Note: MIRACL only annotated a small fraction of passages (10 per query) for relevancy. Especially for larger Wikipedias (like English), we often found many more relevant passages. This is know as annotation holes. Real nDCG@10 and hit@3 performance is likely higher than depicted. \| Model \| cohere multilingual-22-12 nDCG@10 \| cohere multilingual-22-12 hit@3 \| ES 8.6.0 nDCG@10 \| ES 8.6.0 acc@3 \| \|---\|---\|---\|---\|---\| \| miracl-ar \| 64.2 \| 75.2 \| 46.8 \| 56.2 \| \| miracl-bn \| 61.5 \| 75.7 \| 49.2 \| 60.1 \| \| miracl-de \| 44.4 \| 60.7 \| 19.6 \| 29.8 \| \| miracl-en \| 44.6 \| 62.2 \| 30.2 \| 43.2 \| \| miracl-es \| 47.0 \| 74.1 \| 27.0 \| 47.2 \| \| miracl-fi \| 63.7 \| 76.2 \| 51.4 \| 61.6 \| \| miracl-fr \| 46.8 \| 57.1 \| 17.0 \| 21.6 \| \| miracl-hi \| 50.7 \| 62.9 \| 41.0 \| 48.9 \| \| miracl-id \| 44.8 \| 63.8 \| 39.2 \| 54.7 \| \| miracl-ru \| 49.2 \| 66.9 \| 25.4 \| 36.7 \| \| Avg \| 51.7 \| 67.5 \| 34.7 \| 46.0 \| Further languages (not supported by Elasticsearch): \| Model \| cohere multilingual-22-12 nDCG@10 \| cohere multilingual-22-12 hit@3 \| \|---\|---\|---\| \| miracl-fa \| 44.8 \| 53.6 \| \| miracl-ja \| 49.0 \| 61.0 \| \| miracl-ko \| 50.9 \| 64.8 \| \| miracl-sw \| 61.4 \| 74.5 \| \| miracl-te \| 67.8 \| 72.3 \| \| miracl-th \| 60.2 \| 71.9 \| \| miracl-yo \| 56.4 \| 62.2 \| \| miracl-zh \| 43.8 \| 56.5 \| \| Avg \| 54.3 \| 64.6 \|
open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0	--- pretty_name: Evaluation run of azarafrooz/gemma-2b-it-nlai-v0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [azarafrooz/gemma-2b-it-nlai-v0](https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0)\ \ 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_azarafrooz__gemma-2b-it-nlai-v0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-15T12:20:29.148062](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0/blob/main/results_2024-04-15T12-20-29.148062.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\": 0.37660169444969677,\n\ \ \"acc_stderr\": 0.03380673348549725,\n \"acc_norm\": 0.3811167415748182,\n\ \ \"acc_norm_stderr\": 0.03461538621374684,\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.015866346401384308,\n \"mc2\": 0.45797553398869045,\n\ \ \"mc2_stderr\": 0.015928281785783458\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.4052901023890785,\n \"acc_stderr\": 0.014346869060229327,\n\ \ \"acc_norm\": 0.4402730375426621,\n \"acc_norm_stderr\": 0.014506769524804246\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.48137821151165106,\n\ \ \"acc_stderr\": 0.004986319587524964,\n \"acc_norm\": 0.6266679944234216,\n\ \ \"acc_norm_stderr\": 0.004827006520802888\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.3851851851851852,\n\ \ \"acc_stderr\": 0.042039210401562783,\n \"acc_norm\": 0.3851851851851852,\n\ \ \"acc_norm_stderr\": 0.042039210401562783\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.3355263157894737,\n \"acc_stderr\": 0.03842498559395269,\n\ \ \"acc_norm\": 0.3355263157894737,\n \"acc_norm_stderr\": 0.03842498559395269\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.49,\n\ \ \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\": 0.49,\n \ \ \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.4226415094339623,\n \"acc_stderr\": 0.030402331445769537,\n\ \ \"acc_norm\": 0.4226415094339623,\n \"acc_norm_stderr\": 0.030402331445769537\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.3472222222222222,\n\ \ \"acc_stderr\": 0.039812405437178615,\n \"acc_norm\": 0.3472222222222222,\n\ \ \"acc_norm_stderr\": 0.039812405437178615\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.3,\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\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3583815028901734,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.3583815028901734,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617747,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617747\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.45,\n \"\ acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.3574468085106383,\n \"acc_stderr\": 0.03132941789476425,\n\ \ \"acc_norm\": 0.3574468085106383,\n \"acc_norm_stderr\": 0.03132941789476425\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2807017543859649,\n\ \ \"acc_stderr\": 0.042270544512322,\n \"acc_norm\": 0.2807017543859649,\n\ \ \"acc_norm_stderr\": 0.042270544512322\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4689655172413793,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.4689655172413793,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643895,\n \"\ acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643895\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.25396825396825395,\n\ \ \"acc_stderr\": 0.03893259610604674,\n \"acc_norm\": 0.25396825396825395,\n\ \ \"acc_norm_stderr\": 0.03893259610604674\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.3193548387096774,\n\ \ \"acc_stderr\": 0.026522709674667765,\n \"acc_norm\": 0.3193548387096774,\n\ \ \"acc_norm_stderr\": 0.026522709674667765\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.29064039408866993,\n \"acc_stderr\": 0.0319474007226554,\n\ \ \"acc_norm\": 0.29064039408866993,\n \"acc_norm_stderr\": 0.0319474007226554\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\"\ : 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.45454545454545453,\n \"acc_stderr\": 0.03888176921674098,\n\ \ \"acc_norm\": 0.45454545454545453,\n \"acc_norm_stderr\": 0.03888176921674098\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.4595959595959596,\n \"acc_stderr\": 0.035507024651313425,\n \"\ acc_norm\": 0.4595959595959596,\n \"acc_norm_stderr\": 0.035507024651313425\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.47150259067357514,\n \"acc_stderr\": 0.03602573571288442,\n\ \ \"acc_norm\": 0.47150259067357514,\n \"acc_norm_stderr\": 0.03602573571288442\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.33076923076923076,\n \"acc_stderr\": 0.023854795680971135,\n\ \ \"acc_norm\": 0.33076923076923076,\n \"acc_norm_stderr\": 0.023854795680971135\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2,\n \"acc_stderr\": 0.024388430433987664,\n \"acc_norm\"\ : 0.2,\n \"acc_norm_stderr\": 0.024388430433987664\n },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\"\ : {\n \"acc\": 0.3403361344537815,\n \"acc_stderr\": 0.030778057422931673,\n\ \ \"acc_norm\": 0.3403361344537815,\n \"acc_norm_stderr\": 0.030778057422931673\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5027522935779817,\n \"acc_stderr\": 0.021436998359765317,\n \"\ acc_norm\": 0.5027522935779817,\n \"acc_norm_stderr\": 0.021436998359765317\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.19907407407407407,\n \"acc_stderr\": 0.027232298462690218,\n \"\ acc_norm\": 0.19907407407407407,\n \"acc_norm_stderr\": 0.027232298462690218\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.4166666666666667,\n \"acc_stderr\": 0.03460228327239171,\n \"\ acc_norm\": 0.4166666666666667,\n \"acc_norm_stderr\": 0.03460228327239171\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.5189873417721519,\n \"acc_stderr\": 0.03252375148090448,\n \ \ \"acc_norm\": 0.5189873417721519,\n \"acc_norm_stderr\": 0.03252375148090448\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.38565022421524664,\n\ \ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.38565022421524664,\n\ \ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.4198473282442748,\n \"acc_stderr\": 0.043285772152629715,\n\ \ \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.043285772152629715\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.5206611570247934,\n \"acc_stderr\": 0.04560456086387235,\n \"\ acc_norm\": 0.5206611570247934,\n \"acc_norm_stderr\": 0.04560456086387235\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.4722222222222222,\n\ \ \"acc_stderr\": 0.04826217294139894,\n \"acc_norm\": 0.4722222222222222,\n\ \ \"acc_norm_stderr\": 0.04826217294139894\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.36809815950920244,\n \"acc_stderr\": 0.03789213935838396,\n\ \ \"acc_norm\": 0.36809815950920244,\n \"acc_norm_stderr\": 0.03789213935838396\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.33035714285714285,\n\ \ \"acc_stderr\": 0.044642857142857116,\n \"acc_norm\": 0.33035714285714285,\n\ \ \"acc_norm_stderr\": 0.044642857142857116\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.44660194174757284,\n \"acc_stderr\": 0.04922424153458933,\n\ \ \"acc_norm\": 0.44660194174757284,\n \"acc_norm_stderr\": 0.04922424153458933\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.594017094017094,\n\ \ \"acc_stderr\": 0.03217180182641086,\n \"acc_norm\": 0.594017094017094,\n\ \ \"acc_norm_stderr\": 0.03217180182641086\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.4648786717752235,\n\ \ \"acc_stderr\": 0.017835798806290642,\n \"acc_norm\": 0.4648786717752235,\n\ \ \"acc_norm_stderr\": 0.017835798806290642\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\": 0.24581005586592178,\n\ \ \"acc_stderr\": 0.014400296429225624,\n \"acc_norm\": 0.24581005586592178,\n\ \ \"acc_norm_stderr\": 0.014400296429225624\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.4444444444444444,\n \"acc_stderr\": 0.028452639985088003,\n\ \ \"acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.028452639985088003\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.40514469453376206,\n\ \ \"acc_stderr\": 0.02788238379132596,\n \"acc_norm\": 0.40514469453376206,\n\ \ \"acc_norm_stderr\": 0.02788238379132596\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.41358024691358025,\n \"acc_stderr\": 0.027402042040269952,\n\ \ \"acc_norm\": 0.41358024691358025,\n \"acc_norm_stderr\": 0.027402042040269952\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.3049645390070922,\n \"acc_stderr\": 0.027464708442022135,\n \ \ \"acc_norm\": 0.3049645390070922,\n \"acc_norm_stderr\": 0.027464708442022135\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.31747066492829207,\n\ \ \"acc_stderr\": 0.011888892068809312,\n \"acc_norm\": 0.31747066492829207,\n\ \ \"acc_norm_stderr\": 0.011888892068809312\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.20220588235294118,\n \"acc_stderr\": 0.024398192986654924,\n\ \ \"acc_norm\": 0.20220588235294118,\n \"acc_norm_stderr\": 0.024398192986654924\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.37745098039215685,\n \"acc_stderr\": 0.019610851474880286,\n \ \ \"acc_norm\": 0.37745098039215685,\n \"acc_norm_stderr\": 0.019610851474880286\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.41818181818181815,\n\ \ \"acc_stderr\": 0.0472457740573157,\n \"acc_norm\": 0.41818181818181815,\n\ \ \"acc_norm_stderr\": 0.0472457740573157\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.46938775510204084,\n \"acc_stderr\": 0.031949171367580624,\n\ \ \"acc_norm\": 0.46938775510204084,\n \"acc_norm_stderr\": 0.031949171367580624\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.4427860696517413,\n\ \ \"acc_stderr\": 0.03512310964123936,\n \"acc_norm\": 0.4427860696517413,\n\ \ \"acc_norm_stderr\": 0.03512310964123936\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.41566265060240964,\n\ \ \"acc_stderr\": 0.038367221765980515,\n \"acc_norm\": 0.41566265060240964,\n\ \ \"acc_norm_stderr\": 0.038367221765980515\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.4327485380116959,\n \"acc_stderr\": 0.03799978644370607,\n\ \ \"acc_norm\": 0.4327485380116959,\n \"acc_norm_stderr\": 0.03799978644370607\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.015866346401384308,\n \"mc2\": 0.45797553398869045,\n\ \ \"mc2_stderr\": 0.015928281785783458\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6132596685082873,\n \"acc_stderr\": 0.013687214761883042\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.053828658074298714,\n \ \ \"acc_stderr\": 0.006216328640238136\n }\n}\n```" repo_url: https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0 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_04_15T12_20_29.148062 path: - '/details_harness\|arc:challenge\|25_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-04-15T12-20-29.148062.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|gsm8k\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hellaswag\|10_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-15T12-20-29.148062.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-management\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|truthfulqa:mc\|0_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-04-15T12-20-29.148062.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '/details_harness\|winogrande\|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-04-15T12-20-29.148062.parquet' - config_name: results data_files: - split: 2024_04_15T12_20_29.148062 path: - results_2024-04-15T12-20-29.148062.parquet - split: latest path: - results_2024-04-15T12-20-29.148062.parquet --- # Dataset Card for Evaluation run of azarafrooz/gemma-2b-it-nlai-v0 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [azarafrooz/gemma-2b-it-nlai-v0](https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0) 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_azarafrooz__gemma-2b-it-nlai-v0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-15T12:20:29.148062](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0/blob/main/results_2024-04-15T12-20-29.148062.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": 0.37660169444969677, "acc_stderr": 0.03380673348549725, "acc_norm": 0.3811167415748182, "acc_norm_stderr": 0.03461538621374684, "mc1": 0.28886168910648713, "mc1_stderr": 0.015866346401384308, "mc2": 0.45797553398869045, "mc2_stderr": 0.015928281785783458 }, "harness\|arc:challenge\|25": { "acc": 0.4052901023890785, "acc_stderr": 0.014346869060229327, "acc_norm": 0.4402730375426621, "acc_norm_stderr": 0.014506769524804246 }, "harness\|hellaswag\|10": { "acc": 0.48137821151165106, "acc_stderr": 0.004986319587524964, "acc_norm": 0.6266679944234216, "acc_norm_stderr": 0.004827006520802888 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.3851851851851852, "acc_stderr": 0.042039210401562783, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.042039210401562783 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.3355263157894737, "acc_stderr": 0.03842498559395269, "acc_norm": 0.3355263157894737, "acc_norm_stderr": 0.03842498559395269 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956913, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956913 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.4226415094339623, "acc_stderr": 0.030402331445769537, "acc_norm": 0.4226415094339623, "acc_norm_stderr": 0.030402331445769537 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.3472222222222222, "acc_stderr": 0.039812405437178615, "acc_norm": 0.3472222222222222, "acc_norm_stderr": 0.039812405437178615 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "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": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3583815028901734, "acc_stderr": 0.036563436533531585, "acc_norm": 0.3583815028901734, "acc_norm_stderr": 0.036563436533531585 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617747, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617747 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3574468085106383, "acc_stderr": 0.03132941789476425, "acc_norm": 0.3574468085106383, "acc_norm_stderr": 0.03132941789476425 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.25132275132275134, "acc_stderr": 0.022340482339643895, "acc_norm": 0.25132275132275134, "acc_norm_stderr": 0.022340482339643895 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.3193548387096774, "acc_stderr": 0.026522709674667765, "acc_norm": 0.3193548387096774, "acc_norm_stderr": 0.026522709674667765 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.29064039408866993, "acc_stderr": 0.0319474007226554, "acc_norm": 0.29064039408866993, "acc_norm_stderr": 0.0319474007226554 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.45454545454545453, "acc_stderr": 0.03888176921674098, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.03888176921674098 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.4595959595959596, "acc_stderr": 0.035507024651313425, "acc_norm": 0.4595959595959596, "acc_norm_stderr": 0.035507024651313425 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.47150259067357514, "acc_stderr": 0.03602573571288442, "acc_norm": 0.47150259067357514, "acc_norm_stderr": 0.03602573571288442 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.33076923076923076, "acc_stderr": 0.023854795680971135, "acc_norm": 0.33076923076923076, "acc_norm_stderr": 0.023854795680971135 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2, "acc_stderr": 0.024388430433987664, "acc_norm": 0.2, "acc_norm_stderr": 0.024388430433987664 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.3403361344537815, "acc_stderr": 0.030778057422931673, "acc_norm": 0.3403361344537815, "acc_norm_stderr": 0.030778057422931673 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.26490066225165565, "acc_stderr": 0.03603038545360384, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.03603038545360384 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5027522935779817, "acc_stderr": 0.021436998359765317, "acc_norm": 0.5027522935779817, "acc_norm_stderr": 0.021436998359765317 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.19907407407407407, "acc_stderr": 0.027232298462690218, "acc_norm": 0.19907407407407407, "acc_norm_stderr": 0.027232298462690218 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.4166666666666667, "acc_stderr": 0.03460228327239171, "acc_norm": 0.4166666666666667, "acc_norm_stderr": 0.03460228327239171 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.5189873417721519, "acc_stderr": 0.03252375148090448, "acc_norm": 0.5189873417721519, "acc_norm_stderr": 0.03252375148090448 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.38565022421524664, "acc_stderr": 0.03266842214289201, "acc_norm": 0.38565022421524664, "acc_norm_stderr": 0.03266842214289201 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.4198473282442748, "acc_stderr": 0.043285772152629715, "acc_norm": 0.4198473282442748, "acc_norm_stderr": 0.043285772152629715 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.5206611570247934, "acc_stderr": 0.04560456086387235, "acc_norm": 0.5206611570247934, "acc_norm_stderr": 0.04560456086387235 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04826217294139894, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04826217294139894 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.36809815950920244, "acc_stderr": 0.03789213935838396, "acc_norm": 0.36809815950920244, "acc_norm_stderr": 0.03789213935838396 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.33035714285714285, "acc_stderr": 0.044642857142857116, "acc_norm": 0.33035714285714285, "acc_norm_stderr": 0.044642857142857116 }, "harness\|hendrycksTest-management\|5": { "acc": 0.44660194174757284, "acc_stderr": 0.04922424153458933, "acc_norm": 0.44660194174757284, "acc_norm_stderr": 0.04922424153458933 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.594017094017094, "acc_stderr": 0.03217180182641086, "acc_norm": 0.594017094017094, "acc_norm_stderr": 0.03217180182641086 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.4648786717752235, "acc_stderr": 0.017835798806290642, "acc_norm": 0.4648786717752235, "acc_norm_stderr": 0.017835798806290642 }, "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": 0.24581005586592178, "acc_stderr": 0.014400296429225624, "acc_norm": 0.24581005586592178, "acc_norm_stderr": 0.014400296429225624 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.028452639985088003, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.028452639985088003 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.40514469453376206, "acc_stderr": 0.02788238379132596, "acc_norm": 0.40514469453376206, "acc_norm_stderr": 0.02788238379132596 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.41358024691358025, "acc_stderr": 0.027402042040269952, "acc_norm": 0.41358024691358025, "acc_norm_stderr": 0.027402042040269952 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.3049645390070922, "acc_stderr": 0.027464708442022135, "acc_norm": 0.3049645390070922, "acc_norm_stderr": 0.027464708442022135 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.31747066492829207, "acc_stderr": 0.011888892068809312, "acc_norm": 0.31747066492829207, "acc_norm_stderr": 0.011888892068809312 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.20220588235294118, "acc_stderr": 0.024398192986654924, "acc_norm": 0.20220588235294118, "acc_norm_stderr": 0.024398192986654924 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.37745098039215685, "acc_stderr": 0.019610851474880286, "acc_norm": 0.37745098039215685, "acc_norm_stderr": 0.019610851474880286 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.41818181818181815, "acc_stderr": 0.0472457740573157, "acc_norm": 0.41818181818181815, "acc_norm_stderr": 0.0472457740573157 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.46938775510204084, "acc_stderr": 0.031949171367580624, "acc_norm": 0.46938775510204084, "acc_norm_stderr": 0.031949171367580624 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.4427860696517413, "acc_stderr": 0.03512310964123936, "acc_norm": 0.4427860696517413, "acc_norm_stderr": 0.03512310964123936 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.41566265060240964, "acc_stderr": 0.038367221765980515, "acc_norm": 0.41566265060240964, "acc_norm_stderr": 0.038367221765980515 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.4327485380116959, "acc_stderr": 0.03799978644370607, "acc_norm": 0.4327485380116959, "acc_norm_stderr": 0.03799978644370607 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.28886168910648713, "mc1_stderr": 0.015866346401384308, "mc2": 0.45797553398869045, "mc2_stderr": 0.015928281785783458 }, "harness\|winogrande\|5": { "acc": 0.6132596685082873, "acc_stderr": 0.013687214761883042 }, "harness\|gsm8k\|5": { "acc": 0.053828658074298714, "acc_stderr": 0.006216328640238136 } } ``` ## 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]
mask-distilled-onesec-cv12-each-chunk-uniq/chunk_55	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1315757524.0 num_examples: 258397 download_size: 1345022572 dataset_size: 1315757524.0 --- # Dataset Card for "chunk_55" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
hypno-ai/margiela-style	--- license: apache-2.0 ---
mrzbrt/test_audioset	--- dataset_info: features: - name: audio dtype: audio splits: - name: train num_bytes: 1267533455.0 num_examples: 401 download_size: 1227173992 dataset_size: 1267533455.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
Mitsuki-Sakamoto/alpaca_farm-deberta-re-pref-64-_fil_self_1.4b_bo16_2_64_mix_50_kl_0.1_prm_410m_thr_1.0_seed_2	--- dataset_info: config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string - name: index dtype: int64 - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: filtered_epoch dtype: int64 - name: gen_reward dtype: float64 - name: gen_response dtype: string splits: - name: epoch_0 num_bytes: 43744390 num_examples: 18928 - name: epoch_1 num_bytes: 43853451 num_examples: 18928 - name: epoch_2 num_bytes: 43703566 num_examples: 18928 - name: epoch_3 num_bytes: 43575131 num_examples: 18928 - name: epoch_4 num_bytes: 43518590 num_examples: 18928 - name: epoch_5 num_bytes: 43495671 num_examples: 18928 - name: epoch_6 num_bytes: 43474824 num_examples: 18928 - name: epoch_7 num_bytes: 43481960 num_examples: 18928 - name: epoch_8 num_bytes: 43468743 num_examples: 18928 - name: epoch_9 num_bytes: 43462697 num_examples: 18928 download_size: 278955072 dataset_size: 435779023 configs: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 data_files: - split: epoch_0 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_0-* - split: epoch_1 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_1-* - split: epoch_2 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_2-* - split: epoch_3 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_3-* - split: epoch_4 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_4-* - split: epoch_5 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_5-* - split: epoch_6 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_6-* - split: epoch_7 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_7-* - split: epoch_8 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_8-* - split: epoch_9 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_9-* ---
tanmay2798/codedataset	--- license: llama2 --- annotations_creators: - no-annotation language: - en language_creators: - expert-generated license: - other multilinguality: - monolingual pretty_name: codedataset size_categories: - n<1K source_datasets: - original tags: [] task_categories: - text2text-generation - text-generation - question-answering task_ids: - explanation-generation - open-book-qa - closed-book-qa - abstractive-qa - language-modeling - dialogue-modeling - extractive-qa
LorenzH/juliet_test_suite_c_1_3	--- license: cc0-1.0 task_categories: - text-classification pretty_name: Juliet Test Suite 1.3 size_categories: - 10K<n<100K --- # Dataset Card for the Juliet Test Suite 1.3 ### Dataset Summary This Datasets contains all test cases from the NIST's [Juliet test suite](https://samate.nist.gov/SARD/test-suites/112) for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite. ### Supported Tasks and Leaderboards Software defect prediction, code clone detection. ### Languages The C and C++ programming languages. ## Dataset Structure ### Data Instances ### Data Fields \| index \| name \| type \| description \| \| --- \| --- \| --- \| --- \| \| 0 \| index \| int \| The index of each sample in the dataset. \| \| 1 \| filename \| str \| The path to the test case including the file name. \| \| 2 \| class \| int \| The class of the defect, i.e., the collection by CWE number from which the sample was taken. \| \| 3 \| good \| str \| The code of the benign implementation. \| \| 4 \| bad \| str \| The code of the defective implementation. \| ### Data Splits \| type \| size \| \|------\|------\| \| train \| 80706 cases \| \| test \| 20177 cases \| ## Dataset Creation ### Curation Rationale ### Source Data https://samate.nist.gov/SARD/test-suites/112 #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment. ## Additional Information ### Dataset Curators https://github.com/lorenz9314/ ### Licensing Information ### Citation Information ### Contributions
open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu	--- pretty_name: Evaluation run of Charlie911/MultiLoRA-mmlu dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Charlie911/MultiLoRA-mmlu](https://huggingface.co/Charlie911/MultiLoRA-mmlu)\ \ 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_Charlie911__MultiLoRA-mmlu\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-02T00:16:37.919745](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu/blob/main/results_2024-02-02T00-16-37.919745.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\": 0.49682393519091933,\n\ \ \"acc_stderr\": 0.034234549326781244,\n \"acc_norm\": 0.5024513039750834,\n\ \ \"acc_norm_stderr\": 0.03499839555197597,\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.5020042655317223,\n\ \ \"mc2_stderr\": 0.015409102519026984\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.49658703071672355,\n \"acc_stderr\": 0.014611050403244077,\n\ \ \"acc_norm\": 0.5238907849829352,\n \"acc_norm_stderr\": 0.014594701798071654\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5803624775941048,\n\ \ \"acc_stderr\": 0.004924910433106353,\n \"acc_norm\": 0.7720573590918144,\n\ \ \"acc_norm_stderr\": 0.0041864806453155625\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\": 0.45185185185185184,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.45185185185185184,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.506578947368421,\n \"acc_stderr\": 0.040685900502249704,\n\ \ \"acc_norm\": 0.506578947368421,\n \"acc_norm_stderr\": 0.040685900502249704\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5169811320754717,\n \"acc_stderr\": 0.030755120364119905,\n\ \ \"acc_norm\": 0.5169811320754717,\n \"acc_norm_stderr\": 0.030755120364119905\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04181210050035455,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04181210050035455\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\": 0.4,\n\ \ \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.43352601156069365,\n\ \ \"acc_stderr\": 0.03778621079092055,\n \"acc_norm\": 0.43352601156069365,\n\ \ \"acc_norm_stderr\": 0.03778621079092055\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.16666666666666666,\n \"acc_stderr\": 0.03708284662416542,\n\ \ \"acc_norm\": 0.16666666666666666,\n \"acc_norm_stderr\": 0.03708284662416542\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.65,\n \"acc_stderr\": 0.047937248544110196,\n \"acc_norm\": 0.65,\n\ \ \"acc_norm_stderr\": 0.047937248544110196\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.43829787234042555,\n \"acc_stderr\": 0.032436186361081004,\n\ \ \"acc_norm\": 0.43829787234042555,\n \"acc_norm_stderr\": 0.032436186361081004\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2894736842105263,\n\ \ \"acc_stderr\": 0.04266339443159393,\n \"acc_norm\": 0.2894736842105263,\n\ \ \"acc_norm_stderr\": 0.04266339443159393\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4689655172413793,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.4689655172413793,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2857142857142857,\n \"acc_stderr\": 0.023266512213730578,\n \"\ acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.023266512213730578\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3253968253968254,\n\ \ \"acc_stderr\": 0.04190596438871136,\n \"acc_norm\": 0.3253968253968254,\n\ \ \"acc_norm_stderr\": 0.04190596438871136\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\": 0.535483870967742,\n\ \ \"acc_stderr\": 0.02837228779796293,\n \"acc_norm\": 0.535483870967742,\n\ \ \"acc_norm_stderr\": 0.02837228779796293\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.39901477832512317,\n \"acc_stderr\": 0.03445487686264715,\n\ \ \"acc_norm\": 0.39901477832512317,\n \"acc_norm_stderr\": 0.03445487686264715\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512567,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512567\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.5909090909090909,\n \"acc_stderr\": 0.03502975799413007,\n \"\ acc_norm\": 0.5909090909090909,\n \"acc_norm_stderr\": 0.03502975799413007\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7046632124352331,\n \"acc_stderr\": 0.03292296639155141,\n\ \ \"acc_norm\": 0.7046632124352331,\n \"acc_norm_stderr\": 0.03292296639155141\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4717948717948718,\n \"acc_stderr\": 0.025310639254933893,\n\ \ \"acc_norm\": 0.4717948717948718,\n \"acc_norm_stderr\": 0.025310639254933893\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275805,\n \ \ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275805\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.4369747899159664,\n \"acc_stderr\": 0.03221943636566196,\n \ \ \"acc_norm\": 0.4369747899159664,\n \"acc_norm_stderr\": 0.03221943636566196\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969653,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969653\n },\n\ \ \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\": 0.6770642201834862,\n\ \ \"acc_stderr\": 0.02004811592341531,\n \"acc_norm\": 0.6770642201834862,\n\ \ \"acc_norm_stderr\": 0.02004811592341531\n },\n \"harness\|hendrycksTest-high_school_statistics\|5\"\ : {\n \"acc\": 0.39351851851851855,\n \"acc_stderr\": 0.03331747876370312,\n\ \ \"acc_norm\": 0.39351851851851855,\n \"acc_norm_stderr\": 0.03331747876370312\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.696078431372549,\n \"acc_stderr\": 0.032282103870378935,\n \"\ acc_norm\": 0.696078431372549,\n \"acc_norm_stderr\": 0.032282103870378935\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.6877637130801688,\n \"acc_stderr\": 0.03016513786784701,\n \ \ \"acc_norm\": 0.6877637130801688,\n \"acc_norm_stderr\": 0.03016513786784701\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.5560538116591929,\n\ \ \"acc_stderr\": 0.03334625674242728,\n \"acc_norm\": 0.5560538116591929,\n\ \ \"acc_norm_stderr\": 0.03334625674242728\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5877862595419847,\n \"acc_stderr\": 0.04317171194870254,\n\ \ \"acc_norm\": 0.5877862595419847,\n \"acc_norm_stderr\": 0.04317171194870254\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.5537190082644629,\n \"acc_stderr\": 0.0453793517794788,\n \"acc_norm\"\ : 0.5537190082644629,\n \"acc_norm_stderr\": 0.0453793517794788\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.5648148148148148,\n\ \ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.5648148148148148,\n\ \ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.5337423312883436,\n \"acc_stderr\": 0.039194155450484096,\n\ \ \"acc_norm\": 0.5337423312883436,\n \"acc_norm_stderr\": 0.039194155450484096\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4375,\n\ \ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \ \ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.6699029126213593,\n \"acc_stderr\": 0.0465614711001235,\n\ \ \"acc_norm\": 0.6699029126213593,\n \"acc_norm_stderr\": 0.0465614711001235\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.7692307692307693,\n\ \ \"acc_stderr\": 0.0276019213814176,\n \"acc_norm\": 0.7692307692307693,\n\ \ \"acc_norm_stderr\": 0.0276019213814176\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \ \ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.669220945083014,\n\ \ \"acc_stderr\": 0.01682481846256376,\n \"acc_norm\": 0.669220945083014,\n\ \ \"acc_norm_stderr\": 0.01682481846256376\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.546242774566474,\n \"acc_stderr\": 0.02680372058320617,\n\ \ \"acc_norm\": 0.546242774566474,\n \"acc_norm_stderr\": 0.02680372058320617\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24022346368715083,\n\ \ \"acc_stderr\": 0.014288343803925293,\n \"acc_norm\": 0.24022346368715083,\n\ \ \"acc_norm_stderr\": 0.014288343803925293\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5359477124183006,\n \"acc_stderr\": 0.028555827516528784,\n\ \ \"acc_norm\": 0.5359477124183006,\n \"acc_norm_stderr\": 0.028555827516528784\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.5787781350482315,\n\ \ \"acc_stderr\": 0.02804339985821063,\n \"acc_norm\": 0.5787781350482315,\n\ \ \"acc_norm_stderr\": 0.02804339985821063\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.558641975308642,\n \"acc_stderr\": 0.027628737155668767,\n\ \ \"acc_norm\": 0.558641975308642,\n \"acc_norm_stderr\": 0.027628737155668767\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.36524822695035464,\n \"acc_stderr\": 0.02872386385328128,\n \ \ \"acc_norm\": 0.36524822695035464,\n \"acc_norm_stderr\": 0.02872386385328128\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.363754889178618,\n\ \ \"acc_stderr\": 0.012286991879902887,\n \"acc_norm\": 0.363754889178618,\n\ \ \"acc_norm_stderr\": 0.012286991879902887\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5404411764705882,\n \"acc_stderr\": 0.03027332507734575,\n\ \ \"acc_norm\": 0.5404411764705882,\n \"acc_norm_stderr\": 0.03027332507734575\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.4869281045751634,\n \"acc_stderr\": 0.020220920829626916,\n \ \ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.020220920829626916\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.5727272727272728,\n\ \ \"acc_stderr\": 0.04738198703545484,\n \"acc_norm\": 0.5727272727272728,\n\ \ \"acc_norm_stderr\": 0.04738198703545484\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6408163265306123,\n \"acc_stderr\": 0.030713560455108493,\n\ \ \"acc_norm\": 0.6408163265306123,\n \"acc_norm_stderr\": 0.030713560455108493\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.6865671641791045,\n\ \ \"acc_stderr\": 0.03280188205348644,\n \"acc_norm\": 0.6865671641791045,\n\ \ \"acc_norm_stderr\": 0.03280188205348644\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.45180722891566266,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.45180722891566266,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7192982456140351,\n \"acc_stderr\": 0.03446296217088427,\n\ \ \"acc_norm\": 0.7192982456140351,\n \"acc_norm_stderr\": 0.03446296217088427\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.5020042655317223,\n\ \ \"mc2_stderr\": 0.015409102519026984\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7221783741120757,\n \"acc_stderr\": 0.012588918183871596\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.15845337376800606,\n \ \ \"acc_stderr\": 0.010058474790238962\n }\n}\n```" repo_url: https://huggingface.co/Charlie911/MultiLoRA-mmlu 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_02T00_16_37.919745 path: - '/details_harness\|arc:challenge\|25_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-02T00-16-37.919745.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|gsm8k\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hellaswag\|10_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-02T00-16-37.919745.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-02T00-16-37.919745.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '/details_harness\|winogrande\|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-02T00-16-37.919745.parquet' - config_name: results data_files: - split: 2024_02_02T00_16_37.919745 path: - results_2024-02-02T00-16-37.919745.parquet - split: latest path: - results_2024-02-02T00-16-37.919745.parquet --- # Dataset Card for Evaluation run of Charlie911/MultiLoRA-mmlu <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Charlie911/MultiLoRA-mmlu](https://huggingface.co/Charlie911/MultiLoRA-mmlu) 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_Charlie911__MultiLoRA-mmlu", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-02T00:16:37.919745](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu/blob/main/results_2024-02-02T00-16-37.919745.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": 0.49682393519091933, "acc_stderr": 0.034234549326781244, "acc_norm": 0.5024513039750834, "acc_norm_stderr": 0.03499839555197597, "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.5020042655317223, "mc2_stderr": 0.015409102519026984 }, "harness\|arc:challenge\|25": { "acc": 0.49658703071672355, "acc_stderr": 0.014611050403244077, "acc_norm": 0.5238907849829352, "acc_norm_stderr": 0.014594701798071654 }, "harness\|hellaswag\|10": { "acc": 0.5803624775941048, "acc_stderr": 0.004924910433106353, "acc_norm": 0.7720573590918144, "acc_norm_stderr": 0.0041864806453155625 }, "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": 0.45185185185185184, "acc_stderr": 0.04299268905480864, "acc_norm": 0.45185185185185184, "acc_norm_stderr": 0.04299268905480864 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.506578947368421, "acc_stderr": 0.040685900502249704, "acc_norm": 0.506578947368421, "acc_norm_stderr": 0.040685900502249704 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5169811320754717, "acc_stderr": 0.030755120364119905, "acc_norm": 0.5169811320754717, "acc_norm_stderr": 0.030755120364119905 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.5, "acc_stderr": 0.04181210050035455, "acc_norm": 0.5, "acc_norm_stderr": 0.04181210050035455 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.43352601156069365, "acc_stderr": 0.03778621079092055, "acc_norm": 0.43352601156069365, "acc_norm_stderr": 0.03778621079092055 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.16666666666666666, "acc_stderr": 0.03708284662416542, "acc_norm": 0.16666666666666666, "acc_norm_stderr": 0.03708284662416542 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.43829787234042555, "acc_stderr": 0.032436186361081004, "acc_norm": 0.43829787234042555, "acc_norm_stderr": 0.032436186361081004 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159393, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159393 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2857142857142857, "acc_stderr": 0.023266512213730578, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.023266512213730578 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3253968253968254, "acc_stderr": 0.04190596438871136, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.04190596438871136 }, "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": 0.535483870967742, "acc_stderr": 0.02837228779796293, "acc_norm": 0.535483870967742, "acc_norm_stderr": 0.02837228779796293 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.39901477832512317, "acc_stderr": 0.03445487686264715, "acc_norm": 0.39901477832512317, "acc_norm_stderr": 0.03445487686264715 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512567, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512567 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.5909090909090909, "acc_stderr": 0.03502975799413007, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.03502975799413007 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7046632124352331, "acc_stderr": 0.03292296639155141, "acc_norm": 0.7046632124352331, "acc_norm_stderr": 0.03292296639155141 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.4717948717948718, "acc_stderr": 0.025310639254933893, "acc_norm": 0.4717948717948718, "acc_norm_stderr": 0.025310639254933893 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.24074074074074073, "acc_stderr": 0.026067159222275805, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.026067159222275805 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.4369747899159664, "acc_stderr": 0.03221943636566196, "acc_norm": 0.4369747899159664, "acc_norm_stderr": 0.03221943636566196 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969653, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969653 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.6770642201834862, "acc_stderr": 0.02004811592341531, "acc_norm": 0.6770642201834862, "acc_norm_stderr": 0.02004811592341531 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.39351851851851855, "acc_stderr": 0.03331747876370312, "acc_norm": 0.39351851851851855, "acc_norm_stderr": 0.03331747876370312 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.696078431372549, "acc_stderr": 0.032282103870378935, "acc_norm": 0.696078431372549, "acc_norm_stderr": 0.032282103870378935 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.6877637130801688, "acc_stderr": 0.03016513786784701, "acc_norm": 0.6877637130801688, "acc_norm_stderr": 0.03016513786784701 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.5560538116591929, "acc_stderr": 0.03334625674242728, "acc_norm": 0.5560538116591929, "acc_norm_stderr": 0.03334625674242728 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5877862595419847, "acc_stderr": 0.04317171194870254, "acc_norm": 0.5877862595419847, "acc_norm_stderr": 0.04317171194870254 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.5537190082644629, "acc_stderr": 0.0453793517794788, "acc_norm": 0.5537190082644629, "acc_norm_stderr": 0.0453793517794788 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.5648148148148148, "acc_stderr": 0.04792898170907061, "acc_norm": 0.5648148148148148, "acc_norm_stderr": 0.04792898170907061 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.5337423312883436, "acc_stderr": 0.039194155450484096, "acc_norm": 0.5337423312883436, "acc_norm_stderr": 0.039194155450484096 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4375, "acc_stderr": 0.04708567521880525, "acc_norm": 0.4375, "acc_norm_stderr": 0.04708567521880525 }, "harness\|hendrycksTest-management\|5": { "acc": 0.6699029126213593, "acc_stderr": 0.0465614711001235, "acc_norm": 0.6699029126213593, "acc_norm_stderr": 0.0465614711001235 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.7692307692307693, "acc_stderr": 0.0276019213814176, "acc_norm": 0.7692307692307693, "acc_norm_stderr": 0.0276019213814176 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.669220945083014, "acc_stderr": 0.01682481846256376, "acc_norm": 0.669220945083014, "acc_norm_stderr": 0.01682481846256376 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.546242774566474, "acc_stderr": 0.02680372058320617, "acc_norm": 0.546242774566474, "acc_norm_stderr": 0.02680372058320617 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.24022346368715083, "acc_stderr": 0.014288343803925293, "acc_norm": 0.24022346368715083, "acc_norm_stderr": 0.014288343803925293 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.5359477124183006, "acc_stderr": 0.028555827516528784, "acc_norm": 0.5359477124183006, "acc_norm_stderr": 0.028555827516528784 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.5787781350482315, "acc_stderr": 0.02804339985821063, "acc_norm": 0.5787781350482315, "acc_norm_stderr": 0.02804339985821063 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.558641975308642, "acc_stderr": 0.027628737155668767, "acc_norm": 0.558641975308642, "acc_norm_stderr": 0.027628737155668767 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.36524822695035464, "acc_stderr": 0.02872386385328128, "acc_norm": 0.36524822695035464, "acc_norm_stderr": 0.02872386385328128 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.363754889178618, "acc_stderr": 0.012286991879902887, "acc_norm": 0.363754889178618, "acc_norm_stderr": 0.012286991879902887 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5404411764705882, "acc_stderr": 0.03027332507734575, "acc_norm": 0.5404411764705882, "acc_norm_stderr": 0.03027332507734575 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.4869281045751634, "acc_stderr": 0.020220920829626916, "acc_norm": 0.4869281045751634, "acc_norm_stderr": 0.020220920829626916 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.5727272727272728, "acc_stderr": 0.04738198703545484, "acc_norm": 0.5727272727272728, "acc_norm_stderr": 0.04738198703545484 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6408163265306123, "acc_stderr": 0.030713560455108493, "acc_norm": 0.6408163265306123, "acc_norm_stderr": 0.030713560455108493 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.6865671641791045, "acc_stderr": 0.03280188205348644, "acc_norm": 0.6865671641791045, "acc_norm_stderr": 0.03280188205348644 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.45180722891566266, "acc_stderr": 0.03874371556587953, "acc_norm": 0.45180722891566266, "acc_norm_stderr": 0.03874371556587953 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7192982456140351, "acc_stderr": 0.03446296217088427, "acc_norm": 0.7192982456140351, "acc_norm_stderr": 0.03446296217088427 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.5020042655317223, "mc2_stderr": 0.015409102519026984 }, "harness\|winogrande\|5": { "acc": 0.7221783741120757, "acc_stderr": 0.012588918183871596 }, "harness\|gsm8k\|5": { "acc": 0.15845337376800606, "acc_stderr": 0.010058474790238962 } } ``` ## 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]
gemma111/customhkcode2	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5826 num_examples: 39 download_size: 2572 dataset_size: 5826 configs: - config_name: default data_files: - split: train path: data/train-* ---

d0rj/conala-mined-ru

--- dataset_info: features: - name: question_id dtype: int64 - name: parent_answer_post_id dtype: int64 - name: prob dtype: float64 - name: snippet dtype: string - name: intent dtype: string - name: id dtype: string splits: - name: train num_bytes: 115298717.0 num_examples: 593891 download_size: 78541384 dataset_size: 115298717.0 --- # Dataset Card for "conala-mined-ru" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

autoevaluate/autoeval-eval-samsum-samsum-ec1044-95879146522

--- type: predictions tags: - autotrain - evaluation datasets: - samsum eval_info: task: summarization model: Joemgu/mlong-t5-large-sumstew metrics: [] dataset_name: samsum dataset_config: samsum dataset_split: test col_mapping: text: dialogue target: summary --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: Joemgu/mlong-t5-large-sumstew * Dataset: samsum * Config: samsum * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@baohuynhbk14](https://huggingface.co/baohuynhbk14) for evaluating this model.

CyberHarem/mutsu_kantaicollection

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of mutsu/陸奥 (Kantai Collection) This is the dataset of mutsu/陸奥 (Kantai Collection), containing 500 images and their tags. The core tags of this character are `brown_hair, short_hair, green_eyes, breasts, large_breasts, headgear, hair_between_eyes`, 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 | 608.09 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 500 | 377.33 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 1228 | 781.47 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 500 | 551.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1228 | 1.02 GiB | [Download](https://huggingface.co/datasets/CyberHarem/mutsu_kantaicollection/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/mutsu_kantaicollection', 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 | 11 | ![](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, chain, looking_at_viewer, pleated_skirt, solo, white_gloves, black_skirt, smile, midriff, miniskirt, red_thighhighs, radio_antenna, simple_background, turret, cleavage, navel, rigging, white_background, blush, cannon | | 1 | 39 | ![](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) | midriff, solo, 1girl, looking_at_viewer, white_gloves, bare_shoulders, miniskirt, hairband, navel, chain, red_thighhighs, smile | | 2 | 14 | ![](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, collarbone, looking_at_viewer, solo, smile, blush, simple_background, white_background, closed_mouth, cleavage, upper_body, alternate_costume | | 3 | 8 | ![](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, cloud, day, looking_at_viewer, outdoors, solo, blush, collarbone, cowboy_shot, navel, smile, beach, black_bikini, cleavage, ocean, side-tie_bikini_bottom, closed_mouth, flipped_hair, blue_sky, open_mouth | | 4 | 15 | ![](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, huge_breasts, looking_at_viewer, solo, thick_thighs, curvy, thighhighs, navel, cleavage, wide_hips, bikini, gloves, smile, tan, collar | | 5 | 23 | ![](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, solo, alternate_costume, looking_at_viewer, smile, obi, wide_sleeves, blush, long_sleeves, yukata, floral_print, hair_flower, striped, upper_body | | 6 | 15 | ![](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, fake_animal_ears, playboy_bunny, rabbit_ears, solo, detached_collar, wrist_cuffs, black_leotard, looking_at_viewer, bowtie, cleavage, pantyhose, simple_background, smile, strapless_leotard, blush, rabbit_tail, white_background, collarbone, cowboy_shot | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | chain | looking_at_viewer | pleated_skirt | solo | white_gloves | black_skirt | smile | midriff | miniskirt | red_thighhighs | radio_antenna | simple_background | turret | cleavage | navel | rigging | white_background | blush | cannon | bare_shoulders | hairband | collarbone | closed_mouth | upper_body | alternate_costume | cloud | day | outdoors | cowboy_shot | beach | black_bikini | ocean | side-tie_bikini_bottom | flipped_hair | blue_sky | open_mouth | huge_breasts | thick_thighs | curvy | thighhighs | wide_hips | bikini | gloves | tan | collar | obi | wide_sleeves | long_sleeves | yukata | floral_print | hair_flower | striped | fake_animal_ears | playboy_bunny | rabbit_ears | detached_collar | wrist_cuffs | black_leotard | bowtie | pantyhose | strapless_leotard | rabbit_tail | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:--------------------|:----------------|:-------|:---------------|:--------------|:--------|:----------|:------------|:-----------------|:----------------|:--------------------|:---------|:-----------|:--------|:----------|:-------------------|:--------|:---------|:-----------------|:-----------|:-------------|:---------------|:-------------|:--------------------|:--------|:------|:-----------|:--------------|:--------|:---------------|:--------|:-------------------------|:---------------|:-----------|:-------------|:---------------|:---------------|:--------|:-------------|:------------|:---------|:---------|:------|:---------|:------|:---------------|:---------------|:---------|:---------------|:--------------|:----------|:-------------------|:----------------|:--------------|:------------------|:--------------|:----------------|:---------|:------------|:--------------------|:--------------| | 0 | 11 | ![](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 | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 39 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 14 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 8 | ![](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 | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 15 | ![](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 | | | | | | | | | | | | | | | | | | | 5 | 23 | ![](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 | | | | | | | | | | | | 6 | 15 | ![](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 |

fformosa/LSUN_bedroom_VQA_v2

--- dataset_info: features: - name: image dtype: image - name: size sequence: int64 - name: proportion dtype: float64 - name: new_image_id dtype: int64 - name: new_attributes sequence: string splits: - name: train num_bytes: 836782860 num_examples: 58266 download_size: 815988446 dataset_size: 836782860 configs: - config_name: default data_files: - split: train path: data/train-* license: mit task_categories: - question-answering - zero-shot-classification - feature-extraction - visual-question-answering - image-classification language: - en size_categories: - 10K<n<100K --- # Dataset Card for "CSUN_bedroom_VQA_feliu_v2" ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63e128c64d82d6230587e5ee/9-vsm9GttCzxpZI6hrIJW.png)

open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser

--- pretty_name: Evaluation run of Kquant03/NeuralTrix-7B-dpo-laser dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser)\ \ 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_Kquant03__NeuralTrix-7B-dpo-laser\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-14T14:37:51.781058](https://huggingface.co/datasets/open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser/blob/main/results_2024-02-14T14-37-51.781058.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\": 0.645893629951843,\n\ \ \"acc_stderr\": 0.03226186920457953,\n \"acc_norm\": 0.6452717180915718,\n\ \ \"acc_norm_stderr\": 0.03293869736005958,\n \"mc1\": 0.6291309669522643,\n\ \ \"mc1_stderr\": 0.01690969358024884,\n \"mc2\": 0.7814534342142354,\n\ \ \"mc2_stderr\": 0.013720660446321574\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6911262798634812,\n \"acc_stderr\": 0.013501770929344003,\n\ \ \"acc_norm\": 0.7133105802047781,\n \"acc_norm_stderr\": 0.013214986329274772\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7005576578370842,\n\ \ \"acc_stderr\": 0.004570777326263903,\n \"acc_norm\": 0.8850826528579964,\n\ \ \"acc_norm_stderr\": 0.00318270383035113\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\ \ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\ \ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6981132075471698,\n \"acc_stderr\": 0.028254200344438662,\n\ \ \"acc_norm\": 0.6981132075471698,\n \"acc_norm_stderr\": 0.028254200344438662\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7638888888888888,\n\ \ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.7638888888888888,\n\ \ \"acc_norm_stderr\": 0.03551446610810826\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\"\ : 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n\ \ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.31,\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\": 0.6416184971098265,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107224,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107224\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n\ \ \"acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5087719298245614,\n\ \ \"acc_stderr\": 0.047028804320496165,\n \"acc_norm\": 0.5087719298245614,\n\ \ \"acc_norm_stderr\": 0.047028804320496165\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555498,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555498\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42328042328042326,\n \"acc_stderr\": 0.025446365634406762,\n \"\ acc_norm\": 0.42328042328042326,\n \"acc_norm_stderr\": 0.025446365634406762\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\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\": 0.7580645161290323,\n\ \ \"acc_stderr\": 0.024362599693031086,\n \"acc_norm\": 0.7580645161290323,\n\ \ \"acc_norm_stderr\": 0.024362599693031086\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\": 0.71,\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\": 0.7818181818181819,\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\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.02247325333276877,\n\ \ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.02247325333276877\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\": 0.3148148148148148,\n \"acc_stderr\": 0.02831753349606649,\n \ \ \"acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.02831753349606649\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.030778057422931673,\n\ \ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.030778057422931673\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.39072847682119205,\n \"acc_stderr\": 0.039837983066598075,\n \"\ acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.039837983066598075\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8422018348623853,\n \"acc_stderr\": 0.015630022970092427,\n \"\ acc_norm\": 0.8422018348623853,\n \"acc_norm_stderr\": 0.015630022970092427\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8333333333333334,\n \"acc_stderr\": 0.026156867523931048,\n \"\ acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.026156867523931048\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.810126582278481,\n \"acc_stderr\": 0.02553010046023349,\n \ \ \"acc_norm\": 0.810126582278481,\n \"acc_norm_stderr\": 0.02553010046023349\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.036412970813137296,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.036412970813137296\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4107142857142857,\n\ \ \"acc_stderr\": 0.046695106638751906,\n \"acc_norm\": 0.4107142857142857,\n\ \ \"acc_norm_stderr\": 0.046695106638751906\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406974,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406974\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.8263090676883781,\n\ \ \"acc_stderr\": 0.01354741565866226,\n \"acc_norm\": 0.8263090676883781,\n\ \ \"acc_norm_stderr\": 0.01354741565866226\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7138728323699421,\n \"acc_stderr\": 0.02433214677913413,\n\ \ \"acc_norm\": 0.7138728323699421,\n \"acc_norm_stderr\": 0.02433214677913413\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4424581005586592,\n\ \ \"acc_stderr\": 0.01661139368726858,\n \"acc_norm\": 0.4424581005586592,\n\ \ \"acc_norm_stderr\": 0.01661139368726858\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7124183006535948,\n \"acc_stderr\": 0.02591780611714716,\n\ \ \"acc_norm\": 0.7124183006535948,\n \"acc_norm_stderr\": 0.02591780611714716\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6752411575562701,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7407407407407407,\n \"acc_stderr\": 0.024383665531035454,\n\ \ \"acc_norm\": 0.7407407407407407,\n \"acc_norm_stderr\": 0.024383665531035454\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\": 0.470013037809648,\n\ \ \"acc_stderr\": 0.012747248967079072,\n \"acc_norm\": 0.470013037809648,\n\ \ \"acc_norm_stderr\": 0.012747248967079072\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6691176470588235,\n \"acc_stderr\": 0.028582709753898445,\n\ \ \"acc_norm\": 0.6691176470588235,\n \"acc_norm_stderr\": 0.028582709753898445\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6748366013071896,\n \"acc_stderr\": 0.01895088677080632,\n \ \ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.01895088677080632\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7224489795918367,\n \"acc_stderr\": 0.028666857790274648,\n\ \ \"acc_norm\": 0.7224489795918367,\n \"acc_norm_stderr\": 0.028666857790274648\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.845771144278607,\n\ \ \"acc_stderr\": 0.025538433368578337,\n \"acc_norm\": 0.845771144278607,\n\ \ \"acc_norm_stderr\": 0.025538433368578337\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5602409638554217,\n\ \ \"acc_stderr\": 0.03864139923699122,\n \"acc_norm\": 0.5602409638554217,\n\ \ \"acc_norm_stderr\": 0.03864139923699122\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\": 0.6291309669522643,\n\ \ \"mc1_stderr\": 0.01690969358024884,\n \"mc2\": 0.7814534342142354,\n\ \ \"mc2_stderr\": 0.013720660446321574\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8445146014206788,\n \"acc_stderr\": 0.010184308214775777\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.690674753601213,\n \ \ \"acc_stderr\": 0.012731710925078134\n }\n}\n```" repo_url: https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser 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_14T14_37_51.781058 path: - '**/details_harness|arc:challenge|25_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-14T14-37-51.781058.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|gsm8k|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hellaswag|10_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-14T14-37-51.781058.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-management|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-14T14-37-51.781058.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|truthfulqa:mc|0_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-14T14-37-51.781058.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_14T14_37_51.781058 path: - '**/details_harness|winogrande|5_2024-02-14T14-37-51.781058.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-14T14-37-51.781058.parquet' - config_name: results data_files: - split: 2024_02_14T14_37_51.781058 path: - results_2024-02-14T14-37-51.781058.parquet - split: latest path: - results_2024-02-14T14-37-51.781058.parquet --- # Dataset Card for Evaluation run of Kquant03/NeuralTrix-7B-dpo-laser  Dataset automatically created during the evaluation run of model [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser) 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_Kquant03__NeuralTrix-7B-dpo-laser", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-14T14:37:51.781058](https://huggingface.co/datasets/open-llm-leaderboard/details_Kquant03__NeuralTrix-7B-dpo-laser/blob/main/results_2024-02-14T14-37-51.781058.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": 0.645893629951843, "acc_stderr": 0.03226186920457953, "acc_norm": 0.6452717180915718, "acc_norm_stderr": 0.03293869736005958, "mc1": 0.6291309669522643, "mc1_stderr": 0.01690969358024884, "mc2": 0.7814534342142354, "mc2_stderr": 0.013720660446321574 }, "harness|arc:challenge|25": { "acc": 0.6911262798634812, "acc_stderr": 0.013501770929344003, "acc_norm": 0.7133105802047781, "acc_norm_stderr": 0.013214986329274772 }, "harness|hellaswag|10": { "acc": 0.7005576578370842, "acc_stderr": 0.004570777326263903, "acc_norm": 0.8850826528579964, "acc_norm_stderr": 0.00318270383035113 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595853, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6981132075471698, "acc_stderr": 0.028254200344438662, "acc_norm": 0.6981132075471698, "acc_norm_stderr": 0.028254200344438662 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "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": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "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": 0.6416184971098265, "acc_stderr": 0.036563436533531585, "acc_norm": 0.6416184971098265, "acc_norm_stderr": 0.036563436533531585 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107224, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107224 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5087719298245614, "acc_stderr": 0.047028804320496165, "acc_norm": 0.5087719298245614, "acc_norm_stderr": 0.047028804320496165 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555498, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555498 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42328042328042326, "acc_stderr": 0.025446365634406762, "acc_norm": 0.42328042328042326, "acc_norm_stderr": 0.025446365634406762 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7580645161290323, "acc_stderr": 0.024362599693031086, "acc_norm": 0.7580645161290323, "acc_norm_stderr": 0.024362599693031086 }, "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": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "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": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8911917098445595, "acc_stderr": 0.02247325333276877, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.02247325333276877 }, "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": 0.3148148148148148, "acc_stderr": 0.02831753349606649, "acc_norm": 0.3148148148148148, "acc_norm_stderr": 0.02831753349606649 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6596638655462185, "acc_stderr": 0.030778057422931673, "acc_norm": 0.6596638655462185, "acc_norm_stderr": 0.030778057422931673 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.39072847682119205, "acc_stderr": 0.039837983066598075, "acc_norm": 0.39072847682119205, "acc_norm_stderr": 0.039837983066598075 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8422018348623853, "acc_stderr": 0.015630022970092427, "acc_norm": 0.8422018348623853, "acc_norm_stderr": 0.015630022970092427 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8333333333333334, "acc_stderr": 0.026156867523931048, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.026156867523931048 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.810126582278481, "acc_stderr": 0.02553010046023349, "acc_norm": 0.810126582278481, "acc_norm_stderr": 0.02553010046023349 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6905829596412556, "acc_stderr": 0.03102441174057221, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.03102441174057221 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7786259541984732, "acc_stderr": 0.036412970813137296, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.036412970813137296 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070416, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070416 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7484662576687117, "acc_stderr": 0.03408997886857529, "acc_norm": 0.7484662576687117, "acc_norm_stderr": 0.03408997886857529 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4107142857142857, "acc_stderr": 0.046695106638751906, "acc_norm": 0.4107142857142857, "acc_norm_stderr": 0.046695106638751906 }, "harness|hendrycksTest-management|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406974, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406974 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8263090676883781, "acc_stderr": 0.01354741565866226, "acc_norm": 0.8263090676883781, "acc_norm_stderr": 0.01354741565866226 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7138728323699421, "acc_stderr": 0.02433214677913413, "acc_norm": 0.7138728323699421, "acc_norm_stderr": 0.02433214677913413 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4424581005586592, "acc_stderr": 0.01661139368726858, "acc_norm": 0.4424581005586592, "acc_norm_stderr": 0.01661139368726858 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7124183006535948, "acc_stderr": 0.02591780611714716, "acc_norm": 0.7124183006535948, "acc_norm_stderr": 0.02591780611714716 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6752411575562701, "acc_stderr": 0.026596782287697043, "acc_norm": 0.6752411575562701, "acc_norm_stderr": 0.026596782287697043 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7407407407407407, "acc_stderr": 0.024383665531035454, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.024383665531035454 }, "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": 0.470013037809648, "acc_stderr": 0.012747248967079072, "acc_norm": 0.470013037809648, "acc_norm_stderr": 0.012747248967079072 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6691176470588235, "acc_stderr": 0.028582709753898445, "acc_norm": 0.6691176470588235, "acc_norm_stderr": 0.028582709753898445 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6748366013071896, "acc_stderr": 0.01895088677080632, "acc_norm": 0.6748366013071896, "acc_norm_stderr": 0.01895088677080632 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7224489795918367, "acc_stderr": 0.028666857790274648, "acc_norm": 0.7224489795918367, "acc_norm_stderr": 0.028666857790274648 }, "harness|hendrycksTest-sociology|5": { "acc": 0.845771144278607, "acc_stderr": 0.025538433368578337, "acc_norm": 0.845771144278607, "acc_norm_stderr": 0.025538433368578337 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.03588702812826371, "acc_norm": 0.85, "acc_norm_stderr": 0.03588702812826371 }, "harness|hendrycksTest-virology|5": { "acc": 0.5602409638554217, "acc_stderr": 0.03864139923699122, "acc_norm": 0.5602409638554217, "acc_norm_stderr": 0.03864139923699122 }, "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": 0.6291309669522643, "mc1_stderr": 0.01690969358024884, "mc2": 0.7814534342142354, "mc2_stderr": 0.013720660446321574 }, "harness|winogrande|5": { "acc": 0.8445146014206788, "acc_stderr": 0.010184308214775777 }, "harness|gsm8k|5": { "acc": 0.690674753601213, "acc_stderr": 0.012731710925078134 } } ``` ## 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]

syeda-raisa/paraphrase_final

--- license: apache-2.0 --- #idiom paraphrase

socius/VADER_2014

--- license: cc-by-nc-sa-4.0 language: - en tags: - sentiment - social media size_categories: - 1K<n<10K ---

open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M

--- pretty_name: Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M)\ \ 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_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-12T07:34:24.161560](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M/blob/main/results_2023-12-12T07-34-24.161560.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\": 0.2574568669647554,\n\ \ \"acc_stderr\": 0.03077370055460631,\n \"acc_norm\": 0.258555233951132,\n\ \ \"acc_norm_stderr\": 0.031529415596877046,\n \"mc1\": 0.25091799265605874,\n\ \ \"mc1_stderr\": 0.015176985027707687,\n \"mc2\": 0.38841425251899087,\n\ \ \"mc2_stderr\": 0.014859033830490542\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.1945392491467577,\n \"acc_stderr\": 0.011567709174648728,\n\ \ \"acc_norm\": 0.24573378839590443,\n \"acc_norm_stderr\": 0.012581033453730113\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.2842063333997212,\n\ \ \"acc_stderr\": 0.004501137895230712,\n \"acc_norm\": 0.29426409081856203,\n\ \ \"acc_norm_stderr\": 0.00454779896412667\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909283\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.2518518518518518,\n\ \ \"acc_stderr\": 0.037498507091740234,\n \"acc_norm\": 0.2518518518518518,\n\ \ \"acc_norm_stderr\": 0.037498507091740234\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\": 0.22,\n\ \ \"acc_stderr\": 0.0416333199893227,\n \"acc_norm\": 0.22,\n \ \ \"acc_norm_stderr\": 0.0416333199893227\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.02461829819586651,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.02461829819586651\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\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\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\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.26011560693641617,\n\ \ \"acc_stderr\": 0.03345036916788992,\n \"acc_norm\": 0.26011560693641617,\n\ \ \"acc_norm_stderr\": 0.03345036916788992\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.23529411764705882,\n \"acc_stderr\": 0.04220773659171453,\n\ \ \"acc_norm\": 0.23529411764705882,\n \"acc_norm_stderr\": 0.04220773659171453\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.15,\n \"acc_stderr\": 0.035887028128263734,\n \"acc_norm\": 0.15,\n\ \ \"acc_norm_stderr\": 0.035887028128263734\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.2765957446808511,\n \"acc_stderr\": 0.0292418838696288,\n\ \ \"acc_norm\": 0.2765957446808511,\n \"acc_norm_stderr\": 0.0292418838696288\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\": 0.33793103448275863,\n \"acc_stderr\": 0.039417076320648906,\n\ \ \"acc_norm\": 0.33793103448275863,\n \"acc_norm_stderr\": 0.039417076320648906\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.24867724867724866,\n \"acc_stderr\": 0.02226181769240019,\n \"\ acc_norm\": 0.24867724867724866,\n \"acc_norm_stderr\": 0.02226181769240019\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.18253968253968253,\n\ \ \"acc_stderr\": 0.03455071019102146,\n \"acc_norm\": 0.18253968253968253,\n\ \ \"acc_norm_stderr\": 0.03455071019102146\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.19,\n \"acc_stderr\": 0.039427724440366234,\n \ \ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.039427724440366234\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.3064516129032258,\n \"acc_stderr\": 0.026226485652553883,\n \"\ acc_norm\": 0.3064516129032258,\n \"acc_norm_stderr\": 0.026226485652553883\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.2561576354679803,\n \"acc_stderr\": 0.030712730070982592,\n \"\ acc_norm\": 0.2561576354679803,\n \"acc_norm_stderr\": 0.030712730070982592\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.21818181818181817,\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\"\ : 0.3434343434343434,\n \"acc_stderr\": 0.033832012232444426,\n \"\ acc_norm\": 0.3434343434343434,\n \"acc_norm_stderr\": 0.033832012232444426\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.37823834196891193,\n \"acc_stderr\": 0.034998072761933396,\n\ \ \"acc_norm\": 0.37823834196891193,\n \"acc_norm_stderr\": 0.034998072761933396\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.35128205128205126,\n \"acc_stderr\": 0.024203665177902803,\n\ \ \"acc_norm\": 0.35128205128205126,\n \"acc_norm_stderr\": 0.024203665177902803\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2518518518518518,\n \"acc_stderr\": 0.02646611753895991,\n \ \ \"acc_norm\": 0.2518518518518518,\n \"acc_norm_stderr\": 0.02646611753895991\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.24369747899159663,\n \"acc_stderr\": 0.027886828078380565,\n\ \ \"acc_norm\": 0.24369747899159663,\n \"acc_norm_stderr\": 0.027886828078380565\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.037345356767871984,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.037345356767871984\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.3211009174311927,\n \"acc_stderr\": 0.020018149772733744,\n \"\ acc_norm\": 0.3211009174311927,\n \"acc_norm_stderr\": 0.020018149772733744\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4675925925925926,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.4675925925925926,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.2647058823529412,\n \"acc_stderr\": 0.03096451792692341,\n \"\ acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.03096451792692341\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.2320675105485232,\n \"acc_stderr\": 0.027479744550808514,\n \ \ \"acc_norm\": 0.2320675105485232,\n \"acc_norm_stderr\": 0.027479744550808514\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.23766816143497757,\n\ \ \"acc_stderr\": 0.02856807946471428,\n \"acc_norm\": 0.23766816143497757,\n\ \ \"acc_norm_stderr\": 0.02856807946471428\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.1984732824427481,\n \"acc_stderr\": 0.03498149385462472,\n\ \ \"acc_norm\": 0.1984732824427481,\n \"acc_norm_stderr\": 0.03498149385462472\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.2892561983471074,\n \"acc_stderr\": 0.04139112727635464,\n \"\ acc_norm\": 0.2892561983471074,\n \"acc_norm_stderr\": 0.04139112727635464\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.26993865030674846,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.26993865030674846,\n \"acc_norm_stderr\": 0.034878251684978906\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.23214285714285715,\n\ \ \"acc_stderr\": 0.04007341809755806,\n \"acc_norm\": 0.23214285714285715,\n\ \ \"acc_norm_stderr\": 0.04007341809755806\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.23300970873786409,\n \"acc_stderr\": 0.041858325989283136,\n\ \ \"acc_norm\": 0.23300970873786409,\n \"acc_norm_stderr\": 0.041858325989283136\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.19230769230769232,\n\ \ \"acc_stderr\": 0.0258192332564837,\n \"acc_norm\": 0.19230769230769232,\n\ \ \"acc_norm_stderr\": 0.0258192332564837\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\": 0.2796934865900383,\n\ \ \"acc_stderr\": 0.016050792148036546,\n \"acc_norm\": 0.2796934865900383,\n\ \ \"acc_norm_stderr\": 0.016050792148036546\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.23410404624277456,\n \"acc_stderr\": 0.02279711027807114,\n\ \ \"acc_norm\": 0.23410404624277456,\n \"acc_norm_stderr\": 0.02279711027807114\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.24183006535947713,\n \"acc_stderr\": 0.024518195641879334,\n\ \ \"acc_norm\": 0.24183006535947713,\n \"acc_norm_stderr\": 0.024518195641879334\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.26366559485530544,\n\ \ \"acc_stderr\": 0.02502553850053234,\n \"acc_norm\": 0.26366559485530544,\n\ \ \"acc_norm_stderr\": 0.02502553850053234\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.023132376234543332,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.023132376234543332\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.2801418439716312,\n \"acc_stderr\": 0.026789172351140245,\n \ \ \"acc_norm\": 0.2801418439716312,\n \"acc_norm_stderr\": 0.026789172351140245\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.23663624511082137,\n\ \ \"acc_stderr\": 0.010855137351572735,\n \"acc_norm\": 0.23663624511082137,\n\ \ \"acc_norm_stderr\": 0.010855137351572735\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.4338235294117647,\n \"acc_stderr\": 0.030105636570016643,\n\ \ \"acc_norm\": 0.4338235294117647,\n \"acc_norm_stderr\": 0.030105636570016643\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.2647058823529412,\n \"acc_stderr\": 0.017848089574913226,\n \ \ \"acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.017848089574913226\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.17272727272727273,\n\ \ \"acc_stderr\": 0.0362069183392922,\n \"acc_norm\": 0.17272727272727273,\n\ \ \"acc_norm_stderr\": 0.0362069183392922\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.2163265306122449,\n \"acc_stderr\": 0.026358916334904035,\n\ \ \"acc_norm\": 0.2163265306122449,\n \"acc_norm_stderr\": 0.026358916334904035\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.23880597014925373,\n\ \ \"acc_stderr\": 0.030147775935409217,\n \"acc_norm\": 0.23880597014925373,\n\ \ \"acc_norm_stderr\": 0.030147775935409217\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909281,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909281\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.1927710843373494,\n\ \ \"acc_stderr\": 0.03070982405056527,\n \"acc_norm\": 0.1927710843373494,\n\ \ \"acc_norm_stderr\": 0.03070982405056527\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.23976608187134502,\n \"acc_stderr\": 0.03274485211946956,\n\ \ \"acc_norm\": 0.23976608187134502,\n \"acc_norm_stderr\": 0.03274485211946956\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.25091799265605874,\n\ \ \"mc1_stderr\": 0.015176985027707687,\n \"mc2\": 0.38841425251899087,\n\ \ \"mc2_stderr\": 0.014859033830490542\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.49013417521704816,\n \"acc_stderr\": 0.014049749833367589\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.02122820318423048,\n \ \ \"acc_stderr\": 0.003970449129848635\n }\n}\n```" repo_url: https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M 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_12T07_34_24.161560 path: - '**/details_harness|arc:challenge|25_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-12T07-34-24.161560.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|gsm8k|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hellaswag|10_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-12T07-34-24.161560.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-management|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T07-34-24.161560.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|truthfulqa:mc|0_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-12T07-34-24.161560.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_12T07_34_24.161560 path: - '**/details_harness|winogrande|5_2023-12-12T07-34-24.161560.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-12T07-34-24.161560.parquet' - config_name: results data_files: - split: 2023_12_12T07_34_24.161560 path: - results_2023-12-12T07-34-24.161560.parquet - split: latest path: - results_2023-12-12T07-34-24.161560.parquet --- # Dataset Card for Evaluation run of xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M  Dataset automatically created during the evaluation run of model [xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M](https://huggingface.co/xzuyn/GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M) 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_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-12T07:34:24.161560](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__GPT-2-SlimOrcaDeduped-airoboros-3.1-MetaMathQA-SFT-124M/blob/main/results_2023-12-12T07-34-24.161560.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": 0.2574568669647554, "acc_stderr": 0.03077370055460631, "acc_norm": 0.258555233951132, "acc_norm_stderr": 0.031529415596877046, "mc1": 0.25091799265605874, "mc1_stderr": 0.015176985027707687, "mc2": 0.38841425251899087, "mc2_stderr": 0.014859033830490542 }, "harness|arc:challenge|25": { "acc": 0.1945392491467577, "acc_stderr": 0.011567709174648728, "acc_norm": 0.24573378839590443, "acc_norm_stderr": 0.012581033453730113 }, "harness|hellaswag|10": { "acc": 0.2842063333997212, "acc_stderr": 0.004501137895230712, "acc_norm": 0.29426409081856203, "acc_norm_stderr": 0.00454779896412667 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2518518518518518, "acc_stderr": 0.037498507091740234, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.037498507091740234 }, "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": 0.22, "acc_stderr": 0.0416333199893227, "acc_norm": 0.22, "acc_norm_stderr": 0.0416333199893227 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2, "acc_stderr": 0.02461829819586651, "acc_norm": 0.2, "acc_norm_stderr": 0.02461829819586651 }, "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": 0.23, "acc_stderr": 0.04229525846816505, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816505 }, "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": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.26011560693641617, "acc_stderr": 0.03345036916788992, "acc_norm": 0.26011560693641617, "acc_norm_stderr": 0.03345036916788992 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.23529411764705882, "acc_stderr": 0.04220773659171453, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.04220773659171453 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.15, "acc_stderr": 0.035887028128263734, "acc_norm": 0.15, "acc_norm_stderr": 0.035887028128263734 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2765957446808511, "acc_stderr": 0.0292418838696288, "acc_norm": 0.2765957446808511, "acc_norm_stderr": 0.0292418838696288 }, "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": 0.33793103448275863, "acc_stderr": 0.039417076320648906, "acc_norm": 0.33793103448275863, "acc_norm_stderr": 0.039417076320648906 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24867724867724866, "acc_stderr": 0.02226181769240019, "acc_norm": 0.24867724867724866, "acc_norm_stderr": 0.02226181769240019 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.18253968253968253, "acc_stderr": 0.03455071019102146, "acc_norm": 0.18253968253968253, "acc_norm_stderr": 0.03455071019102146 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.19, "acc_stderr": 0.039427724440366234, "acc_norm": 0.19, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3064516129032258, "acc_stderr": 0.026226485652553883, "acc_norm": 0.3064516129032258, "acc_norm_stderr": 0.026226485652553883 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2561576354679803, "acc_stderr": 0.030712730070982592, "acc_norm": 0.2561576354679803, "acc_norm_stderr": 0.030712730070982592 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.3434343434343434, "acc_stderr": 0.033832012232444426, "acc_norm": 0.3434343434343434, "acc_norm_stderr": 0.033832012232444426 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.37823834196891193, "acc_stderr": 0.034998072761933396, "acc_norm": 0.37823834196891193, "acc_norm_stderr": 0.034998072761933396 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.35128205128205126, "acc_stderr": 0.024203665177902803, "acc_norm": 0.35128205128205126, "acc_norm_stderr": 0.024203665177902803 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2518518518518518, "acc_stderr": 0.02646611753895991, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.02646611753895991 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.24369747899159663, "acc_stderr": 0.027886828078380565, "acc_norm": 0.24369747899159663, "acc_norm_stderr": 0.027886828078380565 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.2980132450331126, "acc_stderr": 0.037345356767871984, "acc_norm": 0.2980132450331126, "acc_norm_stderr": 0.037345356767871984 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.3211009174311927, "acc_stderr": 0.020018149772733744, "acc_norm": 0.3211009174311927, "acc_norm_stderr": 0.020018149772733744 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4675925925925926, "acc_stderr": 0.03402801581358966, "acc_norm": 0.4675925925925926, "acc_norm_stderr": 0.03402801581358966 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.2647058823529412, "acc_stderr": 0.03096451792692341, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.03096451792692341 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.2320675105485232, "acc_stderr": 0.027479744550808514, "acc_norm": 0.2320675105485232, "acc_norm_stderr": 0.027479744550808514 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.23766816143497757, "acc_stderr": 0.02856807946471428, "acc_norm": 0.23766816143497757, "acc_norm_stderr": 0.02856807946471428 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.1984732824427481, "acc_stderr": 0.03498149385462472, "acc_norm": 0.1984732824427481, "acc_norm_stderr": 0.03498149385462472 }, "harness|hendrycksTest-international_law|5": { "acc": 0.2892561983471074, "acc_stderr": 0.04139112727635464, "acc_norm": 0.2892561983471074, "acc_norm_stderr": 0.04139112727635464 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.25, "acc_stderr": 0.04186091791394607, "acc_norm": 0.25, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.26993865030674846, "acc_stderr": 0.034878251684978906, "acc_norm": 0.26993865030674846, "acc_norm_stderr": 0.034878251684978906 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.23214285714285715, "acc_stderr": 0.04007341809755806, "acc_norm": 0.23214285714285715, "acc_norm_stderr": 0.04007341809755806 }, "harness|hendrycksTest-management|5": { "acc": 0.23300970873786409, "acc_stderr": 0.041858325989283136, "acc_norm": 0.23300970873786409, "acc_norm_stderr": 0.041858325989283136 }, "harness|hendrycksTest-marketing|5": { "acc": 0.19230769230769232, "acc_stderr": 0.0258192332564837, "acc_norm": 0.19230769230769232, "acc_norm_stderr": 0.0258192332564837 }, "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": 0.2796934865900383, "acc_stderr": 0.016050792148036546, "acc_norm": 0.2796934865900383, "acc_norm_stderr": 0.016050792148036546 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.23410404624277456, "acc_stderr": 0.02279711027807114, "acc_norm": 0.23410404624277456, "acc_norm_stderr": 0.02279711027807114 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.24183006535947713, "acc_stderr": 0.024518195641879334, "acc_norm": 0.24183006535947713, "acc_norm_stderr": 0.024518195641879334 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.26366559485530544, "acc_stderr": 0.02502553850053234, "acc_norm": 0.26366559485530544, "acc_norm_stderr": 0.02502553850053234 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.2222222222222222, "acc_stderr": 0.023132376234543332, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.023132376234543332 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.2801418439716312, "acc_stderr": 0.026789172351140245, "acc_norm": 0.2801418439716312, "acc_norm_stderr": 0.026789172351140245 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.23663624511082137, "acc_stderr": 0.010855137351572735, "acc_norm": 0.23663624511082137, "acc_norm_stderr": 0.010855137351572735 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.4338235294117647, "acc_stderr": 0.030105636570016643, "acc_norm": 0.4338235294117647, "acc_norm_stderr": 0.030105636570016643 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.2647058823529412, "acc_stderr": 0.017848089574913226, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.017848089574913226 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.17272727272727273, "acc_stderr": 0.0362069183392922, "acc_norm": 0.17272727272727273, "acc_norm_stderr": 0.0362069183392922 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.2163265306122449, "acc_stderr": 0.026358916334904035, "acc_norm": 0.2163265306122449, "acc_norm_stderr": 0.026358916334904035 }, "harness|hendrycksTest-sociology|5": { "acc": 0.23880597014925373, "acc_stderr": 0.030147775935409217, "acc_norm": 0.23880597014925373, "acc_norm_stderr": 0.030147775935409217 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.24, "acc_stderr": 0.04292346959909281, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909281 }, "harness|hendrycksTest-virology|5": { "acc": 0.1927710843373494, "acc_stderr": 0.03070982405056527, "acc_norm": 0.1927710843373494, "acc_norm_stderr": 0.03070982405056527 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.23976608187134502, "acc_stderr": 0.03274485211946956, "acc_norm": 0.23976608187134502, "acc_norm_stderr": 0.03274485211946956 }, "harness|truthfulqa:mc|0": { "mc1": 0.25091799265605874, "mc1_stderr": 0.015176985027707687, "mc2": 0.38841425251899087, "mc2_stderr": 0.014859033830490542 }, "harness|winogrande|5": { "acc": 0.49013417521704816, "acc_stderr": 0.014049749833367589 }, "harness|gsm8k|5": { "acc": 0.02122820318423048, "acc_stderr": 0.003970449129848635 } } ``` ## 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]

bys2058/mydataset_bai

--- dataset_info: features: - name: image dtype: image - name: image_caption dtype: string splits: - name: train num_bytes: 672992285.125 num_examples: 1375 download_size: 672547372 dataset_size: 672992285.125 --- # Dataset Card for "mydataset_bai" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

deivsu/2ne1CL

--- license: openrail ---

joey234/mmlu-human_sexuality-original-neg

--- 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 splits: - name: test num_bytes: 3185.297709923664 num_examples: 13 download_size: 6364 dataset_size: 3185.297709923664 --- # Dataset Card for "mmlu-human_sexuality-original-neg" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ciempiess/voxforge_spanish

--- license: gpl-3.0 ---

wmt/wmt16

--- annotations_creators: - no-annotation language_creators: - found language: - cs - de - en - fi - ro - ru - tr license: - unknown multilinguality: - translation size_categories: - 10M<n<100M source_datasets: - extended|europarl_bilingual - extended|news_commentary - extended|setimes - extended|un_multi task_categories: - translation task_ids: [] paperswithcode_id: wmt-2016 pretty_name: WMT16 dataset_info: - config_name: cs-en features: - name: translation dtype: translation: languages: - cs - en splits: - name: train num_bytes: 295995226 num_examples: 997240 - name: validation num_bytes: 572195 num_examples: 2656 - name: test num_bytes: 707862 num_examples: 2999 download_size: 178250444 dataset_size: 297275283 - config_name: de-en features: - name: translation dtype: translation: languages: - de - en splits: - name: train num_bytes: 1373099816 num_examples: 4548885 - name: validation num_bytes: 522981 num_examples: 2169 - name: test num_bytes: 735508 num_examples: 2999 download_size: 827152589 dataset_size: 1374358305 - config_name: fi-en features: - name: translation dtype: translation: languages: - fi - en splits: - name: train num_bytes: 605145153 num_examples: 2073394 - name: validation num_bytes: 306327 num_examples: 1370 - name: test num_bytes: 1410507 num_examples: 6000 download_size: 348306427 dataset_size: 606861987 - config_name: ro-en features: - name: translation dtype: translation: languages: - ro - en splits: - name: train num_bytes: 188287711 num_examples: 610320 - name: validation num_bytes: 561791 num_examples: 1999 - name: test num_bytes: 539208 num_examples: 1999 download_size: 108584039 dataset_size: 189388710 - config_name: ru-en features: - name: translation dtype: translation: languages: - ru - en splits: - name: train num_bytes: 448322024 num_examples: 1516162 - name: validation num_bytes: 955964 num_examples: 2818 - name: test num_bytes: 1050669 num_examples: 2998 download_size: 231557371 dataset_size: 450328657 - config_name: tr-en features: - name: translation dtype: translation: languages: - tr - en splits: - name: train num_bytes: 60416449 num_examples: 205756 - name: validation num_bytes: 240642 num_examples: 1001 - name: test num_bytes: 732428 num_examples: 3000 download_size: 37389436 dataset_size: 61389519 configs: - config_name: cs-en data_files: - split: train path: cs-en/train-* - split: validation path: cs-en/validation-* - split: test path: cs-en/test-* - config_name: de-en data_files: - split: train path: de-en/train-* - split: validation path: de-en/validation-* - split: test path: de-en/test-* - config_name: fi-en data_files: - split: train path: fi-en/train-* - split: validation path: fi-en/validation-* - split: test path: fi-en/test-* - config_name: ro-en data_files: - split: train path: ro-en/train-* - split: validation path: ro-en/validation-* - split: test path: ro-en/test-* - config_name: ru-en data_files: - split: train path: ru-en/train-* - split: validation path: ru-en/validation-* - split: test path: ru-en/test-* - config_name: tr-en data_files: - split: train path: tr-en/train-* - split: validation path: tr-en/validation-* - split: test path: tr-en/test-* --- # Dataset Card for "wmt16" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [http://www.statmt.org/wmt16/translation-task.html](http://www.statmt.org/wmt16/translation-task.html) - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of downloaded dataset files:** 1.69 GB - **Size of the generated dataset:** 297.28 MB - **Total amount of disk used:** 1.99 GB ### Dataset Summary <div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400"> <p><b>Warning:</b> There are issues with the Common Crawl corpus data (<a href="https://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz">training-parallel-commoncrawl.tgz</a>):</p> <ul> <li>Non-English files contain many English sentences.</li> <li>Their "parallel" sentences in English are not aligned: they are uncorrelated with their counterpart.</li> </ul> <p>We have contacted the WMT organizers, and in response, they have indicated that they do not have plans to update the Common Crawl corpus data. Their rationale pertains to the expectation that such data has been superseded, primarily by CCMatrix, and to some extent, by ParaCrawl datasets.</p> </div> Translation dataset based on the data from statmt.org. Versions exist for different years using a combination of data sources. The base `wmt` allows you to create a custom dataset by choosing your own data/language pair. This can be done as follows: ```python from datasets import inspect_dataset, load_dataset_builder inspect_dataset("wmt16", "path/to/scripts") builder = load_dataset_builder( "path/to/scripts/wmt_utils.py", language_pair=("fr", "de"), subsets={ datasets.Split.TRAIN: ["commoncrawl_frde"], datasets.Split.VALIDATION: ["euelections_dev2019"], }, ) # Standard version builder.download_and_prepare() ds = builder.as_dataset() # Streamable version ds = builder.as_streaming_dataset() ``` ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### cs-en - **Size of downloaded dataset files:** 1.69 GB - **Size of the generated dataset:** 297.28 MB - **Total amount of disk used:** 1.99 GB An example of 'validation' looks as follows. ``` ``` ### Data Fields The data fields are the same among all splits. #### cs-en - `translation`: a multilingual `string` variable, with possible languages including `cs`, `en`. ### Data Splits |name |train |validation|test| |-----|-----:|---------:|---:| |cs-en|997240| 2656|2999| ## 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{bojar-EtAl:2016:WMT1, author = {Bojar, Ond {r}ej and Chatterjee, Rajen and Federmann, Christian and Graham, Yvette and Haddow, Barry and Huck, Matthias and Jimeno Yepes, Antonio and Koehn, Philipp and Logacheva, Varvara and Monz, Christof and Negri, Matteo and Neveol, Aurelie and Neves, Mariana and Popel, Martin and Post, Matt and Rubino, Raphael and Scarton, Carolina and Specia, Lucia and Turchi, Marco and Verspoor, Karin and Zampieri, Marcos}, title = {Findings of the 2016 Conference on Machine Translation}, booktitle = {Proceedings of the First Conference on Machine Translation}, month = {August}, year = {2016}, address = {Berlin, Germany}, publisher = {Association for Computational Linguistics}, pages = {131--198}, url = {http://www.aclweb.org/anthology/W/W16/W16-2301} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

TinyPixel/lima_2

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 2960580 num_examples: 1030 download_size: 1703604 dataset_size: 2960580 --- # Dataset Card for "lima_2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

kbharat7/DogChestXrayDatasetNew

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 444263783.625 num_examples: 1395 download_size: 444252328 dataset_size: 444263783.625 --- # Dataset Card for "DogChestXrayDatasetNew" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

autoevaluate/autoeval-staging-eval-squad_v2-squad_v2-76c05b-14906070

--- type: predictions tags: - autotrain - evaluation datasets: - squad_v2 eval_info: task: extractive_question_answering model: deepset/roberta-base-squad2-covid metrics: ['bertscore'] dataset_name: squad_v2 dataset_config: squad_v2 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: deepset/roberta-base-squad2-covid * Dataset: squad_v2 * Config: squad_v2 * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@nonchalant-nagavalli](https://huggingface.co/nonchalant-nagavalli) for evaluating this model.

UsmanMalikLearn/Pak-Legal-Llama2

--- dataset_info: features: - name: transformed_text dtype: string splits: - name: train num_bytes: 857655 num_examples: 2229 download_size: 369985 dataset_size: 857655 configs: - config_name: default data_files: - split: train path: data/train-* ---

youlive789/sales

--- dataset_info: features: - name: original_image dtype: image - name: edited_image dtype: image - name: edit_promt dtype: string splits: - name: train num_bytes: 111237824.0 num_examples: 140 download_size: 111236059 dataset_size: 111237824.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

Techatach/mini-platypus

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 4186564 num_examples: 1000 download_size: 2245921 dataset_size: 4186564 configs: - config_name: default data_files: - split: train path: data/train-* ---

tyzhu/squad_qa_context_v5_full_recite_full_passage_random_permute_rerun_8

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 6222942.0 num_examples: 2385 - name: validation num_bytes: 808532 num_examples: 300 download_size: 1374285 dataset_size: 7031474.0 --- # Dataset Card for "squad_qa_context_v5_full_recite_full_passage_random_permute_rerun_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Xokito/datasethevelyn

--- license: openrail ---

CyberHarem/le_malin_azurlane

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of le_malin/ル・マラン/恶毒 (Azur Lane) This is the dataset of le_malin/ル・マラン/恶毒 (Azur Lane), containing 500 images and their tags. The core tags of this character are `long_hair, blue_eyes, white_hair, very_long_hair, bangs, breasts, small_breasts, animal_ears, rabbit_ears, braid, twin_braids, fake_animal_ears, hair_bun, double_bun, animal_ear_fluff`, 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 | 933.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 500 | 419.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 1378 | 988.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 500 | 767.52 MiB | [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1378 | 1.52 GiB | [Download](https://huggingface.co/datasets/CyberHarem/le_malin_azurlane/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/le_malin_azurlane', 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 | 7 | ![](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, choker, criss-cross_halter, solo, white_dress, white_rose, bare_shoulders, blush, hair_between_eyes, looking_at_viewer, sleeveless_dress, collarbone, sidelocks, bare_arms, parted_lips, barefoot, grey_hair, hand_up, on_back | | 1 | 17 | ![](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, solo, white_pantyhose, sidelocks, white_dress, hair_between_eyes, looking_at_viewer, long_sleeves, symbol-shaped_pupils, blush, navel, detached_sleeves, parted_lips, sitting, tutu | | 2 | 13 | ![](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, solo, white_dress, white_pantyhose, hair_between_eyes, long_sleeves, sidelocks, holding_sword, looking_at_viewer, thighband_pantyhose, closed_mouth, rapier, simple_background, underboob_cutout, blush, white_background, cape, hair_bow, full_body, pocket_watch, ribbon | | 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, looking_at_viewer, navel, nipples, nude, simple_background, solo, +_+, hair_between_eyes, blush, collarbone, hair_ribbon, loli, open_mouth, white_background, anus, clitoris, closed_mouth, spread_pussy, standing, symbol-shaped_pupils, uncensored | | 4 | 18 | ![](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, bare_shoulders, solo, looking_at_viewer, white_bikini, symbol-shaped_pupils, sidelocks, barefoot, blush, bare_legs, headphones_around_neck, hammock, arm_garter, on_back, hair_between_eyes, navel, ass, feet, thighs, purple_flower, stomach | | 5 | 9 | ![](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, looking_at_viewer, official_alternate_costume, playboy_bunny, solo, white_leotard, white_pantyhose, wrist_cuffs, blush, simple_background, white_background, choker, sitting, +_+, closed_mouth, thigh_strap, twintails, hairband, rabbit_tail | | 6 | 10 | ![](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, ass, looking_at_viewer, official_alternate_costume, playboy_bunny, rabbit_tail, solo, white_leotard, white_pantyhose, from_behind, hairband, looking_back, +_+, simple_background, thigh_strap, white_background, wrist_cuffs, blush, parted_lips, sideboob, thighs | | 7 | 7 | ![](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, covered_navel, looking_at_viewer, official_alternate_costume, playboy_bunny, simple_background, solo, white_leotard, white_pantyhose, blush, thigh_strap, white_background, wrist_cuffs, choker, closed_mouth, highleg_leotard, +_+, thighs, twintails | | 8 | 5 | ![](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, looking_at_viewer, official_alternate_costume, playboy_bunny, rabbit_tail, solo, white_leotard, white_pantyhose, +_+, ass, from_behind, looking_back, no_shoes, wrist_cuffs, couch, blush, full_body, low_twin_braids, sideboob, thigh_strap, wariza, white_hairband | | 9 | 16 | ![](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, hetero, solo_focus, penis, sex, 1boy, blush, censored, nipples, +_+, pussy, vaginal, open_mouth, pantyhose, official_alternate_costume, straddling, loli, looking_at_viewer, playboy_bunny, simple_background, spread_legs, clothed_female_nude_male, girl_on_top, white_leotard, crotchless, dark-skinned_male, interracial, navel, wrist_cuffs | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | +_+ | 1girl | choker | criss-cross_halter | solo | white_dress | white_rose | bare_shoulders | blush | hair_between_eyes | looking_at_viewer | sleeveless_dress | collarbone | sidelocks | bare_arms | parted_lips | barefoot | grey_hair | hand_up | on_back | white_pantyhose | long_sleeves | symbol-shaped_pupils | navel | detached_sleeves | sitting | tutu | holding_sword | thighband_pantyhose | closed_mouth | rapier | simple_background | underboob_cutout | white_background | cape | hair_bow | full_body | pocket_watch | ribbon | nipples | nude | hair_ribbon | loli | open_mouth | anus | clitoris | spread_pussy | standing | uncensored | white_bikini | bare_legs | headphones_around_neck | hammock | arm_garter | ass | feet | thighs | purple_flower | stomach | official_alternate_costume | playboy_bunny | white_leotard | wrist_cuffs | thigh_strap | twintails | hairband | rabbit_tail | from_behind | looking_back | sideboob | covered_navel | highleg_leotard | no_shoes | couch | low_twin_braids | wariza | white_hairband | hetero | solo_focus | penis | sex | 1boy | censored | pussy | vaginal | pantyhose | straddling | spread_legs | clothed_female_nude_male | girl_on_top | crotchless | dark-skinned_male | interracial | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------|:--------|:---------|:---------------------|:-------|:--------------|:-------------|:-----------------|:--------|:--------------------|:--------------------|:-------------------|:-------------|:------------|:------------|:--------------|:-----------|:------------|:----------|:----------|:------------------|:---------------|:-----------------------|:--------|:-------------------|:----------|:-------|:----------------|:----------------------|:---------------|:---------|:--------------------|:-------------------|:-------------------|:-------|:-----------|:------------|:---------------|:---------|:----------|:-------|:--------------|:-------|:-------------|:-------|:-----------|:---------------|:-----------|:-------------|:---------------|:------------|:-------------------------|:----------|:-------------|:------|:-------|:---------|:----------------|:----------|:-----------------------------|:----------------|:----------------|:--------------|:--------------|:------------|:-----------|:--------------|:--------------|:---------------|:-----------|:----------------|:------------------|:-----------|:--------|:------------------|:---------|:-----------------|:---------|:-------------|:--------|:------|:-------|:-----------|:--------|:----------|:------------|:-------------|:--------------|:---------------------------|:--------------|:-------------|:--------------------|:--------------| | 0 | 7 | ![](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 | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 17 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 13 | ![](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 | 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 | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 18 | ![](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 | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 9 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | 6 | 10 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | 7 | 7 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | 8 | 5 | ![](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 | X | | | | | | | | | | | | | | | | | | 9 | 16 | ![](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 | 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davisonye/cg_pad_mai_dav_1

--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': maize '1': paddy_rice '2': unknown splits: - name: train num_bytes: 5026074267.1 num_examples: 1683 - name: validation num_bytes: 308905569.0 num_examples: 89 - name: test num_bytes: 330351357.0 num_examples: 96 download_size: 6239113776 dataset_size: 5665331193.1 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

autoevaluate/autoeval-eval-futin__guess-en-6f8c6a-2012266598

--- type: predictions tags: - autotrain - evaluation datasets: - futin/guess eval_info: task: text_zero_shot_classification model: facebook/opt-2.7b metrics: [] dataset_name: futin/guess dataset_config: en dataset_split: test col_mapping: text: text classes: classes target: target --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Zero-Shot Text Classification * Model: facebook/opt-2.7b * Dataset: futin/guess * Config: en * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@futin](https://huggingface.co/futin) for evaluating this model.

ctang/1k_deontology_train_llama2

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 679786 num_examples: 1000 download_size: 84465 dataset_size: 679786 configs: - config_name: default data_files: - split: train path: data/train-* ---

HuggingFaceH4/ifeval

--- license: apache-2.0 --- # Dataset Card for IFEval  This dataset contains the prompts used in Google's [Instruction-Following Evaluation for Large Language Models](https://arxiv.org/abs/2311.07911). You can find the original source data and evaluation code [here](https://github.com/google-research/google-research/tree/master/instruction_following_eval). ## 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_porkorbeef__Llama-2-13b-sf

--- pretty_name: Evaluation run of porkorbeef/Llama-2-13b-sf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [porkorbeef/Llama-2-13b-sf](https://huggingface.co/porkorbeef/Llama-2-13b-sf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the 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_porkorbeef__Llama-2-13b-sf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-19T10:54:43.878914](https://huggingface.co/datasets/open-llm-leaderboard/details_porkorbeef__Llama-2-13b-sf/blob/main/results_2023-10-19T10-54-43.878914.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\": 0.0,\n \"\ em_stderr\": 0.0,\n \"f1\": 2.3070469798657717e-05,\n \"f1_stderr\"\ : 1.0056123859027576e-05,\n \"acc\": 0.2517758484609313,\n \"acc_stderr\"\ : 0.0070260655734579345\n },\n \"harness|drop|3\": {\n \"em\": 0.0,\n\ \ \"em_stderr\": 0.0,\n \"f1\": 2.3070469798657717e-05,\n \"\ f1_stderr\": 1.0056123859027576e-05\n },\n \"harness|gsm8k|5\": {\n \ \ \"acc\": 0.0,\n \"acc_stderr\": 0.0\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.5035516969218626,\n \"acc_stderr\": 0.014052131146915869\n\ \ }\n}\n```" repo_url: https://huggingface.co/porkorbeef/Llama-2-13b-sf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_drop_3 data_files: - split: 2023_10_19T10_54_43.878914 path: - '**/details_harness|drop|3_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-19T10-54-43.878914.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_19T10_54_43.878914 path: - '**/details_harness|gsm8k|5_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-19T10-54-43.878914.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_19T10_54_43.878914 path: - '**/details_harness|winogrande|5_2023-10-19T10-54-43.878914.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-19T10-54-43.878914.parquet' - config_name: results data_files: - split: 2023_10_19T10_54_43.878914 path: - results_2023-10-19T10-54-43.878914.parquet - split: latest path: - results_2023-10-19T10-54-43.878914.parquet --- # Dataset Card for Evaluation run of porkorbeef/Llama-2-13b-sf ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/porkorbeef/Llama-2-13b-sf - **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 [porkorbeef/Llama-2-13b-sf](https://huggingface.co/porkorbeef/Llama-2-13b-sf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the 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_porkorbeef__Llama-2-13b-sf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-19T10:54:43.878914](https://huggingface.co/datasets/open-llm-leaderboard/details_porkorbeef__Llama-2-13b-sf/blob/main/results_2023-10-19T10-54-43.878914.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": 0.0, "em_stderr": 0.0, "f1": 2.3070469798657717e-05, "f1_stderr": 1.0056123859027576e-05, "acc": 0.2517758484609313, "acc_stderr": 0.0070260655734579345 }, "harness|drop|3": { "em": 0.0, "em_stderr": 0.0, "f1": 2.3070469798657717e-05, "f1_stderr": 1.0056123859027576e-05 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness|winogrande|5": { "acc": 0.5035516969218626, "acc_stderr": 0.014052131146915869 } } ``` ### 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]

kkcosmos/instagram-images-with-captions

--- license: unknown dataset_info: features: - name: image dtype: image - name: item_id dtype: int64 - name: image_path dtype: string - name: caption dtype: string splits: - name: train num_bytes: 3516512787.609302 num_examples: 28360 - name: test num_bytes: 391305063.2386981 num_examples: 3152 download_size: 0 dataset_size: 3907817850.848 ---

bhjhk/samino11

--- license: bigscience-bloom-rail-1.0 ---

AdapterOcean/med_alpaca_standardized_cluster_68_std

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 16970130 num_examples: 24531 download_size: 8602932 dataset_size: 16970130 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_68_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ivanfdzm/Arq-Style

--- license: afl-3.0 ---

Seanxh/twitter_dataset_1713173437

--- 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: 25981 num_examples: 64 download_size: 15681 dataset_size: 25981 configs: - config_name: default data_files: - split: train path: data/train-* ---

chirp-watai/audio_dataset

--- task_categories: - zero-shot-classification tags: - audio - sound pretty_name: audio size_categories: - 1K<n<10K --- # Audio Dataset This dataset consists of audio data for the following categories: * Coughing * Running water * Toilet flush * Other sounds Although this data is unbalanced, data augmentations can be added to process the data for audio classification. The file structure looks as follows: \- audio/        \- coughing/        \- toilet_flush/        \- running_water/        \- other_1/        \- other_2/

AdapterOcean/med_alpaca_standardized_cluster_10_std

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 18079246 num_examples: 25458 download_size: 9399571 dataset_size: 18079246 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_10_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Capsekai/Badge_crafts

--- license: creativeml-openrail-m task_categories: - text-to-image - image-classification language: - en tags: - badges - crafts pretty_name: Badge Craft Dataset size_categories: - 1K<n<10K --- # Do what you will with the data this is old photos of crafts I used to make - just abide by the liscence above and you good to go!

dlwh/Multi_Legal_Pile

--- license: cc-by-4.0 ---

luckeciano/hermes-features-ultrafeedback

--- configs: - config_name: default data_files: - split: train path: "train.csv" - split: valid path: "eval.csv" - split: test path: "test.csv" --- --- license: apache-2.0 ---

AIGym/TextbookChapters

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1013875541 num_examples: 77932 download_size: 504483603 dataset_size: 1013875541 configs: - config_name: default data_files: - split: train path: data/train-* ---

lshowway/wikipedia.reorder.svo.de

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 2385745587 num_examples: 1137317 download_size: 1063402086 dataset_size: 2385745587 --- # Dataset Card for "wikipedia.reorder.svo.de" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

pvduy/exp_dpo_1

--- 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 splits: - name: train num_bytes: 120210099 num_examples: 14313 - name: test num_bytes: 4538037 num_examples: 750 download_size: 64945705 dataset_size: 124748136 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

GVJahnavi/Crops_set

--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot '1': Corn_(maize)___Common_rust_ '2': Corn_(maize)___Northern_Leaf_Blight '3': Corn_(maize)___healthy '4': Pepper,_bell___Bacterial_spot '5': Pepper,_bell___healthy '6': Potato___Early_blight '7': Potato___Late_blight '8': Potato___healthy '9': Soybean___healthy '10': Tomato___Bacterial_spot '11': Tomato___Early_blight '12': Tomato___Late_blight '13': Tomato___Leaf_Mold '14': Tomato___Septoria_leaf_spot '15': Tomato___Spider_mites Two-spotted_spider_mite '16': Tomato___Target_Spot '17': Tomato___Tomato_Yellow_Leaf_Curl_Virus '18': Tomato___Tomato_mosaic_virus '19': Tomato___healthy splits: - name: train num_bytes: 381142501.808 num_examples: 25384 - name: test num_bytes: 93073910.262 num_examples: 6346 download_size: 514893426 dataset_size: 474216412.07000005 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

benayas/sst2_llm_v0

--- dataset_info: features: - name: sentence dtype: string - name: label dtype: class_label: names: '0': negative '1': positive - name: idx dtype: int32 - name: eval_text dtype: string - name: text dtype: string splits: - name: train num_bytes: 67924009 num_examples: 67349 - name: validation num_bytes: 1016356 num_examples: 872 - name: test num_bytes: 2104899 num_examples: 1821 download_size: 13965924 dataset_size: 71045264 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

seidouz/Diabetes

--- license: openrail --- Simulated dataset for the project https://github.com/bitDalei/Diabetes-Classification-with-Heterogeneous-Data **Explanation** - column 0: label - column 1-576: FGM data - column 576-587: Biomarkers data You might notice some of consecutive rows have same biomarkers, this means that these few rows are contributed by the same patient. There are also some missing value in biomarkers, presented as '0'.

Aashi/Science_Q_and_A_dataset

--- license: mit --- This dataset has been extracted from the class 9 CBSE science book for finetuning an LLM for a chatbot application.

notjoemartinez/Mozart

--- license: apache-2.0 ---

prathap-reddy/autotrain-data-climate-text-classification

--- language: - en task_categories: - text-classification --- # AutoTrain Dataset for project: climate-text-classification ## Dataset Descritpion This dataset has been automatically processed by AutoTrain for project climate-text-classification. ### Languages The BCP-47 code for the dataset's language is en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "text": "So the way our model has currently been built, we would look to pay down debt with our free cash flow generation that we're planning on generating this year, which is around $20 million to $30 million.", "target": 0 }, { "text": "So we don't see any big drama on the long-term FMPs as a result of this.", "target": 0 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "text": "Value(dtype='string', id=None)", "target": "ClassLabel(num_classes=2, names=['0', '1'], id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 1919 | | valid | 481 |

ofir408/try2

--- license: apache-2.0 ---

mfidabel/common_voice_16_1_semisupervised

--- dataset_info: features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 48000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string - name: predicted_sentence dtype: string splits: - name: whisper.medium num_bytes: 8271758359.625 num_examples: 18779 - name: whisper.small num_bytes: 2763174559.625 num_examples: 18779 - name: whisper.large.v3 num_bytes: 8271776000.625 num_examples: 18779 - name: whisper.tiny num_bytes: 8271831240.625 num_examples: 18779 download_size: 23466393916 dataset_size: 27578540160.5 configs: - config_name: default data_files: - split: whisper.medium path: data/whisper.medium-* - split: whisper.small path: data/whisper.small-* - split: whisper.large.v3 path: data/whisper.large.v3-* - split: whisper.tiny path: data/whisper.tiny-* ---

PS-123/LungNodule

--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 132655580.844 num_examples: 1723 download_size: 157049632 dataset_size: 132655580.844 --- # Dataset Card for "LungNodule" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

quibblerquery/youTubeData

--- license: mit ---

open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca

--- pretty_name: Evaluation run of TFLai/gpt-neo-1.3B-4bit-alpaca dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TFLai/gpt-neo-1.3B-4bit-alpaca](https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-23T17:57:15.784929](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca/blob/main/results_2023-09-23T17-57-15.784929.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0009437919463087249,\n\ \ \"em_stderr\": 0.00031446531194133983,\n \"f1\": 0.05118708053691287,\n\ \ \"f1_stderr\": 0.001257884278930374,\n \"acc\": 0.2821159149890526,\n\ \ \"acc_stderr\": 0.007628169555669113\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0009437919463087249,\n \"em_stderr\": 0.00031446531194133983,\n\ \ \"f1\": 0.05118708053691287,\n \"f1_stderr\": 0.001257884278930374\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.002274450341167551,\n \ \ \"acc_stderr\": 0.0013121578148674233\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.5619573796369376,\n \"acc_stderr\": 0.013944181296470803\n\ \ }\n}\n```" repo_url: https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca 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_08_18T13_07_16.687815 path: - '**/details_harness|arc:challenge|25_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-18T13:07:16.687815.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_23T17_57_15.784929 path: - '**/details_harness|drop|3_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '**/details_harness|drop|3_2023-09-23T17-57-15.784929.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_23T17_57_15.784929 path: - '**/details_harness|gsm8k|5_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-09-23T17-57-15.784929.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hellaswag|10_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-18T13:07:16.687815.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-management|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T13:07:16.687815.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_18T13_07_16.687815 path: - '**/details_harness|truthfulqa:mc|0_2023-08-18T13:07:16.687815.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-18T13:07:16.687815.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_23T17_57_15.784929 path: - '**/details_harness|winogrande|5_2023-09-23T17-57-15.784929.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-09-23T17-57-15.784929.parquet' - config_name: results data_files: - split: 2023_08_18T13_07_16.687815 path: - results_2023-08-18T13:07:16.687815.parquet - split: 2023_09_23T17_57_15.784929 path: - results_2023-09-23T17-57-15.784929.parquet - split: latest path: - results_2023-09-23T17-57-15.784929.parquet --- # Dataset Card for Evaluation run of TFLai/gpt-neo-1.3B-4bit-alpaca ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca - **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 [TFLai/gpt-neo-1.3B-4bit-alpaca](https://huggingface.co/TFLai/gpt-neo-1.3B-4bit-alpaca) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-23T17:57:15.784929](https://huggingface.co/datasets/open-llm-leaderboard/details_TFLai__gpt-neo-1.3B-4bit-alpaca/blob/main/results_2023-09-23T17-57-15.784929.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0009437919463087249, "em_stderr": 0.00031446531194133983, "f1": 0.05118708053691287, "f1_stderr": 0.001257884278930374, "acc": 0.2821159149890526, "acc_stderr": 0.007628169555669113 }, "harness|drop|3": { "em": 0.0009437919463087249, "em_stderr": 0.00031446531194133983, "f1": 0.05118708053691287, "f1_stderr": 0.001257884278930374 }, "harness|gsm8k|5": { "acc": 0.002274450341167551, "acc_stderr": 0.0013121578148674233 }, "harness|winogrande|5": { "acc": 0.5619573796369376, "acc_stderr": 0.013944181296470803 } } ``` ### 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]

devjirawat8/Air_Vehicle

--- license: mit ---

CyberHarem/glasgow_azurlane

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of glasgow/グラスゴー/格拉斯哥 (Azur Lane) This is the dataset of glasgow/グラスゴー/格拉斯哥 (Azur Lane), containing 68 images and their tags. The core tags of this character are `long_hair, twintails, bangs, breasts, black_hair, maid_headdress, ribbon, blue_eyes, bow, low_twintails, large_breasts, brown_hair, green_eyes`, 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 | 68 | 76.60 MiB | [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 68 | 44.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 167 | 96.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 68 | 68.16 MiB | [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 167 | 132.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/glasgow_azurlane/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/glasgow_azurlane', 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 | 46 | ![](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, maid, solo, blush, looking_at_viewer, frills, simple_background, wrist_cuffs, white_background, black_dress, puffy_short_sleeves, choker, cleavage, white_apron | | 1 | 18 | ![](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, blush, looking_at_viewer, white_shirt, school_uniform, plaid_skirt, red_necktie, solo, long_sleeves, pleated_skirt, collared_shirt, black_jacket, hairclip, red_skirt, blazer, hair_between_eyes, open_jacket, hair_ribbon, open_mouth, very_long_hair | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | maid | solo | blush | looking_at_viewer | frills | simple_background | wrist_cuffs | white_background | black_dress | puffy_short_sleeves | choker | cleavage | white_apron | white_shirt | school_uniform | plaid_skirt | red_necktie | long_sleeves | pleated_skirt | collared_shirt | black_jacket | hairclip | red_skirt | blazer | hair_between_eyes | open_jacket | hair_ribbon | open_mouth | very_long_hair | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:-------|:--------|:--------------------|:---------|:--------------------|:--------------|:-------------------|:--------------|:----------------------|:---------|:-----------|:--------------|:--------------|:-----------------|:--------------|:--------------|:---------------|:----------------|:-----------------|:---------------|:-----------|:------------|:---------|:--------------------|:--------------|:--------------|:-------------|:-----------------| | 0 | 46 | ![](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 | | | | | | | | | | | | | | | | | | 1 | 18 | ![](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 |

NathanRoll/TalkBank_CA_CABNC_1

--- dataset_info: features: - name: audio sequence: float32 - name: __index_level_0__ dtype: string splits: - name: train num_bytes: 17080612876 num_examples: 100 download_size: 17100223923 dataset_size: 17080612876 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "TalkBank_CA_CABNC_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

datasciathlete/open-ner-english

--- dataset_info: features: - name: entities list: - name: entity_mentions sequence: string - name: entity_type dtype: string - name: spans sequence: sequence: int64 - name: text dtype: string splits: - name: train num_bytes: 72484875.50541525 num_examples: 36711 - name: validation num_bytes: 18121712.494584758 num_examples: 9178 download_size: 90106463 dataset_size: 90606588.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

cimadure/snow_removal_transactions_in_montreal

--- license: cc-by-4.0 ---

open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused

--- pretty_name: Evaluation run of stanford-oval/Llama-2-7b-WikiChat-fused dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [stanford-oval/Llama-2-7b-WikiChat-fused](https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused)\ \ 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_stanford-oval__Llama-2-7b-WikiChat-fused\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-16T05:29:49.524111](https://huggingface.co/datasets/open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused/blob/main/results_2024-01-16T05-29-49.524111.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\": 0.3993615462452277,\n\ \ \"acc_stderr\": 0.03426948672248777,\n \"acc_norm\": 0.4047541011703342,\n\ \ \"acc_norm_stderr\": 0.035187845841979204,\n \"mc1\": 0.30966952264381886,\n\ \ \"mc1_stderr\": 0.01618574435514492,\n \"mc2\": 0.46362057203759177,\n\ \ \"mc2_stderr\": 0.015792473170958256\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.47696245733788395,\n \"acc_stderr\": 0.014595873205358262,\n\ \ \"acc_norm\": 0.5068259385665529,\n \"acc_norm_stderr\": 0.014610029151379813\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5690101573391755,\n\ \ \"acc_stderr\": 0.00494202620027959,\n \"acc_norm\": 0.7499502091216889,\n\ \ \"acc_norm_stderr\": 0.004321564303822422\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\": 0.37777777777777777,\n\ \ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.37777777777777777,\n\ \ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.32894736842105265,\n \"acc_stderr\": 0.038234289699266046,\n\ \ \"acc_norm\": 0.32894736842105265,\n \"acc_norm_stderr\": 0.038234289699266046\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.46,\n\ \ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.46,\n \ \ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.4188679245283019,\n \"acc_stderr\": 0.030365050829115208,\n\ \ \"acc_norm\": 0.4188679245283019,\n \"acc_norm_stderr\": 0.030365050829115208\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4652777777777778,\n\ \ \"acc_stderr\": 0.04171115858181618,\n \"acc_norm\": 0.4652777777777778,\n\ \ \"acc_norm_stderr\": 0.04171115858181618\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.31,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952344,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952344\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3179190751445087,\n\ \ \"acc_stderr\": 0.0355068398916558,\n \"acc_norm\": 0.3179190751445087,\n\ \ \"acc_norm_stderr\": 0.0355068398916558\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.41,\n\ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.37446808510638296,\n \"acc_stderr\": 0.03163910665367291,\n\ \ \"acc_norm\": 0.37446808510638296,\n \"acc_norm_stderr\": 0.03163910665367291\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3157894736842105,\n\ \ \"acc_stderr\": 0.043727482902780064,\n \"acc_norm\": 0.3157894736842105,\n\ \ \"acc_norm_stderr\": 0.043727482902780064\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.38620689655172413,\n \"acc_stderr\": 0.04057324734419035,\n\ \ \"acc_norm\": 0.38620689655172413,\n \"acc_norm_stderr\": 0.04057324734419035\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2724867724867725,\n \"acc_stderr\": 0.022930973071633356,\n \"\ acc_norm\": 0.2724867724867725,\n \"acc_norm_stderr\": 0.022930973071633356\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.040061680838488774,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.040061680838488774\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.4290322580645161,\n\ \ \"acc_stderr\": 0.028156036538233217,\n \"acc_norm\": 0.4290322580645161,\n\ \ \"acc_norm_stderr\": 0.028156036538233217\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.24630541871921183,\n \"acc_stderr\": 0.030315099285617715,\n\ \ \"acc_norm\": 0.24630541871921183,\n \"acc_norm_stderr\": 0.030315099285617715\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\"\ : 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.41818181818181815,\n \"acc_stderr\": 0.03851716319398393,\n\ \ \"acc_norm\": 0.41818181818181815,\n \"acc_norm_stderr\": 0.03851716319398393\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.4898989898989899,\n \"acc_stderr\": 0.035616254886737454,\n \"\ acc_norm\": 0.4898989898989899,\n \"acc_norm_stderr\": 0.035616254886737454\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.5492227979274611,\n \"acc_stderr\": 0.03590910952235524,\n\ \ \"acc_norm\": 0.5492227979274611,\n \"acc_norm_stderr\": 0.03590910952235524\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4153846153846154,\n \"acc_stderr\": 0.02498535492310234,\n \ \ \"acc_norm\": 0.4153846153846154,\n \"acc_norm_stderr\": 0.02498535492310234\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.23333333333333334,\n \"acc_stderr\": 0.025787874220959316,\n \ \ \"acc_norm\": 0.23333333333333334,\n \"acc_norm_stderr\": 0.025787874220959316\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.42436974789915966,\n \"acc_stderr\": 0.032104790510157764,\n\ \ \"acc_norm\": 0.42436974789915966,\n \"acc_norm_stderr\": 0.032104790510157764\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969654,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969654\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.5247706422018349,\n\ \ \"acc_stderr\": 0.021410999753635914,\n \"acc_norm\": 0.5247706422018349,\n\ \ \"acc_norm_stderr\": 0.021410999753635914\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.3888888888888889,\n \"acc_stderr\": 0.033247089118091176,\n\ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.033247089118091176\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.45098039215686275,\n \"acc_stderr\": 0.03492406104163613,\n \"\ acc_norm\": 0.45098039215686275,\n \"acc_norm_stderr\": 0.03492406104163613\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.4388185654008439,\n \"acc_stderr\": 0.032302649315470375,\n \ \ \"acc_norm\": 0.4388185654008439,\n \"acc_norm_stderr\": 0.032302649315470375\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4618834080717489,\n\ \ \"acc_stderr\": 0.03346015011973228,\n \"acc_norm\": 0.4618834080717489,\n\ \ \"acc_norm_stderr\": 0.03346015011973228\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.4198473282442748,\n \"acc_stderr\": 0.04328577215262971,\n\ \ \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.04328577215262971\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.4462809917355372,\n \"acc_stderr\": 0.0453793517794788,\n \"acc_norm\"\ : 0.4462809917355372,\n \"acc_norm_stderr\": 0.0453793517794788\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4351851851851852,\n\ \ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.4351851851851852,\n\ \ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.4233128834355828,\n \"acc_stderr\": 0.038818912133343826,\n\ \ \"acc_norm\": 0.4233128834355828,\n \"acc_norm_stderr\": 0.038818912133343826\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.38392857142857145,\n\ \ \"acc_stderr\": 0.04616143075028547,\n \"acc_norm\": 0.38392857142857145,\n\ \ \"acc_norm_stderr\": 0.04616143075028547\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5145631067961165,\n \"acc_stderr\": 0.049486373240266356,\n\ \ \"acc_norm\": 0.5145631067961165,\n \"acc_norm_stderr\": 0.049486373240266356\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.5811965811965812,\n\ \ \"acc_stderr\": 0.03232128912157792,\n \"acc_norm\": 0.5811965811965812,\n\ \ \"acc_norm_stderr\": 0.03232128912157792\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.5759897828863346,\n\ \ \"acc_stderr\": 0.017672263329084222,\n \"acc_norm\": 0.5759897828863346,\n\ \ \"acc_norm_stderr\": 0.017672263329084222\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.3699421965317919,\n \"acc_stderr\": 0.025992472029306376,\n\ \ \"acc_norm\": 0.3699421965317919,\n \"acc_norm_stderr\": 0.025992472029306376\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.28044692737430166,\n\ \ \"acc_stderr\": 0.01502408388332289,\n \"acc_norm\": 0.28044692737430166,\n\ \ \"acc_norm_stderr\": 0.01502408388332289\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.4150326797385621,\n \"acc_stderr\": 0.028213504177824103,\n\ \ \"acc_norm\": 0.4150326797385621,\n \"acc_norm_stderr\": 0.028213504177824103\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.44694533762057875,\n\ \ \"acc_stderr\": 0.028237769422085335,\n \"acc_norm\": 0.44694533762057875,\n\ \ \"acc_norm_stderr\": 0.028237769422085335\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.3487654320987654,\n \"acc_stderr\": 0.02651759772446501,\n\ \ \"acc_norm\": 0.3487654320987654,\n \"acc_norm_stderr\": 0.02651759772446501\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.29432624113475175,\n \"acc_stderr\": 0.027187127011503786,\n \ \ \"acc_norm\": 0.29432624113475175,\n \"acc_norm_stderr\": 0.027187127011503786\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3200782268578879,\n\ \ \"acc_stderr\": 0.011914791947638519,\n \"acc_norm\": 0.3200782268578879,\n\ \ \"acc_norm_stderr\": 0.011914791947638519\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.4411764705882353,\n \"acc_stderr\": 0.030161911930767102,\n\ \ \"acc_norm\": 0.4411764705882353,\n \"acc_norm_stderr\": 0.030161911930767102\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.34967320261437906,\n \"acc_stderr\": 0.019291961895066365,\n \ \ \"acc_norm\": 0.34967320261437906,\n \"acc_norm_stderr\": 0.019291961895066365\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.45454545454545453,\n\ \ \"acc_stderr\": 0.04769300568972744,\n \"acc_norm\": 0.45454545454545453,\n\ \ \"acc_norm_stderr\": 0.04769300568972744\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.3469387755102041,\n \"acc_stderr\": 0.030472526026726496,\n\ \ \"acc_norm\": 0.3469387755102041,\n \"acc_norm_stderr\": 0.030472526026726496\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.5422885572139303,\n\ \ \"acc_stderr\": 0.035228658640995975,\n \"acc_norm\": 0.5422885572139303,\n\ \ \"acc_norm_stderr\": 0.035228658640995975\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.04999999999999999,\n \ \ \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.04999999999999999\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.3493975903614458,\n\ \ \"acc_stderr\": 0.0371172519074075,\n \"acc_norm\": 0.3493975903614458,\n\ \ \"acc_norm_stderr\": 0.0371172519074075\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.5906432748538012,\n \"acc_stderr\": 0.03771283107626544,\n\ \ \"acc_norm\": 0.5906432748538012,\n \"acc_norm_stderr\": 0.03771283107626544\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.30966952264381886,\n\ \ \"mc1_stderr\": 0.01618574435514492,\n \"mc2\": 0.46362057203759177,\n\ \ \"mc2_stderr\": 0.015792473170958256\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6906077348066298,\n \"acc_stderr\": 0.012991329330822999\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.000758150113722517,\n \ \ \"acc_stderr\": 0.0007581501137225212\n }\n}\n```" repo_url: https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused 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_16T05_29_49.524111 path: - '**/details_harness|arc:challenge|25_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-16T05-29-49.524111.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|gsm8k|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hellaswag|10_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-16T05-29-49.524111.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-management|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-16T05-29-49.524111.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|truthfulqa:mc|0_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-16T05-29-49.524111.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_16T05_29_49.524111 path: - '**/details_harness|winogrande|5_2024-01-16T05-29-49.524111.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-16T05-29-49.524111.parquet' - config_name: results data_files: - split: 2024_01_16T05_29_49.524111 path: - results_2024-01-16T05-29-49.524111.parquet - split: latest path: - results_2024-01-16T05-29-49.524111.parquet --- # Dataset Card for Evaluation run of stanford-oval/Llama-2-7b-WikiChat-fused  Dataset automatically created during the evaluation run of model [stanford-oval/Llama-2-7b-WikiChat-fused](https://huggingface.co/stanford-oval/Llama-2-7b-WikiChat-fused) 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_stanford-oval__Llama-2-7b-WikiChat-fused", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-16T05:29:49.524111](https://huggingface.co/datasets/open-llm-leaderboard/details_stanford-oval__Llama-2-7b-WikiChat-fused/blob/main/results_2024-01-16T05-29-49.524111.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": 0.3993615462452277, "acc_stderr": 0.03426948672248777, "acc_norm": 0.4047541011703342, "acc_norm_stderr": 0.035187845841979204, "mc1": 0.30966952264381886, "mc1_stderr": 0.01618574435514492, "mc2": 0.46362057203759177, "mc2_stderr": 0.015792473170958256 }, "harness|arc:challenge|25": { "acc": 0.47696245733788395, "acc_stderr": 0.014595873205358262, "acc_norm": 0.5068259385665529, "acc_norm_stderr": 0.014610029151379813 }, "harness|hellaswag|10": { "acc": 0.5690101573391755, "acc_stderr": 0.00494202620027959, "acc_norm": 0.7499502091216889, "acc_norm_stderr": 0.004321564303822422 }, "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": 0.37777777777777777, "acc_stderr": 0.04188307537595853, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.32894736842105265, "acc_stderr": 0.038234289699266046, "acc_norm": 0.32894736842105265, "acc_norm_stderr": 0.038234289699266046 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4188679245283019, "acc_stderr": 0.030365050829115208, "acc_norm": 0.4188679245283019, "acc_norm_stderr": 0.030365050829115208 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4652777777777778, "acc_stderr": 0.04171115858181618, "acc_norm": 0.4652777777777778, "acc_norm_stderr": 0.04171115858181618 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.047609522856952344, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952344 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3179190751445087, "acc_stderr": 0.0355068398916558, "acc_norm": 0.3179190751445087, "acc_norm_stderr": 0.0355068398916558 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.37446808510638296, "acc_stderr": 0.03163910665367291, "acc_norm": 0.37446808510638296, "acc_norm_stderr": 0.03163910665367291 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.043727482902780064, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.043727482902780064 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.38620689655172413, "acc_stderr": 0.04057324734419035, "acc_norm": 0.38620689655172413, "acc_norm_stderr": 0.04057324734419035 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2724867724867725, "acc_stderr": 0.022930973071633356, "acc_norm": 0.2724867724867725, "acc_norm_stderr": 0.022930973071633356 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2777777777777778, "acc_stderr": 0.040061680838488774, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.040061680838488774 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4290322580645161, "acc_stderr": 0.028156036538233217, "acc_norm": 0.4290322580645161, "acc_norm_stderr": 0.028156036538233217 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.24630541871921183, "acc_stderr": 0.030315099285617715, "acc_norm": 0.24630541871921183, "acc_norm_stderr": 0.030315099285617715 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.41818181818181815, "acc_stderr": 0.03851716319398393, "acc_norm": 0.41818181818181815, "acc_norm_stderr": 0.03851716319398393 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4898989898989899, "acc_stderr": 0.035616254886737454, "acc_norm": 0.4898989898989899, "acc_norm_stderr": 0.035616254886737454 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5492227979274611, "acc_stderr": 0.03590910952235524, "acc_norm": 0.5492227979274611, "acc_norm_stderr": 0.03590910952235524 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4153846153846154, "acc_stderr": 0.02498535492310234, "acc_norm": 0.4153846153846154, "acc_norm_stderr": 0.02498535492310234 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.23333333333333334, "acc_stderr": 0.025787874220959316, "acc_norm": 0.23333333333333334, "acc_norm_stderr": 0.025787874220959316 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.42436974789915966, "acc_stderr": 0.032104790510157764, "acc_norm": 0.42436974789915966, "acc_norm_stderr": 0.032104790510157764 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969654, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969654 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.5247706422018349, "acc_stderr": 0.021410999753635914, "acc_norm": 0.5247706422018349, "acc_norm_stderr": 0.021410999753635914 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.033247089118091176, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.033247089118091176 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.45098039215686275, "acc_stderr": 0.03492406104163613, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.03492406104163613 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.4388185654008439, "acc_stderr": 0.032302649315470375, "acc_norm": 0.4388185654008439, "acc_norm_stderr": 0.032302649315470375 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4618834080717489, "acc_stderr": 0.03346015011973228, "acc_norm": 0.4618834080717489, "acc_norm_stderr": 0.03346015011973228 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.4198473282442748, "acc_stderr": 0.04328577215262971, "acc_norm": 0.4198473282442748, "acc_norm_stderr": 0.04328577215262971 }, "harness|hendrycksTest-international_law|5": { "acc": 0.4462809917355372, "acc_stderr": 0.0453793517794788, "acc_norm": 0.4462809917355372, "acc_norm_stderr": 0.0453793517794788 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4351851851851852, "acc_stderr": 0.04792898170907061, "acc_norm": 0.4351851851851852, "acc_norm_stderr": 0.04792898170907061 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.4233128834355828, "acc_stderr": 0.038818912133343826, "acc_norm": 0.4233128834355828, "acc_norm_stderr": 0.038818912133343826 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.38392857142857145, "acc_stderr": 0.04616143075028547, "acc_norm": 0.38392857142857145, "acc_norm_stderr": 0.04616143075028547 }, "harness|hendrycksTest-management|5": { "acc": 0.5145631067961165, "acc_stderr": 0.049486373240266356, "acc_norm": 0.5145631067961165, "acc_norm_stderr": 0.049486373240266356 }, "harness|hendrycksTest-marketing|5": { "acc": 0.5811965811965812, "acc_stderr": 0.03232128912157792, "acc_norm": 0.5811965811965812, "acc_norm_stderr": 0.03232128912157792 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.5759897828863346, "acc_stderr": 0.017672263329084222, "acc_norm": 0.5759897828863346, "acc_norm_stderr": 0.017672263329084222 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.3699421965317919, "acc_stderr": 0.025992472029306376, "acc_norm": 0.3699421965317919, "acc_norm_stderr": 0.025992472029306376 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.28044692737430166, "acc_stderr": 0.01502408388332289, "acc_norm": 0.28044692737430166, "acc_norm_stderr": 0.01502408388332289 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.4150326797385621, "acc_stderr": 0.028213504177824103, "acc_norm": 0.4150326797385621, "acc_norm_stderr": 0.028213504177824103 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.44694533762057875, "acc_stderr": 0.028237769422085335, "acc_norm": 0.44694533762057875, "acc_norm_stderr": 0.028237769422085335 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.3487654320987654, "acc_stderr": 0.02651759772446501, "acc_norm": 0.3487654320987654, "acc_norm_stderr": 0.02651759772446501 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.29432624113475175, "acc_stderr": 0.027187127011503786, "acc_norm": 0.29432624113475175, "acc_norm_stderr": 0.027187127011503786 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3200782268578879, "acc_stderr": 0.011914791947638519, "acc_norm": 0.3200782268578879, "acc_norm_stderr": 0.011914791947638519 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.4411764705882353, "acc_stderr": 0.030161911930767102, "acc_norm": 0.4411764705882353, "acc_norm_stderr": 0.030161911930767102 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.34967320261437906, "acc_stderr": 0.019291961895066365, "acc_norm": 0.34967320261437906, "acc_norm_stderr": 0.019291961895066365 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.45454545454545453, "acc_stderr": 0.04769300568972744, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.04769300568972744 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.3469387755102041, "acc_stderr": 0.030472526026726496, "acc_norm": 0.3469387755102041, "acc_norm_stderr": 0.030472526026726496 }, "harness|hendrycksTest-sociology|5": { "acc": 0.5422885572139303, "acc_stderr": 0.035228658640995975, "acc_norm": 0.5422885572139303, "acc_norm_stderr": 0.035228658640995975 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.45, "acc_stderr": 0.04999999999999999, "acc_norm": 0.45, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-virology|5": { "acc": 0.3493975903614458, "acc_stderr": 0.0371172519074075, "acc_norm": 0.3493975903614458, "acc_norm_stderr": 0.0371172519074075 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.5906432748538012, "acc_stderr": 0.03771283107626544, "acc_norm": 0.5906432748538012, "acc_norm_stderr": 0.03771283107626544 }, "harness|truthfulqa:mc|0": { "mc1": 0.30966952264381886, "mc1_stderr": 0.01618574435514492, "mc2": 0.46362057203759177, "mc2_stderr": 0.015792473170958256 }, "harness|winogrande|5": { "acc": 0.6906077348066298, "acc_stderr": 0.012991329330822999 }, "harness|gsm8k|5": { "acc": 0.000758150113722517, "acc_stderr": 0.0007581501137225212 } } ``` ## 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]

distilled-one-sec-cv12-each-chunk-uniq/chunk_54

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1332826588.0 num_examples: 259709 download_size: 1366988795 dataset_size: 1332826588.0 --- # Dataset Card for "chunk_54" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

julia-wenkmann/TennisSegmentation

--- dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 1159771633.0 num_examples: 197 download_size: 77225573 dataset_size: 1159771633.0 configs: - config_name: default data_files: - split: train path: data/train-* --- - **Category Name:** `object` - **ID:** `1` - **Color:** RGB(0, 113, 188) - **Category Name:** `ball` - **ID:** `2` - **Color:** RGB(216, 82, 24) - **Category Name:** `playerTop` - **ID:** `3` - **Color:** RGB(236, 176, 31) - **Category Name:** `playerBottom` - **ID:** `4` - **Color:** RGB(125, 46, 141) - **Category Name:** `court` - **ID:** `5` - **Color:** RGB(118, 171, 47)

Birchlabs/openai-prm800k-phase2_test-stepwise-critique

--- license: mit ---

n3rd0/VSI_biology_QA

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1341870 num_examples: 4500 - name: test num_bytes: 242060 num_examples: 794 download_size: 518043 dataset_size: 1583930 --- # Dataset Card for "VSI_biology_QA" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

AshanGimhana/testing001

--- license: mit ---

germank/hh-generated_flan_t5_large_with_features2_flan_t5_large

--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string - name: 'biased:' dtype: int64 - name: easy-to-understand dtype: int64 - name: enough-detail dtype: int64 - name: factuality dtype: int64 - name: fail-to-consider-context dtype: int64 - name: fail-to-consider-individual-preferences dtype: int64 - name: helpfulness dtype: int64 - name: intent dtype: int64 - name: readability dtype: int64 - name: relevance dtype: int64 - name: repetetive dtype: int64 - name: specificity dtype: int64 - name: too-long dtype: int64 - name: log_score dtype: float64 splits: - name: train num_bytes: 408123 num_examples: 1600 download_size: 87285 dataset_size: 408123 --- # Dataset Card for "hh-generated_flan_t5_large_with_features2_flan_t5_large" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

reza-alipour/discofuse_1percent

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: connective_string dtype: string - name: discourse_type dtype: string - name: coherent_second_sentence dtype: string - name: has_coref_type_pronoun dtype: float32 - name: incoherent_first_sentence dtype: string - name: incoherent_second_sentence dtype: string - name: has_coref_type_nominal dtype: float32 - name: coherent_first_sentence dtype: string splits: - name: train num_bytes: 63778517.906742156 num_examples: 163105 download_size: 42876638 dataset_size: 63778517.906742156 --- # Dataset Card for "discofuse_1percent" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

AdapterOcean/med_alpaca_standardized_cluster_39_std

--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: cluster dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 8221814 num_examples: 19165 download_size: 4380540 dataset_size: 8221814 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_39_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

tdh87/STORYTELLERV100

--- license: apache-2.0 ---

Glavin001/startup-interviews

--- license: cc-by-nc-2.0 task_categories: - question-answering - text-generation language: - en size_categories: - n<1K ---

zelalt/great_papers_augmentation

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 2663516.5807451624 num_examples: 1731 download_size: 1670568 dataset_size: 2663516.5807451624 configs: - config_name: default data_files: - split: train path: data/train-* ---

psroy/mini-platypus-guanaco-one-400

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 543862 num_examples: 400 download_size: 328169 dataset_size: 543862 configs: - config_name: default data_files: - split: train path: data/train-* ---

BitBasher/mini-dataset-978

--- dataset_info: features: - name: expected_output dtype: string - name: instruction dtype: string - name: input_content dtype: string splits: - name: train num_bytes: 825340 num_examples: 978 download_size: 229603 dataset_size: 825340 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_YeungNLP__firefly-llama-13b

--- pretty_name: Evaluation run of YeungNLP/firefly-llama-13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [YeungNLP/firefly-llama-13b](https://huggingface.co/YeungNLP/firefly-llama-13b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_YeungNLP__firefly-llama-13b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-15T14:09:32.562166](https://huggingface.co/datasets/open-llm-leaderboard/details_YeungNLP__firefly-llama-13b/blob/main/results_2023-10-15T14-09-32.562166.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\": 0.12720218120805368,\n\ \ \"em_stderr\": 0.003412272897129365,\n \"f1\": 0.22689702181208146,\n\ \ \"f1_stderr\": 0.003654793246945971,\n \"acc\": 0.418998511823731,\n\ \ \"acc_stderr\": 0.009810630903312568\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.12720218120805368,\n \"em_stderr\": 0.003412272897129365,\n\ \ \"f1\": 0.22689702181208146,\n \"f1_stderr\": 0.003654793246945971\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.08188021228203184,\n \ \ \"acc_stderr\": 0.0075523385277169374\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7561168113654302,\n \"acc_stderr\": 0.012068923278908197\n\ \ }\n}\n```" repo_url: https://huggingface.co/YeungNLP/firefly-llama-13b 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_19T18_51_43.691477 path: - '**/details_harness|arc:challenge|25_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-07-19T18:51:43.691477.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_15T14_09_32.562166 path: - '**/details_harness|drop|3_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-15T14-09-32.562166.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_15T14_09_32.562166 path: - '**/details_harness|gsm8k|5_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-15T14-09-32.562166.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hellaswag|10_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-management|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:51:43.691477.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-management|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-07-19T18:51:43.691477.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_07_19T18_51_43.691477 path: - '**/details_harness|truthfulqa:mc|0_2023-07-19T18:51:43.691477.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-07-19T18:51:43.691477.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_15T14_09_32.562166 path: - '**/details_harness|winogrande|5_2023-10-15T14-09-32.562166.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-15T14-09-32.562166.parquet' - config_name: results data_files: - split: 2023_07_19T18_51_43.691477 path: - results_2023-07-19T18:51:43.691477.parquet - split: 2023_10_15T14_09_32.562166 path: - results_2023-10-15T14-09-32.562166.parquet - split: latest path: - results_2023-10-15T14-09-32.562166.parquet --- # Dataset Card for Evaluation run of YeungNLP/firefly-llama-13b ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/YeungNLP/firefly-llama-13b - **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 [YeungNLP/firefly-llama-13b](https://huggingface.co/YeungNLP/firefly-llama-13b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_YeungNLP__firefly-llama-13b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-15T14:09:32.562166](https://huggingface.co/datasets/open-llm-leaderboard/details_YeungNLP__firefly-llama-13b/blob/main/results_2023-10-15T14-09-32.562166.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": 0.12720218120805368, "em_stderr": 0.003412272897129365, "f1": 0.22689702181208146, "f1_stderr": 0.003654793246945971, "acc": 0.418998511823731, "acc_stderr": 0.009810630903312568 }, "harness|drop|3": { "em": 0.12720218120805368, "em_stderr": 0.003412272897129365, "f1": 0.22689702181208146, "f1_stderr": 0.003654793246945971 }, "harness|gsm8k|5": { "acc": 0.08188021228203184, "acc_stderr": 0.0075523385277169374 }, "harness|winogrande|5": { "acc": 0.7561168113654302, "acc_stderr": 0.012068923278908197 } } ``` ### 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]

tejas21private/ai2d_dataset

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 238194265 num_examples: 4900 download_size: 238194265 dataset_size: 238194265 --- # Dataset Card for "ai2d dataset"

candelaz/Kevin

--- license: apache-2.0 ---

harpreetsahota/five_shot_comparison

--- dataset_info: features: - name: source dtype: string - name: target dtype: string - name: rationale dtype: string - name: task dtype: string - name: type dtype: string - name: decilm_generation dtype: string - name: mistral_generation dtype: string - name: falcon_generation dtype: string splits: - name: train num_bytes: 120687 num_examples: 30 download_size: 60550 dataset_size: 120687 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "five_shot_comparison" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

distilabel-internal-testing/Capybara-Preferences-Remaining

--- size_categories: n<1K tags: - synthetic - distilabel - rlaif dataset_info: config_name: keep_columns features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: generations sequence: string - name: generation_models sequence: string - name: ratings sequence: int64 - name: rationales sequence: string - name: ultrafeedback_model dtype: string splits: - name: train num_bytes: 54020454 num_examples: 8375 download_size: 27568892 dataset_size: 54020454 configs: - config_name: keep_columns data_files: - split: train path: keep_columns/train-* --- <p align="left"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> # Dataset Card for Capybara-Preferences-Remaining This dataset has been created with [Distilabel](https://distilabel.argilla.io/). ## Dataset Summary This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI: ```console distilabel pipeline run --config "https://huggingface.co/datasets/distilabel-internal-testing/Capybara-Preferences-Remaining/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/Capybara-Preferences-Remaining/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration: <details><summary> Configuration: keep_columns </summary><hr> ```json { "generation_models": [ "teknium/OpenHermes-2.5-Mistral-7B", "argilla/notus-7b-v1", "mlabonne/NeuralBeagle14-7B", "ask_ldj" ], "generations": [ "Certainly, there are several strategies that can help prevent the creation of a hostile environment during a debate or discussion:\n\n1. Encourage Respectful Communication: Set a tone of respect and promote civil discourse by emphasizing the importance of listening, asking questions, and acknowledging different perspectives.\n\n2. Establish Clear Rules: Clearly outline the ground rules for the discussion or debate, emphasizing that personal attacks or ad hominem remarks will not be tolerated.\n\n3. Promote Active Listening: Encourage participants to actively listen to each other, rather than just waiting for", "Certainly! Here are some strategies that can help prevent the creation of a hostile environment during a debate or discussion:\n\n1. Encourage a Safe and Respectful Space: Create an environment that makes participants feel safe and respected by reminding everyone to avoid ad hominem attacks, to listen to each other, and to respect each other\u0027s viewpoints. Establishing clear ground rules can help everyone focus on the topic at hand and avoid distractions. 2. Encourage Active Listening: Encourage participants to listen actively to each other by letting everyone know that they have been heard,", "Here are some strategies to prevent the creation of a hostile environment during a debate or discussion:\n\n1. Establish ground rules: At the beginning of a debate or discussion, establish clear ground rules or guidelines that promote civility and respect among participants. This may include prohibiting personal attacks, ad hominem arguments, interruptions, or negative body language.\n\n2. Encourage active listening: Encourage all participants to listen actively and attentively to each other\u0027s perspectives. This promotes understanding and can help reduce misunderstandings or emotional escalation.\n\n3. Focus on the issue", "Absolutely, here are some strategies to prevent the creation of a hostile environment during a debate or discussion:\n\n1. Establish Ground Rules: Before starting the discussion, set clear expectations for respectful and constructive dialogue. This might include rules against personal attacks, interruptions, or disrespectful language.\n\n2. Encourage Active Listening: Participants should be encouraged to listen to others\u0027 viewpoints with an open mind, rather than formulating their own responses while others are speaking.\n\n3. Promote Empathy: Encourage participants to try to understand the perspectives and feelings of others, even if they disagree. This can help to foster a sense of mutual respect and understanding.\n\n4. Focus on the Issue, Not the Person: Remind participants to focus on the topic at hand, rather than resorting to personal attacks or criticisms. \n\n5. Use Neutral Language: Avoid inflammatory or loaded language that could escalate tensions. Instead, use neutral, objective language to express your points.\n\n6. Facilitate Fairness: If you\u0027re leading the discussion, ensure that all participants have an equal opportunity to speak and that their viewpoints are given fair consideration.\n\n7. Encourage Questions: Encourage participants to ask clarifying questions if they don\u0027t understand a point, rather than making assumptions or jumping to conclusions.\n\n8. Model Respectful Behavior: If you\u0027re leading the discussion, model the kind of behavior you want to see from participants. This includes listening attentively, responding respectfully, and admitting when you\u0027re wrong.\n\n9. Manage Conflict: If tensions do arise, address them directly and calmly. This might involve taking a short break, reminding participants of the ground rules, or facilitating a resolution between conflicting parties.\n\n10. Provide Positive Feedback: Recognize and reinforce positive behaviors, such as when participants express their points respectfully, listen attentively, or show empathy towards others. This can help to create a more positive and collaborative environment." ], "messages": [ { "content": "Identify the type of logical fallacy in this argument: \u0027You can\u0027t trust Peter because he didn\u0027t go to college.\u0027\n", "role": "user" }, { "content": "The logical fallacy in this argument is ad hominem, because it attacks Peter\u0027s personal characteristics or circumstances (not going to college) rather than addressing the merits of his arguments or ideas.", "role": "assistant" }, { "content": "Given that ad hominem is a type of logical fallacy, how might this bias affect the quality of a debate or discussion?", "role": "user" }, { "content": "Ad hominem fallacies can significantly lower the quality of a debate or discussion. Instead of focusing on the merits of the arguments, ideas, or evidence at hand, participants might get distracted by personal attacks or irrelevant criticisms. This can lead to a hostile environment, where the focus is on winning the argument rather than seeking truth or understanding. Furthermore, it can prevent a fair and balanced evaluation of the actual topic being discussed, as it diverts attention away from the substantive issues.", "role": "assistant" }, { "content": "Discuss the potential consequences of a hostile environment in a debate or discussion.", "role": "user" }, { "content": "A hostile environment in a debate or discussion can have several negative consequences:\n\n1. Deterioration of Communication: When the environment becomes hostile, it can lead to breakdowns in communication. Participants may become defensive or aggressive, which can hinder effective exchange of ideas.\n\n2. Reduced Participation: Some individuals may feel intimidated or uncomfortable in a hostile environment, leading them to withdraw or refrain from contributing their ideas or perspectives.\n\n3. Bias and Prejudice: Hostility can exacerbate biases and prejudices, as participants may resort to stereotypes or discriminatory remarks, further escalating the conflict.\n\n4. Loss of Objectivity: In a hostile environment, participants may lose sight of the objective of the discussion or debate. Instead of seeking to understand different viewpoints or find common ground, they may focus on winning the argument at all costs.\n\n5. Damage to Relationships: If the debate or discussion involves individuals who have ongoing relationships (like colleagues, friends, or family members), a hostile environment can cause long-term damage to these relationships.\n\n6. Misinformation: In a hostile debate, the focus often shifts from facts and logical reasoning to personal attacks. This can lead to the spread of misinformation, as participants may overlook or dismiss valid points or evidence.\n\nOverall, a hostile environment in a debate or discussion can inhibit productive dialogue, discourage participation, and potentially lead to misinformation or misunderstanding.", "role": "assistant" }, { "content": "Could you elaborate on strategies to prevent the creation of a hostile environment during a debate or discussion?", "role": "user" } ], "ratings": [ 4, 4 ], "rationales": [ "The text provides correct and informative strategies to prevent hostility, expressing a clear understanding of the set topics. It does not appear to include any dishonesty, uncertainty, or hallucination; however, the response is cut off, hence not fully complete. This affects the instruction following slightly as the list of strategies is incomplete.", "This text also offers valuable strategies for maintaining a non-hostile environment, aligning well with the user\u0027s request. The strategies are articulated clearly and confidently. However, the output" ], "ultrafeedback_model": "gpt-4-1106-preview" } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("distilabel-internal-testing/Capybara-Preferences-Remaining", "keep_columns") ``` </details>

spdenisov/processed

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 548644785 num_examples: 191025 download_size: 80309791 dataset_size: 548644785 --- # Dataset Card for "processed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

alisson40889/HOLK

--- license: openrail ---

Mitsuki-Sakamoto/alpaca_farm-reward-model-deberta-v3-large-v2-re-preference-64-nsample-2_random

--- dataset_info: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25669546 num_examples: 20001 download_size: 12196543 dataset_size: 25669546 - config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25645562 num_examples: 20001 download_size: 12148697 dataset_size: 25645562 - config_name: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string splits: - name: preference num_bytes: 25489159 num_examples: 20001 download_size: 11795765 dataset_size: 25489159 configs: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 data_files: - split: preference path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/preference-* - config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 data_files: - split: preference path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/preference-* - config_name: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1 data_files: - split: preference path: alpaca_instructions-pythia_70m_alpaca_farm_instructions_sft_constant_pa_seed_1/preference-* ---

FarmerlineML/igbo_dataset_2

--- dataset_info: features: - name: transcription dtype: string - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 162930082.12 num_examples: 4892 - name: test num_bytes: 28447287.0 num_examples: 802 download_size: 185263836 dataset_size: 191377369.12 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

nz/ulma_anthropic_hh_golden

--- dataset_info: features: - name: chosen dtype: string - name: rejected dtype: string - name: prompt dtype: string splits: - name: train num_bytes: 37152501 num_examples: 42537 - name: test num_bytes: 2071585 num_examples: 2312 download_size: 22809621 dataset_size: 39224086 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

Damoniano/Agent1

--- license: creativeml-openrail-m ---

davidfant/natural-questions-chunk-11

--- dataset_info: features: - name: id dtype: string - name: document struct: - name: html dtype: string - name: title dtype: string - name: tokens sequence: - name: end_byte dtype: int64 - name: is_html dtype: bool - name: start_byte dtype: int64 - name: token dtype: string - name: url dtype: string - name: question struct: - name: text dtype: string - name: tokens sequence: string - name: long_answer_candidates sequence: - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: top_level dtype: bool - name: annotations sequence: - name: id dtype: string - name: long_answer struct: - name: candidate_index dtype: int64 - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: short_answers sequence: - name: end_byte dtype: int64 - name: end_token dtype: int64 - name: start_byte dtype: int64 - name: start_token dtype: int64 - name: text dtype: string - name: yes_no_answer dtype: class_label: names: '0': 'NO' '1': 'YES' splits: - name: train num_bytes: 4676417206 num_examples: 10000 download_size: 1813929282 dataset_size: 4676417206 --- # Dataset Card for "natural-questions-chunk-11" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

rafasds/Alannovo

--- license: openrail ---

eduardem/parrot_en_es_sample

--- license: openrail --- # Parrot_en_es Fine-Tuning Dataset ## Introduction This dataset serves as a sample for fine-tuning the `parrot_en_es` translation model. The data is structured in the OpenOrca format and is designed to train the model to perform specific tasks related to translation. ## Objective The primary aim of this dataset is to achieve alignment in the model so that it acts strictly as a translator. The model should output solely the translation, avoiding any additional comments, considerations, extra content, fixes, or refusals. ## Format ### OpenOrca The dataset employs the OpenOrca format and maintains a consistent system prompt across all samples. This uniformity in system prompts is intended to guide the model towards the desired behavior, which is to produce only the translation. ## Usage This dataset can be used to: - Fine-tune the `parrot_en_es` translation model - Validate the model's ability to output clean translations without any superfluous content - Assess the effectiveness of using a consistent system prompt to guide model behavior ## Contributing For suggestions to improve or expand the dataset, feel free to open an issue or submit a pull request.

irds/mr-tydi_ja

--- pretty_name: '`mr-tydi/ja`' viewer: false source_datasets: [] task_categories: - text-retrieval --- # Dataset Card for `mr-tydi/ja` The `mr-tydi/ja` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/mr-tydi#mr-tydi/ja). # Data This dataset provides: - `docs` (documents, i.e., the corpus); count=7,000,027 - `queries` (i.e., topics); count=5,353 - `qrels`: (relevance assessments); count=5,548 This dataset is used by: [`mr-tydi_ja_dev`](https://huggingface.co/datasets/irds/mr-tydi_ja_dev), [`mr-tydi_ja_test`](https://huggingface.co/datasets/irds/mr-tydi_ja_test), [`mr-tydi_ja_train`](https://huggingface.co/datasets/irds/mr-tydi_ja_train) ## Usage ```python from datasets import load_dataset docs = load_dataset('irds/mr-tydi_ja', 'docs') for record in docs: record # {'doc_id': ..., 'text': ...} queries = load_dataset('irds/mr-tydi_ja', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/mr-tydi_ja', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @article{Zhang2021MrTyDi, title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin}, year={2021}, journal={arXiv:2108.08787}, } @article{Clark2020TyDiQa, title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}, year={2020}, journal={Transactions of the Association for Computational Linguistics} } ```

hungsmoie/khoaiphim

--- license: unlicense ---

Farisya/usermanual-dataset

--- dataset_info: features: - name: example dtype: string splits: - name: train num_bytes: 18543 num_examples: 22 - name: test num_bytes: 8671 num_examples: 9 download_size: 20134 dataset_size: 27214 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k

--- pretty_name: Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2927085297989137,\n\ \ \"acc_stderr\": 0.03275517148401362,\n \"acc_norm\": 0.29622047886660385,\n\ \ \"acc_norm_stderr\": 0.032746678820457335,\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.46928327645051193,\n \"acc_stderr\": 0.014583792546304038,\n\ \ \"acc_norm\": 0.4974402730375427,\n \"acc_norm_stderr\": 0.014611199329843777\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5497908783110934,\n\ \ \"acc_stderr\": 0.004964979120927565,\n \"acc_norm\": 0.7288388767177854,\n\ \ \"acc_norm_stderr\": 0.004436505187567003\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.2222222222222222,\n\ \ \"acc_stderr\": 0.035914440841969694,\n \"acc_norm\": 0.2222222222222222,\n\ \ \"acc_norm_stderr\": 0.035914440841969694\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.2894736842105263,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.2894736842105263,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.25660377358490566,\n \"acc_stderr\": 0.02688064788905197,\n\ \ \"acc_norm\": 0.25660377358490566,\n \"acc_norm_stderr\": 0.02688064788905197\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.24305555555555555,\n\ \ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.24305555555555555,\n\ \ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165085,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165085\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.20809248554913296,\n\ \ \"acc_stderr\": 0.030952890217749895,\n \"acc_norm\": 0.20809248554913296,\n\ \ \"acc_norm_stderr\": 0.030952890217749895\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.24509803921568626,\n \"acc_stderr\": 0.04280105837364395,\n\ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.04280105837364395\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.37,\n\ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.029513196625539355,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.029513196625539355\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.03999423879281336,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.03999423879281336\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.2689655172413793,\n \"acc_stderr\": 0.03695183311650232,\n\ \ \"acc_norm\": 0.2689655172413793,\n \"acc_norm_stderr\": 0.03695183311650232\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948365,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948365\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.20634920634920634,\n\ \ \"acc_stderr\": 0.0361960452412425,\n \"acc_norm\": 0.20634920634920634,\n\ \ \"acc_norm_stderr\": 0.0361960452412425\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.04093601807403326,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.04093601807403326\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.24838709677419354,\n\ \ \"acc_stderr\": 0.02458002892148101,\n \"acc_norm\": 0.24838709677419354,\n\ \ \"acc_norm_stderr\": 0.02458002892148101\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.1921182266009852,\n \"acc_stderr\": 0.02771931570961478,\n\ \ \"acc_norm\": 0.1921182266009852,\n \"acc_norm_stderr\": 0.02771931570961478\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206824,\n \"acc_norm\"\ : 0.29,\n \"acc_norm_stderr\": 0.045604802157206824\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.36363636363636365,\n \"acc_stderr\": 0.03756335775187896,\n\ \ \"acc_norm\": 0.36363636363636365,\n \"acc_norm_stderr\": 0.03756335775187896\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.2676767676767677,\n \"acc_stderr\": 0.03154449888270285,\n \"\ acc_norm\": 0.2676767676767677,\n \"acc_norm_stderr\": 0.03154449888270285\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.2538860103626943,\n \"acc_stderr\": 0.03141024780565319,\n\ \ \"acc_norm\": 0.2538860103626943,\n \"acc_norm_stderr\": 0.03141024780565319\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.24358974358974358,\n \"acc_stderr\": 0.02176373368417392,\n\ \ \"acc_norm\": 0.24358974358974358,\n \"acc_norm_stderr\": 0.02176373368417392\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.23333333333333334,\n \"acc_stderr\": 0.02578787422095932,\n \ \ \"acc_norm\": 0.23333333333333334,\n \"acc_norm_stderr\": 0.02578787422095932\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.23109243697478993,\n \"acc_stderr\": 0.027381406927868956,\n\ \ \"acc_norm\": 0.23109243697478993,\n \"acc_norm_stderr\": 0.027381406927868956\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.3155963302752294,\n \"acc_stderr\": 0.019926117513869662,\n \"\ acc_norm\": 0.3155963302752294,\n \"acc_norm_stderr\": 0.019926117513869662\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.2962962962962963,\n \"acc_stderr\": 0.031141447823536023,\n \"\ acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.031141447823536023\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.3333333333333333,\n \"acc_stderr\": 0.03308611113236435,\n \"\ acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.03308611113236435\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.3881856540084388,\n \"acc_stderr\": 0.0317229500433233,\n \ \ \"acc_norm\": 0.3881856540084388,\n \"acc_norm_stderr\": 0.0317229500433233\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.273542600896861,\n\ \ \"acc_stderr\": 0.029918586707798824,\n \"acc_norm\": 0.273542600896861,\n\ \ \"acc_norm_stderr\": 0.029918586707798824\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.2748091603053435,\n \"acc_stderr\": 0.039153454088478354,\n\ \ \"acc_norm\": 0.2748091603053435,\n \"acc_norm_stderr\": 0.039153454088478354\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.4132231404958678,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.4132231404958678,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04557239513497751,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04557239513497751\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.2147239263803681,\n \"acc_stderr\": 0.03226219377286774,\n\ \ \"acc_norm\": 0.2147239263803681,\n \"acc_norm_stderr\": 0.03226219377286774\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.29464285714285715,\n\ \ \"acc_stderr\": 0.04327040932578729,\n \"acc_norm\": 0.29464285714285715,\n\ \ \"acc_norm_stderr\": 0.04327040932578729\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690878,\n\ \ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690878\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.3504273504273504,\n\ \ \"acc_stderr\": 0.03125610824421881,\n \"acc_norm\": 0.3504273504273504,\n\ \ \"acc_norm_stderr\": 0.03125610824421881\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.2988505747126437,\n\ \ \"acc_stderr\": 0.01636925681509314,\n \"acc_norm\": 0.2988505747126437,\n\ \ \"acc_norm_stderr\": 0.01636925681509314\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.30057803468208094,\n \"acc_stderr\": 0.024685316867257796,\n\ \ \"acc_norm\": 0.30057803468208094,\n \"acc_norm_stderr\": 0.024685316867257796\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.3300653594771242,\n \"acc_stderr\": 0.026925654653615686,\n\ \ \"acc_norm\": 0.3300653594771242,\n \"acc_norm_stderr\": 0.026925654653615686\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.2733118971061093,\n\ \ \"acc_stderr\": 0.02531176597542612,\n \"acc_norm\": 0.2733118971061093,\n\ \ \"acc_norm_stderr\": 0.02531176597542612\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.3055555555555556,\n \"acc_stderr\": 0.025630824975621344,\n\ \ \"acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.025630824975621344\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.28368794326241137,\n \"acc_stderr\": 0.02689170942834396,\n \ \ \"acc_norm\": 0.28368794326241137,\n \"acc_norm_stderr\": 0.02689170942834396\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.28748370273794005,\n\ \ \"acc_stderr\": 0.011559337355708502,\n \"acc_norm\": 0.28748370273794005,\n\ \ \"acc_norm_stderr\": 0.011559337355708502\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\ \ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.28104575163398693,\n \"acc_stderr\": 0.018185218954318075,\n \ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.018185218954318075\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.4163265306122449,\n \"acc_stderr\": 0.03155782816556165,\n\ \ \"acc_norm\": 0.4163265306122449,\n \"acc_norm_stderr\": 0.03155782816556165\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.34328358208955223,\n\ \ \"acc_stderr\": 0.03357379665433431,\n \"acc_norm\": 0.34328358208955223,\n\ \ \"acc_norm_stderr\": 0.03357379665433431\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.2710843373493976,\n\ \ \"acc_stderr\": 0.034605799075530276,\n \"acc_norm\": 0.2710843373493976,\n\ \ \"acc_norm_stderr\": 0.034605799075530276\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.39766081871345027,\n \"acc_stderr\": 0.0375363895576169,\n\ \ \"acc_norm\": 0.39766081871345027,\n \"acc_norm_stderr\": 0.0375363895576169\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2460220318237454,\n\ \ \"mc1_stderr\": 0.015077219200662594,\n \"mc2\": 0.38838708556166845,\n\ \ \"mc2_stderr\": 0.014198737236851828\n }\n}\n```" repo_url: https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|arc:challenge|25_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hellaswag|10_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-13T10-12-42.075501.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-management|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-13T10-12-42.075501.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_13T10_12_42.075501 path: - '**/details_harness|truthfulqa:mc|0_2023-09-13T10-12-42.075501.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-13T10-12-42.075501.parquet' - config_name: results data_files: - split: 2023_09_13T10_12_42.075501 path: - results_2023-09-13T10-12-42.075501.parquet - split: latest path: - results_2023-09-13T10-12-42.075501.parquet --- # Dataset Card for Evaluation run of conceptofmind/Hermes-LLongMA-2-7b-8k ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [conceptofmind/Hermes-LLongMA-2-7b-8k](https://huggingface.co/conceptofmind/Hermes-LLongMA-2-7b-8k) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-13T10:12:42.075501](https://huggingface.co/datasets/open-llm-leaderboard/details_conceptofmind__Hermes-LLongMA-2-7b-8k/blob/main/results_2023-09-13T10-12-42.075501.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "acc": 0.2927085297989137, "acc_stderr": 0.03275517148401362, "acc_norm": 0.29622047886660385, "acc_norm_stderr": 0.032746678820457335, "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 }, "harness|arc:challenge|25": { "acc": 0.46928327645051193, "acc_stderr": 0.014583792546304038, "acc_norm": 0.4974402730375427, "acc_norm_stderr": 0.014611199329843777 }, "harness|hellaswag|10": { "acc": 0.5497908783110934, "acc_stderr": 0.004964979120927565, "acc_norm": 0.7288388767177854, "acc_norm_stderr": 0.004436505187567003 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.22, "acc_stderr": 0.04163331998932268, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932268 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2222222222222222, "acc_stderr": 0.035914440841969694, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.035914440841969694 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.2894736842105263, "acc_stderr": 0.03690677986137283, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.25660377358490566, "acc_stderr": 0.02688064788905197, "acc_norm": 0.25660377358490566, "acc_norm_stderr": 0.02688064788905197 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.24305555555555555, "acc_stderr": 0.0358687928008034, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.0358687928008034 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.23, "acc_stderr": 0.042295258468165085, "acc_norm": 0.23, "acc_norm_stderr": 0.042295258468165085 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.20809248554913296, "acc_stderr": 0.030952890217749895, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.030952890217749895 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364395, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364395 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2851063829787234, "acc_stderr": 0.029513196625539355, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.029513196625539355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.03999423879281336, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.03999423879281336 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2689655172413793, "acc_stderr": 0.03695183311650232, "acc_norm": 0.2689655172413793, "acc_norm_stderr": 0.03695183311650232 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.20634920634920634, "acc_stderr": 0.0361960452412425, "acc_norm": 0.20634920634920634, "acc_norm_stderr": 0.0361960452412425 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.24838709677419354, "acc_stderr": 0.02458002892148101, "acc_norm": 0.24838709677419354, "acc_norm_stderr": 0.02458002892148101 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.1921182266009852, "acc_stderr": 0.02771931570961478, "acc_norm": 0.1921182266009852, "acc_norm_stderr": 0.02771931570961478 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.29, "acc_stderr": 0.045604802157206824, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206824 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.36363636363636365, "acc_stderr": 0.03756335775187896, "acc_norm": 0.36363636363636365, "acc_norm_stderr": 0.03756335775187896 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.2676767676767677, "acc_stderr": 0.03154449888270285, "acc_norm": 0.2676767676767677, "acc_norm_stderr": 0.03154449888270285 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.2538860103626943, "acc_stderr": 0.03141024780565319, "acc_norm": 0.2538860103626943, "acc_norm_stderr": 0.03141024780565319 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.24358974358974358, "acc_stderr": 0.02176373368417392, "acc_norm": 0.24358974358974358, "acc_norm_stderr": 0.02176373368417392 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.23333333333333334, "acc_stderr": 0.02578787422095932, "acc_norm": 0.23333333333333334, "acc_norm_stderr": 0.02578787422095932 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.23109243697478993, "acc_stderr": 0.027381406927868956, "acc_norm": 0.23109243697478993, "acc_norm_stderr": 0.027381406927868956 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.3155963302752294, "acc_stderr": 0.019926117513869662, "acc_norm": 0.3155963302752294, "acc_norm_stderr": 0.019926117513869662 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.2962962962962963, "acc_stderr": 0.031141447823536023, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.031141447823536023 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.3333333333333333, "acc_stderr": 0.03308611113236435, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.03308611113236435 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.3881856540084388, "acc_stderr": 0.0317229500433233, "acc_norm": 0.3881856540084388, "acc_norm_stderr": 0.0317229500433233 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.273542600896861, "acc_stderr": 0.029918586707798824, "acc_norm": 0.273542600896861, "acc_norm_stderr": 0.029918586707798824 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.2748091603053435, "acc_stderr": 0.039153454088478354, "acc_norm": 0.2748091603053435, "acc_norm_stderr": 0.039153454088478354 }, "harness|hendrycksTest-international_law|5": { "acc": 0.4132231404958678, "acc_stderr": 0.04495087843548408, "acc_norm": 0.4132231404958678, "acc_norm_stderr": 0.04495087843548408 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04557239513497751, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04557239513497751 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.2147239263803681, "acc_stderr": 0.03226219377286774, "acc_norm": 0.2147239263803681, "acc_norm_stderr": 0.03226219377286774 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.29464285714285715, "acc_stderr": 0.04327040932578729, "acc_norm": 0.29464285714285715, "acc_norm_stderr": 0.04327040932578729 }, "harness|hendrycksTest-management|5": { "acc": 0.2524271844660194, "acc_stderr": 0.04301250399690878, "acc_norm": 0.2524271844660194, "acc_norm_stderr": 0.04301250399690878 }, "harness|hendrycksTest-marketing|5": { "acc": 0.3504273504273504, "acc_stderr": 0.03125610824421881, "acc_norm": 0.3504273504273504, "acc_norm_stderr": 0.03125610824421881 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.2988505747126437, "acc_stderr": 0.01636925681509314, "acc_norm": 0.2988505747126437, "acc_norm_stderr": 0.01636925681509314 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.30057803468208094, "acc_stderr": 0.024685316867257796, "acc_norm": 0.30057803468208094, "acc_norm_stderr": 0.024685316867257796 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.3300653594771242, "acc_stderr": 0.026925654653615686, "acc_norm": 0.3300653594771242, "acc_norm_stderr": 0.026925654653615686 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.2733118971061093, "acc_stderr": 0.02531176597542612, "acc_norm": 0.2733118971061093, "acc_norm_stderr": 0.02531176597542612 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.3055555555555556, "acc_stderr": 0.025630824975621344, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.025630824975621344 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.28368794326241137, "acc_stderr": 0.02689170942834396, "acc_norm": 0.28368794326241137, "acc_norm_stderr": 0.02689170942834396 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.28748370273794005, "acc_stderr": 0.011559337355708502, "acc_norm": 0.28748370273794005, "acc_norm_stderr": 0.011559337355708502 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.18382352941176472, "acc_stderr": 0.023529242185193106, "acc_norm": 0.18382352941176472, "acc_norm_stderr": 0.023529242185193106 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.28104575163398693, "acc_stderr": 0.018185218954318075, "acc_norm": 0.28104575163398693, "acc_norm_stderr": 0.018185218954318075 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.3, "acc_stderr": 0.04389311454644286, "acc_norm": 0.3, "acc_norm_stderr": 0.04389311454644286 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.4163265306122449, "acc_stderr": 0.03155782816556165, "acc_norm": 0.4163265306122449, "acc_norm_stderr": 0.03155782816556165 }, "harness|hendrycksTest-sociology|5": { "acc": 0.34328358208955223, "acc_stderr": 0.03357379665433431, "acc_norm": 0.34328358208955223, "acc_norm_stderr": 0.03357379665433431 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-virology|5": { "acc": 0.2710843373493976, "acc_stderr": 0.034605799075530276, "acc_norm": 0.2710843373493976, "acc_norm_stderr": 0.034605799075530276 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.39766081871345027, "acc_stderr": 0.0375363895576169, "acc_norm": 0.39766081871345027, "acc_norm_stderr": 0.0375363895576169 }, "harness|truthfulqa:mc|0": { "mc1": 0.2460220318237454, "mc1_stderr": 0.015077219200662594, "mc2": 0.38838708556166845, "mc2_stderr": 0.014198737236851828 } } ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]

open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B

--- pretty_name: Evaluation run of klyang/MentaLLaMA-chat-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [klyang/MentaLLaMA-chat-7B](https://huggingface.co/klyang/MentaLLaMA-chat-7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 1 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_klyang__MentaLLaMA-chat-7B\"\ ,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\ \ are the [latest results from run 2023-12-02T22:04:51.845916](https://huggingface.co/datasets/open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B/blob/main/results_2023-12-02T22-04-51.845916.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\": 0.16148597422289612,\n\ \ \"acc_stderr\": 0.010135959452134306\n },\n \"harness|gsm8k|5\":\ \ {\n \"acc\": 0.16148597422289612,\n \"acc_stderr\": 0.010135959452134306\n\ \ }\n}\n```" repo_url: https://huggingface.co/klyang/MentaLLaMA-chat-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_gsm8k_5 data_files: - split: 2023_12_02T22_04_51.845916 path: - '**/details_harness|gsm8k|5_2023-12-02T22-04-51.845916.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-02T22-04-51.845916.parquet' - config_name: results data_files: - split: 2023_12_02T22_04_51.845916 path: - results_2023-12-02T22-04-51.845916.parquet - split: latest path: - results_2023-12-02T22-04-51.845916.parquet --- # Dataset Card for Evaluation run of klyang/MentaLLaMA-chat-7B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/klyang/MentaLLaMA-chat-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 [klyang/MentaLLaMA-chat-7B](https://huggingface.co/klyang/MentaLLaMA-chat-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 1 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_klyang__MentaLLaMA-chat-7B", "harness_gsm8k_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-02T22:04:51.845916](https://huggingface.co/datasets/open-llm-leaderboard/details_klyang__MentaLLaMA-chat-7B/blob/main/results_2023-12-02T22-04-51.845916.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": 0.16148597422289612, "acc_stderr": 0.010135959452134306 }, "harness|gsm8k|5": { "acc": 0.16148597422289612, "acc_stderr": 0.010135959452134306 } } ``` ### 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]

edouard-rolland/volcanic-plumes

--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Volcanoes - Plumes - UAVs - Drone dataset_info: features: - name: image_id dtype: int64 - name: image dtype: image - name: width dtype: int32 - name: height dtype: int32 - name: objects sequence: - name: id dtype: int64 - name: area dtype: int64 - name: bbox sequence: float32 length: 4 - name: category dtype: class_label: names: '0': plume '1': summit splits: - name: train num_bytes: 29846342.127 num_examples: 1211 - name: validation num_bytes: 7311174 num_examples: 294 - name: test num_bytes: 12048406 num_examples: 456 download_size: 49324639 dataset_size: 49205922.127000004 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* license: mit language: - en --- <div align="center"> <img width=100% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/thumbnail.png"> </div> # Dataset Description The dataset presents labelled pictures of plumes and of the Fuego Summit in Guatemala. The data was collected by the University of Bristol Flight Lab in Guatemala from March 22 to April 3, 2019. The drone used for this purpose was a Skywalker X8, equipped with a Pixhawk onboard computer running ArduPlane 3.7.1 and a Raspberry Pi 3B+ for mission management and communication with the ground station. The drone was also equipped of a GoPro Hero 9. # Citation ``` @inproceedings{rolland2024volcanic, author = {Edouard G. A. Rolland and Kasper A. R. Grøntved and Anders Lyhne Christensen and Matthew Watson and Tom Richardson}, title = { Autonomous {UAV} Volcanic Plume Sampling Based on Machine Vision and Path Planning}, year = { 2024 }, note = {Under review}, } ``` # Acknowledgement This work is supported by the WildDrone MSCA Doctoral Network funded by EU Horizon Europe under grant agreement no. 101071224, the Innovation Fund Denmark for the project DIREC (9142-00001B), and by the Engineering & Physical Sciences Research Council (UK) through the CASCADE (Complex Autonomous aircraft Systems Configuration, Analysis and Design Exploratory) programme grant (EP/R009953/1). # Dataset Labels ``` ['plume', 'summit'] ``` # Example of Labelled Images <div align="center"> <<img width=50% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/val_batch0_labels.jpg"> </div> # Number of Images ```json {'valid': 294, 'test': 456, 'train': 1211} ``` # Example of Application The dataset was used to train a YOLOv8 neural network. More details can be found in the paper mentioned in the citation section. The following <a href="https://www.youtube.com/watch?v=pSGYUPancfA">video</a> presents the model output for an entire flight. # How to Use - Install [datasets](https://pypi.org/project/datasets/): ```bash pip install datasets ``` - Load the dataset: ```python from datasets import load_dataset ds = load_dataset("edouard-rolland/volcanic-plumes", name="full") example = ds['train'][0] ``` # License MIT

Cohere/miracl-sw-queries-22-12

--- annotations_creators: - expert-generated language: - sw multilinguality: - multilingual size_categories: [] source_datasets: [] tags: [] task_categories: - text-retrieval license: - apache-2.0 task_ids: - document-retrieval --- # MIRACL (sw) embedded with cohere.ai `multilingual-22-12` encoder We encoded the [MIRACL dataset](https://huggingface.co/miracl) using the [cohere.ai](https://txt.cohere.ai/multilingual/) `multilingual-22-12` embedding model. The query embeddings can be found in [Cohere/miracl-sw-queries-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-queries-22-12) and the corpus embeddings can be found in [Cohere/miracl-sw-corpus-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-corpus-22-12). For the orginal datasets, see [miracl/miracl](https://huggingface.co/datasets/miracl/miracl) and [miracl/miracl-corpus](https://huggingface.co/datasets/miracl/miracl-corpus). Dataset info: > MIRACL 🌍🙌🌏 (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual retrieval dataset that focuses on search across 18 different languages, which collectively encompass over three billion native speakers around the world. > > The corpus for each language is prepared from a Wikipedia dump, where we keep only the plain text and discard images, tables, etc. Each article is segmented into multiple passages using WikiExtractor based on natural discourse units (e.g., `\n\n` in the wiki markup). Each of these passages comprises a "document" or unit of retrieval. We preserve the Wikipedia article title of each passage. ## Embeddings We compute for `title+" "+text` the embeddings using our `multilingual-22-12` embedding model, a state-of-the-art model that works for semantic search in 100 languages. If you want to learn more about this model, have a look at [cohere.ai multilingual embedding model](https://txt.cohere.ai/multilingual/). ## Loading the dataset In [miracl-sw-corpus-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-corpus-22-12) we provide the corpus embeddings. Note, depending on the selected split, the respective files can be quite large. You can either load the dataset like this: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train") ``` Or you can also stream it without downloading it before: ```python from datasets import load_dataset docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train", streaming=True) for doc in docs: docid = doc['docid'] title = doc['title'] text = doc['text'] emb = doc['emb'] ``` ## Search Have a look at [miracl-sw-queries-22-12](https://huggingface.co/datasets/Cohere/miracl-sw-queries-22-12) where we provide the query embeddings for the MIRACL dataset. To search in the documents, you must use **dot-product**. And then compare this query embeddings either with a vector database (recommended) or directly computing the dot product. A full search example: ```python # Attention! For large datasets, this requires a lot of memory to store # all document embeddings and to compute the dot product scores. # Only use this for smaller datasets. For large datasets, use a vector DB from datasets import load_dataset import torch #Load documents + embeddings docs = load_dataset(f"Cohere/miracl-sw-corpus-22-12", split="train") doc_embeddings = torch.tensor(docs['emb']) # Load queries queries = load_dataset(f"Cohere/miracl-sw-queries-22-12", split="dev") # Select the first query as example qid = 0 query = queries[qid] query_embedding = torch.tensor(queries['emb']) # Compute dot score between query embedding and document embeddings dot_scores = torch.mm(query_embedding, doc_embeddings.transpose(0, 1)) top_k = torch.topk(dot_scores, k=3) # Print results print("Query:", query['query']) for doc_id in top_k.indices[0].tolist(): print(docs[doc_id]['title']) print(docs[doc_id]['text']) ``` You can get embeddings for new queries using our API: ```python #Run: pip install cohere import cohere co = cohere.Client(f"{api_key}") # You should add your cohere API Key here :)) texts = ['my search query'] response = co.embed(texts=texts, model='multilingual-22-12') query_embedding = response.embeddings[0] # Get the embedding for the first text ``` ## Performance In the following table we compare the cohere multilingual-22-12 model with Elasticsearch version 8.6.0 lexical search (title and passage indexed as independent fields). Note that Elasticsearch doesn't support all languages that are part of the MIRACL dataset. We compute nDCG@10 (a ranking based loss), as well as hit@3: Is at least one relevant document in the top-3 results. We find that hit@3 is easier to interpret, as it presents the number of queries for which a relevant document is found among the top-3 results. Note: MIRACL only annotated a small fraction of passages (10 per query) for relevancy. Especially for larger Wikipedias (like English), we often found many more relevant passages. This is know as annotation holes. Real nDCG@10 and hit@3 performance is likely higher than depicted. | Model | cohere multilingual-22-12 nDCG@10 | cohere multilingual-22-12 hit@3 | ES 8.6.0 nDCG@10 | ES 8.6.0 acc@3 | |---|---|---|---|---| | miracl-ar | 64.2 | 75.2 | 46.8 | 56.2 | | miracl-bn | 61.5 | 75.7 | 49.2 | 60.1 | | miracl-de | 44.4 | 60.7 | 19.6 | 29.8 | | miracl-en | 44.6 | 62.2 | 30.2 | 43.2 | | miracl-es | 47.0 | 74.1 | 27.0 | 47.2 | | miracl-fi | 63.7 | 76.2 | 51.4 | 61.6 | | miracl-fr | 46.8 | 57.1 | 17.0 | 21.6 | | miracl-hi | 50.7 | 62.9 | 41.0 | 48.9 | | miracl-id | 44.8 | 63.8 | 39.2 | 54.7 | | miracl-ru | 49.2 | 66.9 | 25.4 | 36.7 | | **Avg** | 51.7 | 67.5 | 34.7 | 46.0 | Further languages (not supported by Elasticsearch): | Model | cohere multilingual-22-12 nDCG@10 | cohere multilingual-22-12 hit@3 | |---|---|---| | miracl-fa | 44.8 | 53.6 | | miracl-ja | 49.0 | 61.0 | | miracl-ko | 50.9 | 64.8 | | miracl-sw | 61.4 | 74.5 | | miracl-te | 67.8 | 72.3 | | miracl-th | 60.2 | 71.9 | | miracl-yo | 56.4 | 62.2 | | miracl-zh | 43.8 | 56.5 | | **Avg** | 54.3 | 64.6 |

open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0

--- pretty_name: Evaluation run of azarafrooz/gemma-2b-it-nlai-v0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [azarafrooz/gemma-2b-it-nlai-v0](https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0)\ \ 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_azarafrooz__gemma-2b-it-nlai-v0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-15T12:20:29.148062](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0/blob/main/results_2024-04-15T12-20-29.148062.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\": 0.37660169444969677,\n\ \ \"acc_stderr\": 0.03380673348549725,\n \"acc_norm\": 0.3811167415748182,\n\ \ \"acc_norm_stderr\": 0.03461538621374684,\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.015866346401384308,\n \"mc2\": 0.45797553398869045,\n\ \ \"mc2_stderr\": 0.015928281785783458\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.4052901023890785,\n \"acc_stderr\": 0.014346869060229327,\n\ \ \"acc_norm\": 0.4402730375426621,\n \"acc_norm_stderr\": 0.014506769524804246\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.48137821151165106,\n\ \ \"acc_stderr\": 0.004986319587524964,\n \"acc_norm\": 0.6266679944234216,\n\ \ \"acc_norm_stderr\": 0.004827006520802888\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.3851851851851852,\n\ \ \"acc_stderr\": 0.042039210401562783,\n \"acc_norm\": 0.3851851851851852,\n\ \ \"acc_norm_stderr\": 0.042039210401562783\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.3355263157894737,\n \"acc_stderr\": 0.03842498559395269,\n\ \ \"acc_norm\": 0.3355263157894737,\n \"acc_norm_stderr\": 0.03842498559395269\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.49,\n\ \ \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\": 0.49,\n \ \ \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.4226415094339623,\n \"acc_stderr\": 0.030402331445769537,\n\ \ \"acc_norm\": 0.4226415094339623,\n \"acc_norm_stderr\": 0.030402331445769537\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3472222222222222,\n\ \ \"acc_stderr\": 0.039812405437178615,\n \"acc_norm\": 0.3472222222222222,\n\ \ \"acc_norm_stderr\": 0.039812405437178615\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.3,\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\": 0.26,\n \"acc_stderr\": 0.0440844002276808,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.0440844002276808\n },\n\ \ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3583815028901734,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.3583815028901734,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617747,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617747\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.45,\n \"\ acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.3574468085106383,\n \"acc_stderr\": 0.03132941789476425,\n\ \ \"acc_norm\": 0.3574468085106383,\n \"acc_norm_stderr\": 0.03132941789476425\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2807017543859649,\n\ \ \"acc_stderr\": 0.042270544512322,\n \"acc_norm\": 0.2807017543859649,\n\ \ \"acc_norm_stderr\": 0.042270544512322\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4689655172413793,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.4689655172413793,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643895,\n \"\ acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643895\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.25396825396825395,\n\ \ \"acc_stderr\": 0.03893259610604674,\n \"acc_norm\": 0.25396825396825395,\n\ \ \"acc_norm_stderr\": 0.03893259610604674\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.3193548387096774,\n\ \ \"acc_stderr\": 0.026522709674667765,\n \"acc_norm\": 0.3193548387096774,\n\ \ \"acc_norm_stderr\": 0.026522709674667765\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.29064039408866993,\n \"acc_stderr\": 0.0319474007226554,\n\ \ \"acc_norm\": 0.29064039408866993,\n \"acc_norm_stderr\": 0.0319474007226554\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\"\ : 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.45454545454545453,\n \"acc_stderr\": 0.03888176921674098,\n\ \ \"acc_norm\": 0.45454545454545453,\n \"acc_norm_stderr\": 0.03888176921674098\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.4595959595959596,\n \"acc_stderr\": 0.035507024651313425,\n \"\ acc_norm\": 0.4595959595959596,\n \"acc_norm_stderr\": 0.035507024651313425\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.47150259067357514,\n \"acc_stderr\": 0.03602573571288442,\n\ \ \"acc_norm\": 0.47150259067357514,\n \"acc_norm_stderr\": 0.03602573571288442\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.33076923076923076,\n \"acc_stderr\": 0.023854795680971135,\n\ \ \"acc_norm\": 0.33076923076923076,\n \"acc_norm_stderr\": 0.023854795680971135\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2,\n \"acc_stderr\": 0.024388430433987664,\n \"acc_norm\"\ : 0.2,\n \"acc_norm_stderr\": 0.024388430433987664\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\ : {\n \"acc\": 0.3403361344537815,\n \"acc_stderr\": 0.030778057422931673,\n\ \ \"acc_norm\": 0.3403361344537815,\n \"acc_norm_stderr\": 0.030778057422931673\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360384,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360384\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.5027522935779817,\n \"acc_stderr\": 0.021436998359765317,\n \"\ acc_norm\": 0.5027522935779817,\n \"acc_norm_stderr\": 0.021436998359765317\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.19907407407407407,\n \"acc_stderr\": 0.027232298462690218,\n \"\ acc_norm\": 0.19907407407407407,\n \"acc_norm_stderr\": 0.027232298462690218\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.4166666666666667,\n \"acc_stderr\": 0.03460228327239171,\n \"\ acc_norm\": 0.4166666666666667,\n \"acc_norm_stderr\": 0.03460228327239171\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.5189873417721519,\n \"acc_stderr\": 0.03252375148090448,\n \ \ \"acc_norm\": 0.5189873417721519,\n \"acc_norm_stderr\": 0.03252375148090448\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.38565022421524664,\n\ \ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.38565022421524664,\n\ \ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.4198473282442748,\n \"acc_stderr\": 0.043285772152629715,\n\ \ \"acc_norm\": 0.4198473282442748,\n \"acc_norm_stderr\": 0.043285772152629715\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5206611570247934,\n \"acc_stderr\": 0.04560456086387235,\n \"\ acc_norm\": 0.5206611570247934,\n \"acc_norm_stderr\": 0.04560456086387235\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4722222222222222,\n\ \ \"acc_stderr\": 0.04826217294139894,\n \"acc_norm\": 0.4722222222222222,\n\ \ \"acc_norm_stderr\": 0.04826217294139894\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.36809815950920244,\n \"acc_stderr\": 0.03789213935838396,\n\ \ \"acc_norm\": 0.36809815950920244,\n \"acc_norm_stderr\": 0.03789213935838396\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.33035714285714285,\n\ \ \"acc_stderr\": 0.044642857142857116,\n \"acc_norm\": 0.33035714285714285,\n\ \ \"acc_norm_stderr\": 0.044642857142857116\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.44660194174757284,\n \"acc_stderr\": 0.04922424153458933,\n\ \ \"acc_norm\": 0.44660194174757284,\n \"acc_norm_stderr\": 0.04922424153458933\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.594017094017094,\n\ \ \"acc_stderr\": 0.03217180182641086,\n \"acc_norm\": 0.594017094017094,\n\ \ \"acc_norm_stderr\": 0.03217180182641086\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.4648786717752235,\n\ \ \"acc_stderr\": 0.017835798806290642,\n \"acc_norm\": 0.4648786717752235,\n\ \ \"acc_norm_stderr\": 0.017835798806290642\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\": 0.24581005586592178,\n\ \ \"acc_stderr\": 0.014400296429225624,\n \"acc_norm\": 0.24581005586592178,\n\ \ \"acc_norm_stderr\": 0.014400296429225624\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.4444444444444444,\n \"acc_stderr\": 0.028452639985088003,\n\ \ \"acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.028452639985088003\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.40514469453376206,\n\ \ \"acc_stderr\": 0.02788238379132596,\n \"acc_norm\": 0.40514469453376206,\n\ \ \"acc_norm_stderr\": 0.02788238379132596\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.41358024691358025,\n \"acc_stderr\": 0.027402042040269952,\n\ \ \"acc_norm\": 0.41358024691358025,\n \"acc_norm_stderr\": 0.027402042040269952\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3049645390070922,\n \"acc_stderr\": 0.027464708442022135,\n \ \ \"acc_norm\": 0.3049645390070922,\n \"acc_norm_stderr\": 0.027464708442022135\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.31747066492829207,\n\ \ \"acc_stderr\": 0.011888892068809312,\n \"acc_norm\": 0.31747066492829207,\n\ \ \"acc_norm_stderr\": 0.011888892068809312\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.20220588235294118,\n \"acc_stderr\": 0.024398192986654924,\n\ \ \"acc_norm\": 0.20220588235294118,\n \"acc_norm_stderr\": 0.024398192986654924\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.37745098039215685,\n \"acc_stderr\": 0.019610851474880286,\n \ \ \"acc_norm\": 0.37745098039215685,\n \"acc_norm_stderr\": 0.019610851474880286\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.41818181818181815,\n\ \ \"acc_stderr\": 0.0472457740573157,\n \"acc_norm\": 0.41818181818181815,\n\ \ \"acc_norm_stderr\": 0.0472457740573157\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.46938775510204084,\n \"acc_stderr\": 0.031949171367580624,\n\ \ \"acc_norm\": 0.46938775510204084,\n \"acc_norm_stderr\": 0.031949171367580624\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.4427860696517413,\n\ \ \"acc_stderr\": 0.03512310964123936,\n \"acc_norm\": 0.4427860696517413,\n\ \ \"acc_norm_stderr\": 0.03512310964123936\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.41566265060240964,\n\ \ \"acc_stderr\": 0.038367221765980515,\n \"acc_norm\": 0.41566265060240964,\n\ \ \"acc_norm_stderr\": 0.038367221765980515\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.4327485380116959,\n \"acc_stderr\": 0.03799978644370607,\n\ \ \"acc_norm\": 0.4327485380116959,\n \"acc_norm_stderr\": 0.03799978644370607\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.015866346401384308,\n \"mc2\": 0.45797553398869045,\n\ \ \"mc2_stderr\": 0.015928281785783458\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6132596685082873,\n \"acc_stderr\": 0.013687214761883042\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.053828658074298714,\n \ \ \"acc_stderr\": 0.006216328640238136\n }\n}\n```" repo_url: https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0 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_04_15T12_20_29.148062 path: - '**/details_harness|arc:challenge|25_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-04-15T12-20-29.148062.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|gsm8k|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hellaswag|10_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-15T12-20-29.148062.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-management|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-virology|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T12-20-29.148062.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|truthfulqa:mc|0_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-04-15T12-20-29.148062.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_15T12_20_29.148062 path: - '**/details_harness|winogrande|5_2024-04-15T12-20-29.148062.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-04-15T12-20-29.148062.parquet' - config_name: results data_files: - split: 2024_04_15T12_20_29.148062 path: - results_2024-04-15T12-20-29.148062.parquet - split: latest path: - results_2024-04-15T12-20-29.148062.parquet --- # Dataset Card for Evaluation run of azarafrooz/gemma-2b-it-nlai-v0  Dataset automatically created during the evaluation run of model [azarafrooz/gemma-2b-it-nlai-v0](https://huggingface.co/azarafrooz/gemma-2b-it-nlai-v0) 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_azarafrooz__gemma-2b-it-nlai-v0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-15T12:20:29.148062](https://huggingface.co/datasets/open-llm-leaderboard/details_azarafrooz__gemma-2b-it-nlai-v0/blob/main/results_2024-04-15T12-20-29.148062.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": 0.37660169444969677, "acc_stderr": 0.03380673348549725, "acc_norm": 0.3811167415748182, "acc_norm_stderr": 0.03461538621374684, "mc1": 0.28886168910648713, "mc1_stderr": 0.015866346401384308, "mc2": 0.45797553398869045, "mc2_stderr": 0.015928281785783458 }, "harness|arc:challenge|25": { "acc": 0.4052901023890785, "acc_stderr": 0.014346869060229327, "acc_norm": 0.4402730375426621, "acc_norm_stderr": 0.014506769524804246 }, "harness|hellaswag|10": { "acc": 0.48137821151165106, "acc_stderr": 0.004986319587524964, "acc_norm": 0.6266679944234216, "acc_norm_stderr": 0.004827006520802888 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3851851851851852, "acc_stderr": 0.042039210401562783, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3355263157894737, "acc_stderr": 0.03842498559395269, "acc_norm": 0.3355263157894737, "acc_norm_stderr": 0.03842498559395269 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956913, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956913 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4226415094339623, "acc_stderr": 0.030402331445769537, "acc_norm": 0.4226415094339623, "acc_norm_stderr": 0.030402331445769537 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3472222222222222, "acc_stderr": 0.039812405437178615, "acc_norm": 0.3472222222222222, "acc_norm_stderr": 0.039812405437178615 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "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": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3583815028901734, "acc_stderr": 0.036563436533531585, "acc_norm": 0.3583815028901734, "acc_norm_stderr": 0.036563436533531585 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617747, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617747 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3574468085106383, "acc_stderr": 0.03132941789476425, "acc_norm": 0.3574468085106383, "acc_norm_stderr": 0.03132941789476425 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.25132275132275134, "acc_stderr": 0.022340482339643895, "acc_norm": 0.25132275132275134, "acc_norm_stderr": 0.022340482339643895 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3193548387096774, "acc_stderr": 0.026522709674667765, "acc_norm": 0.3193548387096774, "acc_norm_stderr": 0.026522709674667765 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.29064039408866993, "acc_stderr": 0.0319474007226554, "acc_norm": 0.29064039408866993, "acc_norm_stderr": 0.0319474007226554 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.45454545454545453, "acc_stderr": 0.03888176921674098, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.03888176921674098 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4595959595959596, "acc_stderr": 0.035507024651313425, "acc_norm": 0.4595959595959596, "acc_norm_stderr": 0.035507024651313425 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.47150259067357514, "acc_stderr": 0.03602573571288442, "acc_norm": 0.47150259067357514, "acc_norm_stderr": 0.03602573571288442 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.33076923076923076, "acc_stderr": 0.023854795680971135, "acc_norm": 0.33076923076923076, "acc_norm_stderr": 0.023854795680971135 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2, "acc_stderr": 0.024388430433987664, "acc_norm": 0.2, "acc_norm_stderr": 0.024388430433987664 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.3403361344537815, "acc_stderr": 0.030778057422931673, "acc_norm": 0.3403361344537815, "acc_norm_stderr": 0.030778057422931673 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.26490066225165565, "acc_stderr": 0.03603038545360384, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.03603038545360384 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.5027522935779817, "acc_stderr": 0.021436998359765317, "acc_norm": 0.5027522935779817, "acc_norm_stderr": 0.021436998359765317 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.19907407407407407, "acc_stderr": 0.027232298462690218, "acc_norm": 0.19907407407407407, "acc_norm_stderr": 0.027232298462690218 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.4166666666666667, "acc_stderr": 0.03460228327239171, "acc_norm": 0.4166666666666667, "acc_norm_stderr": 0.03460228327239171 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.5189873417721519, "acc_stderr": 0.03252375148090448, "acc_norm": 0.5189873417721519, "acc_norm_stderr": 0.03252375148090448 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.38565022421524664, "acc_stderr": 0.03266842214289201, "acc_norm": 0.38565022421524664, "acc_norm_stderr": 0.03266842214289201 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.4198473282442748, "acc_stderr": 0.043285772152629715, "acc_norm": 0.4198473282442748, "acc_norm_stderr": 0.043285772152629715 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5206611570247934, "acc_stderr": 0.04560456086387235, "acc_norm": 0.5206611570247934, "acc_norm_stderr": 0.04560456086387235 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04826217294139894, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04826217294139894 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.36809815950920244, "acc_stderr": 0.03789213935838396, "acc_norm": 0.36809815950920244, "acc_norm_stderr": 0.03789213935838396 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.33035714285714285, "acc_stderr": 0.044642857142857116, "acc_norm": 0.33035714285714285, "acc_norm_stderr": 0.044642857142857116 }, "harness|hendrycksTest-management|5": { "acc": 0.44660194174757284, "acc_stderr": 0.04922424153458933, "acc_norm": 0.44660194174757284, "acc_norm_stderr": 0.04922424153458933 }, "harness|hendrycksTest-marketing|5": { "acc": 0.594017094017094, "acc_stderr": 0.03217180182641086, "acc_norm": 0.594017094017094, "acc_norm_stderr": 0.03217180182641086 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.4648786717752235, "acc_stderr": 0.017835798806290642, "acc_norm": 0.4648786717752235, "acc_norm_stderr": 0.017835798806290642 }, "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": 0.24581005586592178, "acc_stderr": 0.014400296429225624, "acc_norm": 0.24581005586592178, "acc_norm_stderr": 0.014400296429225624 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.4444444444444444, "acc_stderr": 0.028452639985088003, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.028452639985088003 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.40514469453376206, "acc_stderr": 0.02788238379132596, "acc_norm": 0.40514469453376206, "acc_norm_stderr": 0.02788238379132596 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.41358024691358025, "acc_stderr": 0.027402042040269952, "acc_norm": 0.41358024691358025, "acc_norm_stderr": 0.027402042040269952 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3049645390070922, "acc_stderr": 0.027464708442022135, "acc_norm": 0.3049645390070922, "acc_norm_stderr": 0.027464708442022135 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.31747066492829207, "acc_stderr": 0.011888892068809312, "acc_norm": 0.31747066492829207, "acc_norm_stderr": 0.011888892068809312 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.20220588235294118, "acc_stderr": 0.024398192986654924, "acc_norm": 0.20220588235294118, "acc_norm_stderr": 0.024398192986654924 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.37745098039215685, "acc_stderr": 0.019610851474880286, "acc_norm": 0.37745098039215685, "acc_norm_stderr": 0.019610851474880286 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.41818181818181815, "acc_stderr": 0.0472457740573157, "acc_norm": 0.41818181818181815, "acc_norm_stderr": 0.0472457740573157 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.46938775510204084, "acc_stderr": 0.031949171367580624, "acc_norm": 0.46938775510204084, "acc_norm_stderr": 0.031949171367580624 }, "harness|hendrycksTest-sociology|5": { "acc": 0.4427860696517413, "acc_stderr": 0.03512310964123936, "acc_norm": 0.4427860696517413, "acc_norm_stderr": 0.03512310964123936 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-virology|5": { "acc": 0.41566265060240964, "acc_stderr": 0.038367221765980515, "acc_norm": 0.41566265060240964, "acc_norm_stderr": 0.038367221765980515 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.4327485380116959, "acc_stderr": 0.03799978644370607, "acc_norm": 0.4327485380116959, "acc_norm_stderr": 0.03799978644370607 }, "harness|truthfulqa:mc|0": { "mc1": 0.28886168910648713, "mc1_stderr": 0.015866346401384308, "mc2": 0.45797553398869045, "mc2_stderr": 0.015928281785783458 }, "harness|winogrande|5": { "acc": 0.6132596685082873, "acc_stderr": 0.013687214761883042 }, "harness|gsm8k|5": { "acc": 0.053828658074298714, "acc_stderr": 0.006216328640238136 } } ``` ## 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]

mask-distilled-onesec-cv12-each-chunk-uniq/chunk_55

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1315757524.0 num_examples: 258397 download_size: 1345022572 dataset_size: 1315757524.0 --- # Dataset Card for "chunk_55" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

hypno-ai/margiela-style

--- license: apache-2.0 ---

mrzbrt/test_audioset

--- dataset_info: features: - name: audio dtype: audio splits: - name: train num_bytes: 1267533455.0 num_examples: 401 download_size: 1227173992 dataset_size: 1267533455.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

Mitsuki-Sakamoto/alpaca_farm-deberta-re-pref-64-_fil_self_1.4b_bo16_2_64_mix_50_kl_0.1_prm_410m_thr_1.0_seed_2

--- dataset_info: config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string - name: index dtype: int64 - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: filtered_epoch dtype: int64 - name: gen_reward dtype: float64 - name: gen_response dtype: string splits: - name: epoch_0 num_bytes: 43744390 num_examples: 18928 - name: epoch_1 num_bytes: 43853451 num_examples: 18928 - name: epoch_2 num_bytes: 43703566 num_examples: 18928 - name: epoch_3 num_bytes: 43575131 num_examples: 18928 - name: epoch_4 num_bytes: 43518590 num_examples: 18928 - name: epoch_5 num_bytes: 43495671 num_examples: 18928 - name: epoch_6 num_bytes: 43474824 num_examples: 18928 - name: epoch_7 num_bytes: 43481960 num_examples: 18928 - name: epoch_8 num_bytes: 43468743 num_examples: 18928 - name: epoch_9 num_bytes: 43462697 num_examples: 18928 download_size: 278955072 dataset_size: 435779023 configs: - config_name: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500 data_files: - split: epoch_0 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_0-* - split: epoch_1 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_1-* - split: epoch_2 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_2-* - split: epoch_3 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_3-* - split: epoch_4 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_4-* - split: epoch_5 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_5-* - split: epoch_6 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_6-* - split: epoch_7 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_7-* - split: epoch_8 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_8-* - split: epoch_9 path: alpaca_instructions-pythia-1.4b_alpaca_farm_instructions_sft_constant_pa-checkpoint-7500/epoch_9-* ---

tanmay2798/codedataset

--- license: llama2 --- annotations_creators: - no-annotation language: - en language_creators: - expert-generated license: - other multilinguality: - monolingual pretty_name: codedataset size_categories: - n<1K source_datasets: - original tags: [] task_categories: - text2text-generation - text-generation - question-answering task_ids: - explanation-generation - open-book-qa - closed-book-qa - abstractive-qa - language-modeling - dialogue-modeling - extractive-qa

LorenzH/juliet_test_suite_c_1_3

--- license: cc0-1.0 task_categories: - text-classification pretty_name: Juliet Test Suite 1.3 size_categories: - 10K<n<100K --- # Dataset Card for the Juliet Test Suite 1.3 ### Dataset Summary This Datasets contains all test cases from the NIST's [Juliet test suite](https://samate.nist.gov/SARD/test-suites/112) for the C and C++ programming languages. The dataset contains a benign and a defective implementation of each sample, which have been extracting by means of the OMITGOOD and OMITBAD preprocessor macros of the Juliet test suite. ### Supported Tasks and Leaderboards Software defect prediction, code clone detection. ### Languages The C and C++ programming languages. ## Dataset Structure ### Data Instances ### Data Fields | index | name | type | description | | --- | --- | --- | --- | | 0 | index | int | The index of each sample in the dataset. | | 1 | filename | str | The path to the test case including the file name. | | 2 | class | int | The class of the defect, i.e., the collection by CWE number from which the sample was taken. | | 3 | good | str | The code of the benign implementation. | | 4 | bad | str | The code of the defective implementation. | ### Data Splits | type | size | |------|------| | train | 80706 cases | | test | 20177 cases | ## Dataset Creation ### Curation Rationale ### Source Data https://samate.nist.gov/SARD/test-suites/112 #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations The Juliet test suite is a synthetic dataset, meaning that all samples have been manually crafted. Therefore they are not entirely representative of actual software defects found in the wild. A classifier trained on these samples may suffer from decreased predictive performance, leading to gross misclassifactions. Critical software defects may therefore be overlooked, when such model is applied in a realistic environment. ## Additional Information ### Dataset Curators https://github.com/lorenz9314/ ### Licensing Information ### Citation Information ### Contributions

open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu

--- pretty_name: Evaluation run of Charlie911/MultiLoRA-mmlu dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Charlie911/MultiLoRA-mmlu](https://huggingface.co/Charlie911/MultiLoRA-mmlu)\ \ 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_Charlie911__MultiLoRA-mmlu\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-02T00:16:37.919745](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu/blob/main/results_2024-02-02T00-16-37.919745.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\": 0.49682393519091933,\n\ \ \"acc_stderr\": 0.034234549326781244,\n \"acc_norm\": 0.5024513039750834,\n\ \ \"acc_norm_stderr\": 0.03499839555197597,\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.5020042655317223,\n\ \ \"mc2_stderr\": 0.015409102519026984\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.49658703071672355,\n \"acc_stderr\": 0.014611050403244077,\n\ \ \"acc_norm\": 0.5238907849829352,\n \"acc_norm_stderr\": 0.014594701798071654\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5803624775941048,\n\ \ \"acc_stderr\": 0.004924910433106353,\n \"acc_norm\": 0.7720573590918144,\n\ \ \"acc_norm_stderr\": 0.0041864806453155625\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\": 0.45185185185185184,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.45185185185185184,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.506578947368421,\n \"acc_stderr\": 0.040685900502249704,\n\ \ \"acc_norm\": 0.506578947368421,\n \"acc_norm_stderr\": 0.040685900502249704\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5169811320754717,\n \"acc_stderr\": 0.030755120364119905,\n\ \ \"acc_norm\": 0.5169811320754717,\n \"acc_norm_stderr\": 0.030755120364119905\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04181210050035455,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04181210050035455\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\": 0.4,\n\ \ \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.43352601156069365,\n\ \ \"acc_stderr\": 0.03778621079092055,\n \"acc_norm\": 0.43352601156069365,\n\ \ \"acc_norm_stderr\": 0.03778621079092055\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.16666666666666666,\n \"acc_stderr\": 0.03708284662416542,\n\ \ \"acc_norm\": 0.16666666666666666,\n \"acc_norm_stderr\": 0.03708284662416542\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.65,\n \"acc_stderr\": 0.047937248544110196,\n \"acc_norm\": 0.65,\n\ \ \"acc_norm_stderr\": 0.047937248544110196\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.43829787234042555,\n \"acc_stderr\": 0.032436186361081004,\n\ \ \"acc_norm\": 0.43829787234042555,\n \"acc_norm_stderr\": 0.032436186361081004\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2894736842105263,\n\ \ \"acc_stderr\": 0.04266339443159393,\n \"acc_norm\": 0.2894736842105263,\n\ \ \"acc_norm_stderr\": 0.04266339443159393\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4689655172413793,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.4689655172413793,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2857142857142857,\n \"acc_stderr\": 0.023266512213730578,\n \"\ acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.023266512213730578\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3253968253968254,\n\ \ \"acc_stderr\": 0.04190596438871136,\n \"acc_norm\": 0.3253968253968254,\n\ \ \"acc_norm_stderr\": 0.04190596438871136\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\": 0.535483870967742,\n\ \ \"acc_stderr\": 0.02837228779796293,\n \"acc_norm\": 0.535483870967742,\n\ \ \"acc_norm_stderr\": 0.02837228779796293\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.39901477832512317,\n \"acc_stderr\": 0.03445487686264715,\n\ \ \"acc_norm\": 0.39901477832512317,\n \"acc_norm_stderr\": 0.03445487686264715\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512567,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512567\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5909090909090909,\n \"acc_stderr\": 0.03502975799413007,\n \"\ acc_norm\": 0.5909090909090909,\n \"acc_norm_stderr\": 0.03502975799413007\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.7046632124352331,\n \"acc_stderr\": 0.03292296639155141,\n\ \ \"acc_norm\": 0.7046632124352331,\n \"acc_norm_stderr\": 0.03292296639155141\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4717948717948718,\n \"acc_stderr\": 0.025310639254933893,\n\ \ \"acc_norm\": 0.4717948717948718,\n \"acc_norm_stderr\": 0.025310639254933893\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275805,\n \ \ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275805\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.4369747899159664,\n \"acc_stderr\": 0.03221943636566196,\n \ \ \"acc_norm\": 0.4369747899159664,\n \"acc_norm_stderr\": 0.03221943636566196\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969653,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969653\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.6770642201834862,\n\ \ \"acc_stderr\": 0.02004811592341531,\n \"acc_norm\": 0.6770642201834862,\n\ \ \"acc_norm_stderr\": 0.02004811592341531\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.39351851851851855,\n \"acc_stderr\": 0.03331747876370312,\n\ \ \"acc_norm\": 0.39351851851851855,\n \"acc_norm_stderr\": 0.03331747876370312\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.696078431372549,\n \"acc_stderr\": 0.032282103870378935,\n \"\ acc_norm\": 0.696078431372549,\n \"acc_norm_stderr\": 0.032282103870378935\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.6877637130801688,\n \"acc_stderr\": 0.03016513786784701,\n \ \ \"acc_norm\": 0.6877637130801688,\n \"acc_norm_stderr\": 0.03016513786784701\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5560538116591929,\n\ \ \"acc_stderr\": 0.03334625674242728,\n \"acc_norm\": 0.5560538116591929,\n\ \ \"acc_norm_stderr\": 0.03334625674242728\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5877862595419847,\n \"acc_stderr\": 0.04317171194870254,\n\ \ \"acc_norm\": 0.5877862595419847,\n \"acc_norm_stderr\": 0.04317171194870254\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5537190082644629,\n \"acc_stderr\": 0.0453793517794788,\n \"acc_norm\"\ : 0.5537190082644629,\n \"acc_norm_stderr\": 0.0453793517794788\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5648148148148148,\n\ \ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.5648148148148148,\n\ \ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5337423312883436,\n \"acc_stderr\": 0.039194155450484096,\n\ \ \"acc_norm\": 0.5337423312883436,\n \"acc_norm_stderr\": 0.039194155450484096\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4375,\n\ \ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \ \ \"acc_norm_stderr\": 0.04708567521880525\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6699029126213593,\n \"acc_stderr\": 0.0465614711001235,\n\ \ \"acc_norm\": 0.6699029126213593,\n \"acc_norm_stderr\": 0.0465614711001235\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7692307692307693,\n\ \ \"acc_stderr\": 0.0276019213814176,\n \"acc_norm\": 0.7692307692307693,\n\ \ \"acc_norm_stderr\": 0.0276019213814176\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \ \ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.669220945083014,\n\ \ \"acc_stderr\": 0.01682481846256376,\n \"acc_norm\": 0.669220945083014,\n\ \ \"acc_norm_stderr\": 0.01682481846256376\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.546242774566474,\n \"acc_stderr\": 0.02680372058320617,\n\ \ \"acc_norm\": 0.546242774566474,\n \"acc_norm_stderr\": 0.02680372058320617\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24022346368715083,\n\ \ \"acc_stderr\": 0.014288343803925293,\n \"acc_norm\": 0.24022346368715083,\n\ \ \"acc_norm_stderr\": 0.014288343803925293\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5359477124183006,\n \"acc_stderr\": 0.028555827516528784,\n\ \ \"acc_norm\": 0.5359477124183006,\n \"acc_norm_stderr\": 0.028555827516528784\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5787781350482315,\n\ \ \"acc_stderr\": 0.02804339985821063,\n \"acc_norm\": 0.5787781350482315,\n\ \ \"acc_norm_stderr\": 0.02804339985821063\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.558641975308642,\n \"acc_stderr\": 0.027628737155668767,\n\ \ \"acc_norm\": 0.558641975308642,\n \"acc_norm_stderr\": 0.027628737155668767\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.36524822695035464,\n \"acc_stderr\": 0.02872386385328128,\n \ \ \"acc_norm\": 0.36524822695035464,\n \"acc_norm_stderr\": 0.02872386385328128\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.363754889178618,\n\ \ \"acc_stderr\": 0.012286991879902887,\n \"acc_norm\": 0.363754889178618,\n\ \ \"acc_norm_stderr\": 0.012286991879902887\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5404411764705882,\n \"acc_stderr\": 0.03027332507734575,\n\ \ \"acc_norm\": 0.5404411764705882,\n \"acc_norm_stderr\": 0.03027332507734575\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.4869281045751634,\n \"acc_stderr\": 0.020220920829626916,\n \ \ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.020220920829626916\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5727272727272728,\n\ \ \"acc_stderr\": 0.04738198703545484,\n \"acc_norm\": 0.5727272727272728,\n\ \ \"acc_norm_stderr\": 0.04738198703545484\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6408163265306123,\n \"acc_stderr\": 0.030713560455108493,\n\ \ \"acc_norm\": 0.6408163265306123,\n \"acc_norm_stderr\": 0.030713560455108493\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6865671641791045,\n\ \ \"acc_stderr\": 0.03280188205348644,\n \"acc_norm\": 0.6865671641791045,\n\ \ \"acc_norm_stderr\": 0.03280188205348644\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.45180722891566266,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.45180722891566266,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7192982456140351,\n \"acc_stderr\": 0.03446296217088427,\n\ \ \"acc_norm\": 0.7192982456140351,\n \"acc_norm_stderr\": 0.03446296217088427\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.5020042655317223,\n\ \ \"mc2_stderr\": 0.015409102519026984\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7221783741120757,\n \"acc_stderr\": 0.012588918183871596\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.15845337376800606,\n \ \ \"acc_stderr\": 0.010058474790238962\n }\n}\n```" repo_url: https://huggingface.co/Charlie911/MultiLoRA-mmlu 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_02T00_16_37.919745 path: - '**/details_harness|arc:challenge|25_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-02T00-16-37.919745.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|gsm8k|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hellaswag|10_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-02T00-16-37.919745.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-management|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-02T00-16-37.919745.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|truthfulqa:mc|0_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-02T00-16-37.919745.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_02T00_16_37.919745 path: - '**/details_harness|winogrande|5_2024-02-02T00-16-37.919745.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-02T00-16-37.919745.parquet' - config_name: results data_files: - split: 2024_02_02T00_16_37.919745 path: - results_2024-02-02T00-16-37.919745.parquet - split: latest path: - results_2024-02-02T00-16-37.919745.parquet --- # Dataset Card for Evaluation run of Charlie911/MultiLoRA-mmlu  Dataset automatically created during the evaluation run of model [Charlie911/MultiLoRA-mmlu](https://huggingface.co/Charlie911/MultiLoRA-mmlu) 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_Charlie911__MultiLoRA-mmlu", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-02T00:16:37.919745](https://huggingface.co/datasets/open-llm-leaderboard/details_Charlie911__MultiLoRA-mmlu/blob/main/results_2024-02-02T00-16-37.919745.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": 0.49682393519091933, "acc_stderr": 0.034234549326781244, "acc_norm": 0.5024513039750834, "acc_norm_stderr": 0.03499839555197597, "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.5020042655317223, "mc2_stderr": 0.015409102519026984 }, "harness|arc:challenge|25": { "acc": 0.49658703071672355, "acc_stderr": 0.014611050403244077, "acc_norm": 0.5238907849829352, "acc_norm_stderr": 0.014594701798071654 }, "harness|hellaswag|10": { "acc": 0.5803624775941048, "acc_stderr": 0.004924910433106353, "acc_norm": 0.7720573590918144, "acc_norm_stderr": 0.0041864806453155625 }, "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": 0.45185185185185184, "acc_stderr": 0.04299268905480864, "acc_norm": 0.45185185185185184, "acc_norm_stderr": 0.04299268905480864 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.506578947368421, "acc_stderr": 0.040685900502249704, "acc_norm": 0.506578947368421, "acc_norm_stderr": 0.040685900502249704 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5169811320754717, "acc_stderr": 0.030755120364119905, "acc_norm": 0.5169811320754717, "acc_norm_stderr": 0.030755120364119905 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5, "acc_stderr": 0.04181210050035455, "acc_norm": 0.5, "acc_norm_stderr": 0.04181210050035455 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.43352601156069365, "acc_stderr": 0.03778621079092055, "acc_norm": 0.43352601156069365, "acc_norm_stderr": 0.03778621079092055 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.16666666666666666, "acc_stderr": 0.03708284662416542, "acc_norm": 0.16666666666666666, "acc_norm_stderr": 0.03708284662416542 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.43829787234042555, "acc_stderr": 0.032436186361081004, "acc_norm": 0.43829787234042555, "acc_norm_stderr": 0.032436186361081004 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159393, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159393 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2857142857142857, "acc_stderr": 0.023266512213730578, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.023266512213730578 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3253968253968254, "acc_stderr": 0.04190596438871136, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.04190596438871136 }, "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": 0.535483870967742, "acc_stderr": 0.02837228779796293, "acc_norm": 0.535483870967742, "acc_norm_stderr": 0.02837228779796293 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.39901477832512317, "acc_stderr": 0.03445487686264715, "acc_norm": 0.39901477832512317, "acc_norm_stderr": 0.03445487686264715 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512567, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512567 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5909090909090909, "acc_stderr": 0.03502975799413007, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.03502975799413007 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7046632124352331, "acc_stderr": 0.03292296639155141, "acc_norm": 0.7046632124352331, "acc_norm_stderr": 0.03292296639155141 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4717948717948718, "acc_stderr": 0.025310639254933893, "acc_norm": 0.4717948717948718, "acc_norm_stderr": 0.025310639254933893 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24074074074074073, "acc_stderr": 0.026067159222275805, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.026067159222275805 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.4369747899159664, "acc_stderr": 0.03221943636566196, "acc_norm": 0.4369747899159664, "acc_norm_stderr": 0.03221943636566196 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969653, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969653 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.6770642201834862, "acc_stderr": 0.02004811592341531, "acc_norm": 0.6770642201834862, "acc_norm_stderr": 0.02004811592341531 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.39351851851851855, "acc_stderr": 0.03331747876370312, "acc_norm": 0.39351851851851855, "acc_norm_stderr": 0.03331747876370312 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.696078431372549, "acc_stderr": 0.032282103870378935, "acc_norm": 0.696078431372549, "acc_norm_stderr": 0.032282103870378935 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.6877637130801688, "acc_stderr": 0.03016513786784701, "acc_norm": 0.6877637130801688, "acc_norm_stderr": 0.03016513786784701 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.5560538116591929, "acc_stderr": 0.03334625674242728, "acc_norm": 0.5560538116591929, "acc_norm_stderr": 0.03334625674242728 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5877862595419847, "acc_stderr": 0.04317171194870254, "acc_norm": 0.5877862595419847, "acc_norm_stderr": 0.04317171194870254 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5537190082644629, "acc_stderr": 0.0453793517794788, "acc_norm": 0.5537190082644629, "acc_norm_stderr": 0.0453793517794788 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.5648148148148148, "acc_stderr": 0.04792898170907061, "acc_norm": 0.5648148148148148, "acc_norm_stderr": 0.04792898170907061 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5337423312883436, "acc_stderr": 0.039194155450484096, "acc_norm": 0.5337423312883436, "acc_norm_stderr": 0.039194155450484096 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4375, "acc_stderr": 0.04708567521880525, "acc_norm": 0.4375, "acc_norm_stderr": 0.04708567521880525 }, "harness|hendrycksTest-management|5": { "acc": 0.6699029126213593, "acc_stderr": 0.0465614711001235, "acc_norm": 0.6699029126213593, "acc_norm_stderr": 0.0465614711001235 }, "harness|hendrycksTest-marketing|5": { "acc": 0.7692307692307693, "acc_stderr": 0.0276019213814176, "acc_norm": 0.7692307692307693, "acc_norm_stderr": 0.0276019213814176 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.669220945083014, "acc_stderr": 0.01682481846256376, "acc_norm": 0.669220945083014, "acc_norm_stderr": 0.01682481846256376 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.546242774566474, "acc_stderr": 0.02680372058320617, "acc_norm": 0.546242774566474, "acc_norm_stderr": 0.02680372058320617 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24022346368715083, "acc_stderr": 0.014288343803925293, "acc_norm": 0.24022346368715083, "acc_norm_stderr": 0.014288343803925293 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5359477124183006, "acc_stderr": 0.028555827516528784, "acc_norm": 0.5359477124183006, "acc_norm_stderr": 0.028555827516528784 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.5787781350482315, "acc_stderr": 0.02804339985821063, "acc_norm": 0.5787781350482315, "acc_norm_stderr": 0.02804339985821063 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.558641975308642, "acc_stderr": 0.027628737155668767, "acc_norm": 0.558641975308642, "acc_norm_stderr": 0.027628737155668767 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.36524822695035464, "acc_stderr": 0.02872386385328128, "acc_norm": 0.36524822695035464, "acc_norm_stderr": 0.02872386385328128 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.363754889178618, "acc_stderr": 0.012286991879902887, "acc_norm": 0.363754889178618, "acc_norm_stderr": 0.012286991879902887 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5404411764705882, "acc_stderr": 0.03027332507734575, "acc_norm": 0.5404411764705882, "acc_norm_stderr": 0.03027332507734575 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.4869281045751634, "acc_stderr": 0.020220920829626916, "acc_norm": 0.4869281045751634, "acc_norm_stderr": 0.020220920829626916 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5727272727272728, "acc_stderr": 0.04738198703545484, "acc_norm": 0.5727272727272728, "acc_norm_stderr": 0.04738198703545484 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6408163265306123, "acc_stderr": 0.030713560455108493, "acc_norm": 0.6408163265306123, "acc_norm_stderr": 0.030713560455108493 }, "harness|hendrycksTest-sociology|5": { "acc": 0.6865671641791045, "acc_stderr": 0.03280188205348644, "acc_norm": 0.6865671641791045, "acc_norm_stderr": 0.03280188205348644 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-virology|5": { "acc": 0.45180722891566266, "acc_stderr": 0.03874371556587953, "acc_norm": 0.45180722891566266, "acc_norm_stderr": 0.03874371556587953 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7192982456140351, "acc_stderr": 0.03446296217088427, "acc_norm": 0.7192982456140351, "acc_norm_stderr": 0.03446296217088427 }, "harness|truthfulqa:mc|0": { "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.5020042655317223, "mc2_stderr": 0.015409102519026984 }, "harness|winogrande|5": { "acc": 0.7221783741120757, "acc_stderr": 0.012588918183871596 }, "harness|gsm8k|5": { "acc": 0.15845337376800606, "acc_stderr": 0.010058474790238962 } } ``` ## 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]

gemma111/customhkcode2

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5826 num_examples: 39 download_size: 2572 dataset_size: 5826 configs: - config_name: default data_files: - split: train path: data/train-* ---