davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569969	--- type: predictions tags: - autotrain - evaluation datasets: - futin/feed eval_info: task: text_zero_shot_classification model: facebook/opt-66b metrics: [] dataset_name: futin/feed dataset_config: top_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-66b * Dataset: futin/feed * Config: top_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.
proserve/medical-instruct-mixer-v2	--- dataset_info: features: - name: content dtype: string splits: - name: train num_bytes: 463565438.0 num_examples: 482593 - name: test num_bytes: 74684196.0 num_examples: 40159 download_size: 278795913 dataset_size: 538249634.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
Ti-Ma/wikipedia_2018	--- license: cc-by-sa-3.0 ---
lim4349/korquad	--- dataset_info: features: - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: id dtype: string - name: answers struct: - name: text sequence: string - name: answer_start sequence: int64 splits: - name: train num_bytes: 75266074 num_examples: 54366 - name: validation num_bytes: 8358264 num_examples: 6041 download_size: 51472501 dataset_size: 83624338 --- # Dataset Card for "korquad" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mstz/vertebral_column	--- language: - en tags: - vertebral_column - tabular_classification - binary_classification - UCI pretty_name: Vertebral Column size_categories: - n<1K task_categories: - tabular-classification configs: - vertebral license: cc --- # Vertebral Column The [Vertebral Column dataset](https://archive.ics.uci.edu/ml/datasets/vertebral+column) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets). # Configurations and tasks \| Configuration \| Task \| Description \| \|-------------------\|---------------------------\|-------------------------\| \| abnormal \| Binary classification \| Is the spine abnormal?\| # Usage ```python from datasets import load_dataset dataset = load_dataset("mstz/vertebral_column")["train"] ```
torchgeo/l8biome	--- task_categories: - image-segmentation tags: - climate pretty_name: L8 Biome size_categories: - n<1K license: cc0-1.0 --- Redistribution of data from https://landsat.usgs.gov/landsat-8-cloud-cover-assessment-validation-data, masks modified to add georeferencing metadata. Landsat Data Distribution Policy: https://www.usgs.gov/media/files/landsat-data-distribution-policy
akahana/oscar-unshuffled_deduplicated_id_10k	--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 18527241 num_examples: 10000 download_size: 10371685 dataset_size: 18527241 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "oscar-unshuffled_deduplicated_id_10k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Kaludi/data-food-category-classification	--- task_categories: - image-classification --- # Dataset for project: food-category-classification ## Dataset Description This dataset is for project food-category-classification. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "image": "<512x512 RGB PIL image>", "target": 0 }, { "image": "<512x512 RGB PIL image>", "target": 0 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "image": "Image(decode=True, id=None)", "target": "ClassLabel(names=['Bread', 'Dairy product', 'Dessert', 'Egg', 'Fried food', 'Meat', 'Noodles-Pasta', 'Rice', 'Seafood', 'Soup', 'Vegetable-Fruit'], 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 \| 1210 \| \| valid \| 275 \|
EkBass/fin-eng-dataset	--- license: gpl-3.0 task_categories: - translation language: - fi - en tags: - text - translation - finnish - english pretty_name: fin-eng-dataset-6k --- # fin-eng-dataset # Updated 29th October 2023 New version. Covers around 30K individual words and around 10K sentences, phrases etc. # Updated 19th September 2023 New version. Over 20K unique words and over 2K sentences/paragraphs fin-eng versions. # Updated 10th September 2023 Updated version. Around 15K different words and a couple of thousands of sentences, paragraphs, quots, questions and answers. # English The file fine-eng-dataset.json contains over 9000 individual Finnish words with their English translations. Since some of the words are names of places, people, etc., the exact number of Finnish words is unknown. Part of the data includes a list of Finnish words along with their English translations. However, the majority of the data consists of Finnish sentences, questions, statements, etc., that have been translated into English. The data begins with a list of the thousand most common Finnish words with their translations. Following that are sentences, including quotes from Martti Ahtisaari, Public Domain books like "Open Life," Maila Talvio's "The Destruction of Dark Cabin," as well as sentences from free novellas "Midsummer Gift for Readers" and "Erotic Novella: Towards Malaysia." In addition, sentences, quotes from movies, basic sentences produced by artificial intelligence, personal messages, etc., have been added, totaling over a thousand entries. Random paragraphs from Finnish Wikipedia's "random article" have also been included. The work is intended to continue indefinitely. Help is needed; please contact krisu.virtanen@gmail.com. # Suomeksi fine-eng-dataset.json sisältää yli 9000 yksittäistä suomenkielistä sanaa englanninkielisenä käännöksenään. Koska osa sanoista on paikkojen-, ihmisten-, jne, nimiä niin tarkkaa määrää suomenkielisestä sanoista ei tiedetä. Osassa dataa on syötetty lista suomenkielisiä sanoja sekä niiden englanninkieliset käännökset. Suurin osa datasta on kuitenkin suomenkielisiä lauseita, kysymyksiä, toteamuksia jne. jotka on käännetty englanniksi. Data alkaa luettelolla tuhannesta yleisimmästä suomenkilisestä sanasta käännöksineen. Tämän jälkeen tulee lauseita, mm. lainauksia Martti Ahtesaaresta, Public Domain kirjoista "Avoin Elämä", Maila Talvion "Pimeänpirtin hävitys", sekä lauseita ilmaisista novelleista "Juhannustalahja lukijoille" ja "Erottiinen novelli: Kohti Malesiaa". Lisäksi on syötetty lauseita, lainauksia elokuvista, tekoälyn tuottamia peruslauseita, omia viestejä jne. kaiken kaikkiaan yli tuhannen kappaleen verran sekä otettu satunnaisia kappaleita suomenkielisestä wikipediasta "satunnainen artikkeli". Tarkoitus on jatkaa työtä toistaiseksi. Apua tarvitaan, ota yhteyttä krisu.virtanen@gmail.com
open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5	--- pretty_name: Evaluation run of BFauber/lora_llama2-13b_10e5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BFauber/lora_llama2-13b_10e5](https://huggingface.co/BFauber/lora_llama2-13b_10e5)\ \ 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_BFauber__lora_llama2-13b_10e5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-10T01:54:15.995961](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5/blob/main/results_2024-02-10T01-54-15.995961.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\": 0.5557440720682312,\n\ \ \"acc_stderr\": 0.03358121479787839,\n \"acc_norm\": 0.5618325027332456,\n\ \ \"acc_norm_stderr\": 0.03430489410692684,\n \"mc1\": 0.2607099143206854,\n\ \ \"mc1_stderr\": 0.015368841620766373,\n \"mc2\": 0.37646299641377995,\n\ \ \"mc2_stderr\": 0.013743052527776188\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5614334470989761,\n \"acc_stderr\": 0.014500682618212864,\n\ \ \"acc_norm\": 0.5921501706484642,\n \"acc_norm_stderr\": 0.014361097288449703\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.616211909978092,\n\ \ \"acc_stderr\": 0.004853134271547769,\n \"acc_norm\": 0.8241386178052181,\n\ \ \"acc_norm_stderr\": 0.003799241408502968\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\": 0.5407407407407407,\n\ \ \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.5407407407407407,\n\ \ \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5328947368421053,\n \"acc_stderr\": 0.04060127035236397,\n\ \ \"acc_norm\": 0.5328947368421053,\n \"acc_norm_stderr\": 0.04060127035236397\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.53,\n\ \ \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.630188679245283,\n \"acc_stderr\": 0.029711421880107933,\n\ \ \"acc_norm\": 0.630188679245283,\n \"acc_norm_stderr\": 0.029711421880107933\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.5972222222222222,\n\ \ \"acc_stderr\": 0.04101405519842426,\n \"acc_norm\": 0.5972222222222222,\n\ \ \"acc_norm_stderr\": 0.04101405519842426\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.47,\n\ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5491329479768786,\n\ \ \"acc_stderr\": 0.0379401267469703,\n \"acc_norm\": 0.5491329479768786,\n\ \ \"acc_norm_stderr\": 0.0379401267469703\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.043364327079931785,\n\ \ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.043364327079931785\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.41702127659574467,\n \"acc_stderr\": 0.03223276266711712,\n\ \ \"acc_norm\": 0.41702127659574467,\n \"acc_norm_stderr\": 0.03223276266711712\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.30701754385964913,\n\ \ \"acc_stderr\": 0.043391383225798615,\n \"acc_norm\": 0.30701754385964913,\n\ \ \"acc_norm_stderr\": 0.043391383225798615\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\ \ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3333333333333333,\n \"acc_stderr\": 0.024278568024307702,\n \"\ acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.024278568024307702\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3253968253968254,\n\ \ \"acc_stderr\": 0.041905964388711366,\n \"acc_norm\": 0.3253968253968254,\n\ \ \"acc_norm_stderr\": 0.041905964388711366\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.048523658709391,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.048523658709391\n },\n\ \ \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.6838709677419355,\n\ \ \"acc_stderr\": 0.026450874489042774,\n \"acc_norm\": 0.6838709677419355,\n\ \ \"acc_norm_stderr\": 0.026450874489042774\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.458128078817734,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\"\ : 0.58,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512566,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512566\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.6818181818181818,\n \"acc_stderr\": 0.0331847733384533,\n \"acc_norm\"\ : 0.6818181818181818,\n \"acc_norm_stderr\": 0.0331847733384533\n },\n\ \ \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n \ \ \"acc\": 0.8082901554404145,\n \"acc_stderr\": 0.02840895362624527,\n\ \ \"acc_norm\": 0.8082901554404145,\n \"acc_norm_stderr\": 0.02840895362624527\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5076923076923077,\n \"acc_stderr\": 0.02534800603153477,\n \ \ \"acc_norm\": 0.5076923076923077,\n \"acc_norm_stderr\": 0.02534800603153477\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5546218487394958,\n \"acc_stderr\": 0.032284106267163895,\n\ \ \"acc_norm\": 0.5546218487394958,\n \"acc_norm_stderr\": 0.032284106267163895\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7504587155963303,\n \"acc_stderr\": 0.018553897629501617,\n \"\ acc_norm\": 0.7504587155963303,\n \"acc_norm_stderr\": 0.018553897629501617\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\"\ : 0.75,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.7130801687763713,\n \"acc_stderr\": 0.02944377302259469,\n\ \ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.02944377302259469\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6457399103139013,\n\ \ \"acc_stderr\": 0.032100621541349864,\n \"acc_norm\": 0.6457399103139013,\n\ \ \"acc_norm_stderr\": 0.032100621541349864\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6412213740458015,\n \"acc_stderr\": 0.04206739313864908,\n\ \ \"acc_norm\": 0.6412213740458015,\n \"acc_norm_stderr\": 0.04206739313864908\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.039418975265163025,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.039418975265163025\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6687116564417178,\n \"acc_stderr\": 0.03697983910025588,\n\ \ \"acc_norm\": 0.6687116564417178,\n \"acc_norm_stderr\": 0.03697983910025588\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.30357142857142855,\n\ \ \"acc_stderr\": 0.043642261558410445,\n \"acc_norm\": 0.30357142857142855,\n\ \ \"acc_norm_stderr\": 0.043642261558410445\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\": 0.8076923076923077,\n\ \ \"acc_stderr\": 0.025819233256483717,\n \"acc_norm\": 0.8076923076923077,\n\ \ \"acc_norm_stderr\": 0.025819233256483717\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7420178799489144,\n\ \ \"acc_stderr\": 0.01564583018834895,\n \"acc_norm\": 0.7420178799489144,\n\ \ \"acc_norm_stderr\": 0.01564583018834895\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6473988439306358,\n \"acc_stderr\": 0.025722802200895806,\n\ \ \"acc_norm\": 0.6473988439306358,\n \"acc_norm_stderr\": 0.025722802200895806\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.264804469273743,\n\ \ \"acc_stderr\": 0.014756906483260666,\n \"acc_norm\": 0.264804469273743,\n\ \ \"acc_norm_stderr\": 0.014756906483260666\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6339869281045751,\n \"acc_stderr\": 0.027582811415159607,\n\ \ \"acc_norm\": 0.6339869281045751,\n \"acc_norm_stderr\": 0.027582811415159607\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6559485530546624,\n\ \ \"acc_stderr\": 0.026981478043648036,\n \"acc_norm\": 0.6559485530546624,\n\ \ \"acc_norm_stderr\": 0.026981478043648036\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6358024691358025,\n \"acc_stderr\": 0.026774929899722327,\n\ \ \"acc_norm\": 0.6358024691358025,\n \"acc_norm_stderr\": 0.026774929899722327\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.425531914893617,\n \"acc_stderr\": 0.029494827600144373,\n \ \ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.029494827600144373\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4230769230769231,\n\ \ \"acc_stderr\": 0.012618204066588392,\n \"acc_norm\": 0.4230769230769231,\n\ \ \"acc_norm_stderr\": 0.012618204066588392\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5147058823529411,\n \"acc_stderr\": 0.03035969707904612,\n\ \ \"acc_norm\": 0.5147058823529411,\n \"acc_norm_stderr\": 0.03035969707904612\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5506535947712419,\n \"acc_stderr\": 0.02012376652802727,\n \ \ \"acc_norm\": 0.5506535947712419,\n \"acc_norm_stderr\": 0.02012376652802727\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6163265306122448,\n \"acc_stderr\": 0.03113088039623593,\n\ \ \"acc_norm\": 0.6163265306122448,\n \"acc_norm_stderr\": 0.03113088039623593\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.746268656716418,\n\ \ \"acc_stderr\": 0.03076944496729602,\n \"acc_norm\": 0.746268656716418,\n\ \ \"acc_norm_stderr\": 0.03076944496729602\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.463855421686747,\n\ \ \"acc_stderr\": 0.03882310850890593,\n \"acc_norm\": 0.463855421686747,\n\ \ \"acc_norm_stderr\": 0.03882310850890593\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2607099143206854,\n\ \ \"mc1_stderr\": 0.015368841620766373,\n \"mc2\": 0.37646299641377995,\n\ \ \"mc2_stderr\": 0.013743052527776188\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7695343330702447,\n \"acc_stderr\": 0.011835872164836671\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.221379833206975,\n \ \ \"acc_stderr\": 0.01143600000425351\n }\n}\n```" repo_url: https://huggingface.co/BFauber/lora_llama2-13b_10e5 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_10T01_54_15.995961 path: - '/details_harness\|arc:challenge\|25_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-10T01-54-15.995961.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|gsm8k\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hellaswag\|10_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T01-54-15.995961.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-10T01-54-15.995961.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '/details_harness\|winogrande\|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-10T01-54-15.995961.parquet' - config_name: results data_files: - split: 2024_02_10T01_54_15.995961 path: - results_2024-02-10T01-54-15.995961.parquet - split: latest path: - results_2024-02-10T01-54-15.995961.parquet --- # Dataset Card for Evaluation run of BFauber/lora_llama2-13b_10e5 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [BFauber/lora_llama2-13b_10e5](https://huggingface.co/BFauber/lora_llama2-13b_10e5) 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_BFauber__lora_llama2-13b_10e5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-10T01:54:15.995961](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5/blob/main/results_2024-02-10T01-54-15.995961.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": 0.5557440720682312, "acc_stderr": 0.03358121479787839, "acc_norm": 0.5618325027332456, "acc_norm_stderr": 0.03430489410692684, "mc1": 0.2607099143206854, "mc1_stderr": 0.015368841620766373, "mc2": 0.37646299641377995, "mc2_stderr": 0.013743052527776188 }, "harness\|arc:challenge\|25": { "acc": 0.5614334470989761, "acc_stderr": 0.014500682618212864, "acc_norm": 0.5921501706484642, "acc_norm_stderr": 0.014361097288449703 }, "harness\|hellaswag\|10": { "acc": 0.616211909978092, "acc_stderr": 0.004853134271547769, "acc_norm": 0.8241386178052181, "acc_norm_stderr": 0.003799241408502968 }, "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": 0.5407407407407407, "acc_stderr": 0.04304979692464242, "acc_norm": 0.5407407407407407, "acc_norm_stderr": 0.04304979692464242 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5328947368421053, "acc_stderr": 0.04060127035236397, "acc_norm": 0.5328947368421053, "acc_norm_stderr": 0.04060127035236397 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.630188679245283, "acc_stderr": 0.029711421880107933, "acc_norm": 0.630188679245283, "acc_norm_stderr": 0.029711421880107933 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.5972222222222222, "acc_stderr": 0.04101405519842426, "acc_norm": 0.5972222222222222, "acc_norm_stderr": 0.04101405519842426 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5491329479768786, "acc_stderr": 0.0379401267469703, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.0379401267469703 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.41702127659574467, "acc_stderr": 0.03223276266711712, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.03223276266711712 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.30701754385964913, "acc_stderr": 0.043391383225798615, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.043391383225798615 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.024278568024307702, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.024278568024307702 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3253968253968254, "acc_stderr": 0.041905964388711366, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.041905964388711366 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6838709677419355, "acc_stderr": 0.026450874489042774, "acc_norm": 0.6838709677419355, "acc_norm_stderr": 0.026450874489042774 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785741, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785741 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512566, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512566 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.6818181818181818, "acc_stderr": 0.0331847733384533, "acc_norm": 0.6818181818181818, "acc_norm_stderr": 0.0331847733384533 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8082901554404145, "acc_stderr": 0.02840895362624527, "acc_norm": 0.8082901554404145, "acc_norm_stderr": 0.02840895362624527 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5076923076923077, "acc_stderr": 0.02534800603153477, "acc_norm": 0.5076923076923077, "acc_norm_stderr": 0.02534800603153477 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340492, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340492 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5546218487394958, "acc_stderr": 0.032284106267163895, "acc_norm": 0.5546218487394958, "acc_norm_stderr": 0.032284106267163895 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7504587155963303, "acc_stderr": 0.018553897629501617, "acc_norm": 0.7504587155963303, "acc_norm_stderr": 0.018553897629501617 }, "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": 0.75, "acc_stderr": 0.03039153369274154, "acc_norm": 0.75, "acc_norm_stderr": 0.03039153369274154 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7130801687763713, "acc_stderr": 0.02944377302259469, "acc_norm": 0.7130801687763713, "acc_norm_stderr": 0.02944377302259469 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6457399103139013, "acc_stderr": 0.032100621541349864, "acc_norm": 0.6457399103139013, "acc_norm_stderr": 0.032100621541349864 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6412213740458015, "acc_stderr": 0.04206739313864908, "acc_norm": 0.6412213740458015, "acc_norm_stderr": 0.04206739313864908 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7520661157024794, "acc_stderr": 0.039418975265163025, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.039418975265163025 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6687116564417178, "acc_stderr": 0.03697983910025588, "acc_norm": 0.6687116564417178, "acc_norm_stderr": 0.03697983910025588 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.30357142857142855, "acc_stderr": 0.043642261558410445, "acc_norm": 0.30357142857142855, "acc_norm_stderr": 0.043642261558410445 }, "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": 0.8076923076923077, "acc_stderr": 0.025819233256483717, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.025819233256483717 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7420178799489144, "acc_stderr": 0.01564583018834895, "acc_norm": 0.7420178799489144, "acc_norm_stderr": 0.01564583018834895 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6473988439306358, "acc_stderr": 0.025722802200895806, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.025722802200895806 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.264804469273743, "acc_stderr": 0.014756906483260666, "acc_norm": 0.264804469273743, "acc_norm_stderr": 0.014756906483260666 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6339869281045751, "acc_stderr": 0.027582811415159607, "acc_norm": 0.6339869281045751, "acc_norm_stderr": 0.027582811415159607 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6559485530546624, "acc_stderr": 0.026981478043648036, "acc_norm": 0.6559485530546624, "acc_norm_stderr": 0.026981478043648036 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6358024691358025, "acc_stderr": 0.026774929899722327, "acc_norm": 0.6358024691358025, "acc_norm_stderr": 0.026774929899722327 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.425531914893617, "acc_stderr": 0.029494827600144373, "acc_norm": 0.425531914893617, "acc_norm_stderr": 0.029494827600144373 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4230769230769231, "acc_stderr": 0.012618204066588392, "acc_norm": 0.4230769230769231, "acc_norm_stderr": 0.012618204066588392 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5147058823529411, "acc_stderr": 0.03035969707904612, "acc_norm": 0.5147058823529411, "acc_norm_stderr": 0.03035969707904612 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5506535947712419, "acc_stderr": 0.02012376652802727, "acc_norm": 0.5506535947712419, "acc_norm_stderr": 0.02012376652802727 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6163265306122448, "acc_stderr": 0.03113088039623593, "acc_norm": 0.6163265306122448, "acc_norm_stderr": 0.03113088039623593 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.746268656716418, "acc_stderr": 0.03076944496729602, "acc_norm": 0.746268656716418, "acc_norm_stderr": 0.03076944496729602 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.463855421686747, "acc_stderr": 0.03882310850890593, "acc_norm": 0.463855421686747, "acc_norm_stderr": 0.03882310850890593 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2607099143206854, "mc1_stderr": 0.015368841620766373, "mc2": 0.37646299641377995, "mc2_stderr": 0.013743052527776188 }, "harness\|winogrande\|5": { "acc": 0.7695343330702447, "acc_stderr": 0.011835872164836671 }, "harness\|gsm8k\|5": { "acc": 0.221379833206975, "acc_stderr": 0.01143600000425351 } } ``` ## 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 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CyberHarem/sona_leagueoflegends	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sona (League of Legends) This is the dataset of sona (League of Legends), containing 500 images and their tags. The core tags of this character are `long_hair, twintails, breasts, large_breasts, blue_hair, blue_eyes, very_long_hair, aqua_hair, hair_ornament, multicolored_hair, gradient_hair`, 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 \| 748.13 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 500 \| 425.57 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 1150 \| 860.62 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 500 \| 658.30 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1150 \| 1.20 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/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/sona_leagueoflegends', 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 \| 20 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, bare_shoulders, cleavage, solo, instrument, dress, lips \| \| 1 \| 8 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, bare_shoulders, cleavage, collarbone, solo, upper_body, bangs, blush, looking_at_viewer, simple_background, white_background, closed_mouth, low_neckline, smile, blue_dress \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, cleavage, necklace, solo, star_(symbol), midriff, navel, earrings, fingerless_gloves, looking_at_viewer, bra, green_gloves, purple_hair, smile \| \| 3 \| 6 \| ![](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, nipples, nude, pussy, solo, aqua_eyes, blush, looking_at_viewer, navel, on_back, uncensored, bed_sheet, green_eyes, smile \| \| 4 \| 10 \| ![](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) \| 1boy, 1girl, hetero, nipples, solo_focus, penis, blush, cum, nude, collarbone, huge_breasts, paizuri, bare_shoulders, blonde_hair, male_pubic_hair, parted_lips, smile, uncensored \| \| 5 \| 5 \| ![](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, black_panties, looking_at_viewer, solo, black_bra, black_thighhighs, blonde_hair, garter_belt, garter_straps, blush, cleavage, collarbone, huge_breasts, skindentation, ass, bare_shoulders, curvy, hair_between_eyes, lingerie, looking_back, navel, open_mouth, parted_lips, simple_background, thick_thighs, thigh_gap, underwear_only \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| bare_shoulders \| cleavage \| solo \| instrument \| dress \| lips \| collarbone \| upper_body \| bangs \| blush \| looking_at_viewer \| simple_background \| white_background \| closed_mouth \| low_neckline \| smile \| blue_dress \| necklace \| star_(symbol) \| midriff \| navel \| earrings \| fingerless_gloves \| bra \| green_gloves \| purple_hair \| nipples \| nude \| pussy \| aqua_eyes \| on_back \| uncensored \| bed_sheet \| green_eyes \| 1boy \| hetero \| solo_focus \| penis \| cum \| huge_breasts \| paizuri \| blonde_hair \| male_pubic_hair \| parted_lips \| black_panties \| black_bra \| black_thighhighs \| garter_belt \| garter_straps \| skindentation \| ass \| curvy \| hair_between_eyes \| lingerie \| looking_back \| open_mouth \| thick_thighs \| thigh_gap \| underwear_only \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-----------------\|:-----------\|:-------\|:-------------\|:--------\|:-------\|:-------------\|:-------------\|:--------\|:--------\|:--------------------\|:--------------------\|:-------------------\|:---------------\|:---------------\|:--------\|:-------------\|:-----------\|:----------------\|:----------\|:--------\|:-----------\|:--------------------\|:------\|:---------------\|:--------------\|:----------\|:-------\|:--------\|:------------\|:----------\|:-------------\|:------------\|:-------------\|:-------\|:---------\|:-------------\|:--------\|:------\|:---------------\|:----------\|:--------------\|:------------------\|:--------------\|:----------------\|:------------\|:-------------------\|:--------------\|:----------------\|:----------------\|:------\|:--------\|:--------------------\|:-----------\|:---------------\|:-------------\|:---------------\|:------------\|:-----------------\| \| 0 \| 20 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 8 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| \| X \| X \| \| \| \| \| \| \| \| X \| \| \| \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 6 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 10 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 5 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| X \| X \| X \| \| \| \| X \| \| \| X \| X \| X \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf	--- pretty_name: Evaluation run of ehartford/CodeLlama-34b-Python-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ehartford/CodeLlama-34b-Python-hf](https://huggingface.co/ehartford/CodeLlama-34b-Python-hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 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_ehartford__CodeLlama-34b-Python-hf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T22:02:41.600326](https://huggingface.co/datasets/open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf/blob/main/results_2023-09-17T22-02-41.600326.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0012583892617449664,\n\ \ \"em_stderr\": 0.00036305608931190325,\n \"f1\": 0.0019200922818791944,\n\ \ \"f1_stderr\": 0.0004138356823487018,\n \"acc\": 0.3307024467245462,\n\ \ \"acc_stderr\": 0.006650084932921209\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0012583892617449664,\n \"em_stderr\": 0.00036305608931190325,\n\ \ \"f1\": 0.0019200922818791944,\n \"f1_stderr\": 0.0004138356823487018\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.6614048934490924,\n\ \ \"acc_stderr\": 0.013300169865842417\n }\n}\n```" repo_url: https://huggingface.co/ehartford/CodeLlama-34b-Python-hf 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_26T01_57_15.339948 path: - '/details_harness\|arc:challenge\|25_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-26T01:57:15.339948.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T22_02_41.600326 path: - '/details_harness\|drop\|3_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-09-17T22-02-41.600326.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T22_02_41.600326 path: - '/details_harness\|gsm8k\|5_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-09-17T22-02-41.600326.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hellaswag\|10_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T01:57:15.339948.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_26T01_57_15.339948 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-26T01:57:15.339948.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T22_02_41.600326 path: - '/details_harness\|winogrande\|5_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-09-17T22-02-41.600326.parquet' - config_name: results data_files: - split: 2023_08_26T01_57_15.339948 path: - results_2023-08-26T01:57:15.339948.parquet - split: 2023_09_17T22_02_41.600326 path: - results_2023-09-17T22-02-41.600326.parquet - split: latest path: - results_2023-09-17T22-02-41.600326.parquet --- # Dataset Card for Evaluation run of ehartford/CodeLlama-34b-Python-hf ## Dataset Description - Homepage: - Repository: https://huggingface.co/ehartford/CodeLlama-34b-Python-hf - 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 [ehartford/CodeLlama-34b-Python-hf](https://huggingface.co/ehartford/CodeLlama-34b-Python-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 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_ehartford__CodeLlama-34b-Python-hf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T22:02:41.600326](https://huggingface.co/datasets/open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf/blob/main/results_2023-09-17T22-02-41.600326.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190325, "f1": 0.0019200922818791944, "f1_stderr": 0.0004138356823487018, "acc": 0.3307024467245462, "acc_stderr": 0.006650084932921209 }, "harness\|drop\|3": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190325, "f1": 0.0019200922818791944, "f1_stderr": 0.0004138356823487018 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.6614048934490924, "acc_stderr": 0.013300169865842417 } } ``` ### 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]
erfanzar/UltraChat-Mini	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: dialog sequence: string - name: user sequence: string - name: assistant sequence: string - name: system dtype: string - name: id dtype: int64 - name: llama2_prompt dtype: string splits: - name: train num_bytes: 6005323184 num_examples: 239641 download_size: 2964129142 dataset_size: 6005323184 --- # Dataset Card for "UltraChat-Mini" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
adityarra07/test_ds_uwb_atc_noise_trial	--- dataset_info: features: - name: audio struct: - name: array sequence: float32 - name: path dtype: 'null' - name: sampling_rate dtype: int64 - name: transcription dtype: string - name: id dtype: string splits: - name: train num_bytes: 684273363.9015728 num_examples: 3000 - name: test num_bytes: 22809112.13005243 num_examples: 100 download_size: 709812743 dataset_size: 707082476.0316253 --- # Dataset Card for "test_ds_uwb_atc_noise_trial" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
enoahjr/twitter_dataset_1713189012	--- 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: 992034 num_examples: 2929 download_size: 542763 dataset_size: 992034 configs: - config_name: default data_files: - split: train path: data/train-* ---
liuyanchen1015/VALUE_mrpc_lexical	--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: test num_bytes: 402763 num_examples: 1493 - name: train num_bytes: 849076 num_examples: 3134 - name: validation num_bytes: 97832 num_examples: 360 download_size: 921493 dataset_size: 1349671 --- # Dataset Card for "VALUE_mrpc_lexical" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Areeb123/drug_reviews	--- license: mit task_categories: - text-classification language: - en tags: - medical size_categories: - 1M<n<10M ---
aintech/vdf_wolt_food	--- tags: - vdf - vector-io - vector-dataset - vector-embeddings --- This is a dataset created using [vector-io](https://github.com/ai-northstar-tech/vector-io)
tramzel/fndds	--- license: unknown ---
RuudVelo/my_awesome_new_bike	--- license: apache-2.0 dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 29796713.0 num_examples: 10 download_size: 26771158 dataset_size: 29796713.0 ---
betterMateusz/SAT_Writting_Reading_Assessment_Question_Bank	--- language: - en license: mit dataset_info: features: - name: id dtype: string - name: passage dtype: string - name: question dtype: string - name: choice_A dtype: string - name: choice_B dtype: string - name: choice_C dtype: string - name: choice_D dtype: string - name: correct_answer dtype: string - name: rationale dtype: string - name: difficulty dtype: string - name: domain dtype: string splits: - name: train num_bytes: 706258.0 num_examples: 397 download_size: 346011 dataset_size: 706258.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for SAT Reading and Writing Dataset This dataset card aims to be a base template for the SAT Reading and Writing Dataset, optimized for use with Hugging Face's datasets library. ## Dataset Details ### Dataset Description This dataset contains SAT Reading and Writing assessment questions sourced from the College Board's SAT Suite Question Bank, intended for use in training and evaluating Language Models like LLMs. - Curated by: College Board - License: Creative Commons Attribution-ShareAlike 4.0 International License ### Dataset Sources - Repository: [College Board SAT Suite Question Bank](https://satsuitequestionbank.collegeboard.org/) ## Uses ### Direct Use The dataset can be used for SAT exam preparation and educational purposes. It is suitable for training and evaluating Language Models for SAT-style reading comprehension and writing tasks. ## Dataset Structure The dataset contains questions with passages, choices, correct answers, and rationales, making it ideal for training and evaluating Language Models on SAT-style reading comprehension and writing tasks. ## Dataset Creation ### Curation Rationale The dataset was created to provide a resource for students preparing for the SAT exam and for researchers and developers working on Natural Language Processing tasks related to standardized testing. ### Source Data #### Data Collection and Processing The questions were extracted from the College Board SAT Suite Question Bank using automated scraping and filtering processes. #### Who are the source data producers? The College Board is the producer of the source data. ## Bias, Risks, and Limitations Users should be aware of the limitations of using this dataset for predicting SAT scores and should use it in conjunction with other resources for a comprehensive SAT preparation. ### Recommendations Users should use this dataset as a supplementary resource for SAT exam preparation and as a benchmark for evaluating the performance of Language Models on SAT-style reading comprehension and writing tasks. ## Citation APA: College Board. SAT Reading and Writing Dataset. Retrieved from [College Board SAT Suite Question Bank](https://satsuitequestionbank.collegeboard.org/)
YBXL/JAMA_Reasoning_test_Rare_test	--- dataset_info: features: - name: id dtype: string - name: query dtype: string - name: answer dtype: string splits: - name: train num_bytes: 334270 num_examples: 250 - name: valid num_bytes: 334270 num_examples: 250 - name: test num_bytes: 334270 num_examples: 250 download_size: 474801 dataset_size: 1002810 configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* ---
jlbaker361/actstu-dream-50	--- dataset_info: features: - name: image dtype: image - name: prompt dtype: string - name: seed dtype: int64 - name: steps dtype: int64 splits: - name: train num_bytes: 29844939.0 num_examples: 28 download_size: 29847370 dataset_size: 29844939.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
halaction/atm-data-transformers	--- license: openrail ---
allenai/ms2_dense_max	--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - apache-2.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - extended\|other-MS^2 - extended\|other-Cochrane task_categories: - summarization - text2text-generation paperswithcode_id: multi-document-summarization pretty_name: MSLR Shared Task --- This is a copy of the [MS^2](https://huggingface.co/datasets/allenai/mslr2022) dataset, except the input source documents of its `validation` split have been replaced by a __dense__ retriever. The retrieval pipeline used: - __query__: The `background` field of each example - __corpus__: The union of all documents in the `train`, `validation` and `test` splits. A document is the concatenation of the `title` and `abstract`. - __retriever__: [`facebook/contriever-msmarco`](https://huggingface.co/facebook/contriever-msmarco) via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) with default settings - __top-k strategy__: `"max"`, i.e. the number of documents retrieved, `k`, is set as the maximum number of documents seen across examples in this dataset, in this case `k==25` Retrieval results on the `train` set: \| Recall@100 \| Rprec \| Precision@k \| Recall@k \| \| ----------- \| ----------- \| ----------- \| ----------- \| \| 0.4764 \| 0.2395 \| 0.1932 \| 0.2895 \| Retrieval results on the `validation` set: \| Recall@100 \| Rprec \| Precision@k \| Recall@k \| \| ----------- \| ----------- \| ----------- \| ----------- \| \| 0.4364 \| 0.2125 \| 0.1823 \| 0.2524 \| Retrieval results on the `test` set: \| Recall@100 \| Rprec \| Precision@k \| Recall@k \| \| ----------- \| ----------- \| ----------- \| ----------- \| \| 0.4481 \| 0.2224 \| 0.1943 \| 0.2567 \|
ParallelnoMinded/promo_squad_ru	--- license: apache-2.0 ---
kailasv/ArtWhisperer	--- license: mit configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: user_id dtype: string - name: target_id dtype: string - name: target_image dtype: image - name: target_positive_prompt dtype: string - name: target_negative_prompt dtype: string - name: target_image_embedding sequence: - name: value dtype: float32 - name: target_positive_text_embedding sequence: - name: value dtype: float32 - name: target_negative_text_embedding sequence: - name: value dtype: float32 - name: Famous person? dtype: bool - name: Famous landmark? dtype: bool - name: Manmade? dtype: bool - name: People? dtype: bool - name: Real image? dtype: bool - name: AI image? dtype: bool - name: Art? dtype: bool - name: Nature? dtype: bool - name: City? dtype: bool - name: Fantasy? dtype: bool - name: Sci-fi or space? dtype: bool - name: generated_image dtype: image - name: generated_positive_prompt dtype: string - name: generated_negative_prompt dtype: string - name: generated_image_embedding sequence: - name: value dtype: float32 - name: generated_positive_text_embedding sequence: - name: value dtype: float32 - name: generated_negative_text_embedding sequence: - name: value dtype: float32 - name: ai_model_name dtype: string - name: trajectory_index dtype: int32 - name: score dtype: int32 - name: human_rating dtype: float32 - name: time_taken dtype: duration[s] - name: filtered_image dtype: bool splits: - name: train num_bytes: 5743017316.686 num_examples: 51026 - name: validation num_bytes: 475257048.94 num_examples: 4572 download_size: 2185134483 dataset_size: 6218274365.625999 ---
A2H0H0R1/Animal-nutrition-pair	--- dataset_info: features: - name: question dtype: string - name: response_j dtype: string - name: response_k dtype: string splits: - name: train num_bytes: 10252777 num_examples: 5027 download_size: 4012629 dataset_size: 10252777 configs: - config_name: default data_files: - split: train path: data/train-* ---
blanchon/FAIR1M_Small_Caption	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 5528315890.896 num_examples: 22312 download_size: 5560660833 dataset_size: 5528315890.896 configs: - config_name: default data_files: - split: train path: data/train-* ---
sdmattpotter/hftest61223	--- license: mit ---
DjSteker/dataset_ham_spam	--- dataset_info: features: - name: IsSpam struct: - name: '0' dtype: string - name: Text struct: - name: '0' dtype: string splits: - name: train num_bytes: 385 num_examples: 1 download_size: 3829 dataset_size: 385 configs: - config_name: default data_files: - split: train path: data/train-* ---
ziozzang/deepl-trans-IT-KO	--- task_categories: - translation language: - ko - it --- This dataset is some wikipedia article with DeepL translation, auto-aggregated. # String/Corpus pairs From IT/Italian to KO/Korean. # Quality Filtering - Stripping whole HTML tags. - removed references and annotation mark. - Filtered by string length. --- The strings/corpus are aggregated from wikipedia(pt) using DeepL translated. whole data collected by Jioh L. Jung<ziozzang@gmail.com> license: mit ---
M-A-D/Mixed-Arabic-Dataset-Main	--- language: - ar task_categories: - conversational - text-generation - text2text-generation - translation - summarization pretty_name: MAD configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: GenId dtype: int64 - name: SubId dtype: int64 - name: DatasetName dtype: string - name: DatasetLink dtype: string - name: Text dtype: string - name: MetaData struct: - name: AboutAuthor dtype: string - name: AboutBook dtype: string - name: Author dtype: string - name: AuthorName dtype: string - name: BookLink dtype: string - name: BookName dtype: string - name: ChapterLink dtype: string - name: ChapterName dtype: string - name: Tags dtype: float64 - name: __index_level_0__ dtype: float64 - name: created_date dtype: string - name: deleted dtype: bool - name: detoxify dtype: 'null' - name: emojis struct: - name: count sequence: int32 - name: name sequence: string - name: id dtype: string - name: labels struct: - name: count sequence: int32 - name: name sequence: string - name: value sequence: float64 - name: lang dtype: string - name: message_id dtype: string - name: message_tree_id dtype: string - name: model_name dtype: 'null' - name: parent_id dtype: string - name: query_id dtype: string - name: rank dtype: float64 - name: review_count dtype: float64 - name: review_result dtype: bool - name: role dtype: string - name: synthetic dtype: bool - name: title dtype: string - name: tree_state dtype: string - name: url dtype: string - name: user_id dtype: string - name: ConcatenatedText dtype: int64 - name: __index_level_0__ dtype: float64 splits: - name: train num_bytes: 1990497610 num_examples: 131393 download_size: 790648134 dataset_size: 1990497610 --- # Dataset Card for "Mixed-Arabic-Dataset" ## Mixed Arabic Datasets (MAD) The Mixed Arabic Datasets (MAD) project provides a comprehensive collection of diverse Arabic-language datasets, sourced from various repositories, platforms, and domains. These datasets cover a wide range of text types, including books, articles, Wikipedia content, stories, and more. ### MAD Repo vs. MAD Main #### MAD Repo - Versatility: In the MAD Repository (MAD Repo), datasets are made available in their original, native form. Researchers and practitioners can selectively download specific datasets that align with their specific interests or requirements. - Independent Access: Each dataset is self-contained, enabling users to work with individual datasets independently, allowing for focused analyses and experiments. #### MAD Main or simply MAD - Unified Dataframe: MAD Main represents a harmonized and unified dataframe, incorporating all datasets from the MAD Repository. It provides a seamless and consolidated view of the entire MAD collection, making it convenient for comprehensive analyses and applications. - Holistic Perspective: Researchers can access a broad spectrum of Arabic-language content within a single dataframe, promoting holistic exploration and insights across diverse text sources. ### Why MAD Main? - Efficiency: Working with MAD Main streamlines the data acquisition process by consolidating multiple datasets into one structured dataframe. This is particularly beneficial for large-scale projects or studies requiring diverse data sources. - Interoperability: With MAD Main, the datasets are integrated into a standardized format, enhancing interoperability and compatibility with a wide range of data processing and analysis tools. - Meta-Analysis: Researchers can conduct comprehensive analyses, such as cross-domain studies, trend analyses, or comparative studies, by leveraging the combined richness of all MAD datasets. ### Getting Started - To access individual datasets in their original form, refer to the MAD Repository ([Link to MAD Repo](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo)). - For a unified view of all datasets, conveniently organized in a dataframe, you are here in the right place. ```python from datasets import load_dataset dataset = load_dataset("M-A-D/Mixed-Arabic-Dataset-Main") ``` ### Join Us on Discord For discussions, contributions, and community interactions, join us on Discord! [![Discord](https://img.shields.io/discord/798499298231726101?label=Join%20us%20on%20Discord&logo=discord&logoColor=white&style=for-the-badge)](https://discord.gg/2NpJ9JGm) ### How to Contribute Want to contribute to the Mixed Arabic Datasets project? Follow our comprehensive guide on Google Colab for step-by-step instructions: [Contribution Guide](https://colab.research.google.com/drive/1w7_7lL6w7nM9DcDmTZe1Vfiwkio6SA-w?usp=sharing). Note: If you'd like to test a contribution before submitting it, feel free to do so on the [MAD Test Dataset](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Dataset-test). ## Citation ``` @dataset{ title = {Mixed Arabic Datasets (MAD)}, author = {MAD Community}, howpublished = {Dataset}, url = {https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo}, year = {2023}, } ```
ImruQays/Alukah-Arabic	--- language: - ar license: cc-by-4.0 --- # Introduction This dataset is a comprehensive collection of articles sourced from the Alukah website, a renowned platform offering extensive content primarily in Arabic. Alukah is known for its high-quality Arabic prose, significantly surpassing the standard found in contemporary media outlets. The majority of the articles are contributed by Muslim scholars, encompassing a wide range of topics related to Islam and the Muslim community. The dataset also includes a valuable section on fatwas, which could be instrumental in developing question-answer datasets for Islamic jurisprudence. ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Language(s) (NLP): [Arabic, minor content in other languages] - License: [Refer to [Alukah terms of use](https://www.alukah.net/pages/terms_of_use.aspx)] ### Dataset Sources <!-- Provide the basic links for the dataset. --> - Website: [https://www.alukah.net/] ## Uses The Alukah Arabic Articles Collection is particularly suitable for training large language models (LLMs) in Arabic. It offers a refined variant of the language that stands in contrast to the more commonly found less sophisticated forms in modern media. This dataset is an invaluable resource for: - Language Model Training: Enriching LLMs with high-quality Arabic data, enhancing their understanding and generation capabilities in the language. - Islamic Content Analysis: Providing a rich source of Islamic scholarly articles for research and analysis in religious studies, cultural studies, and linguistics. - Historical and Cultural Research: The dataset can be used as a reference for studying the evolution of Arabic language usage in scholarly contexts. ## Dataset Structure The dataset is organized into 9 files, each representing a distinct section of the Alukah website. It is important to note the potential for duplicate articles across these files, as some topics may overlap. ## Quality of Arabic Writing While the articles on Alukah showcase a superior level of Arabic compared to contemporary writings, it's important to acknowledge that even these articles may not fully match the exemplary standards of classical Arabic literature. For enthusiasts and researchers aiming to explore the pinnacle of Arabic literary excellence, it is recommended to refer to works that are over 200 years old or consult the book "العرنجية" for further insights into the nuances of high-quality Arabic prose.
ehcalabres/ravdess_speech	--- annotations_creators: - no-annotation language_creators: - found language: - en license: - cc-by-nc-sa-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - audio-classification task_ids: - speech-emotion-recognition --- # Dataset Card for ravdess_speech ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - Homepage: [Needs More Information] - Repository: https://zenodo.org/record/1188976#.YUS4MrozZdS - Paper: https://doi.org/10.1371/journal.pone.0196391 - Leaderboard: [Needs More Information] - Point of Contact: ravdess@gmail.com ### Dataset Summary The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) contains 24 professional actors (12 female, 12 male), vocalizing two lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. The conditions of the audio files are: 16bit, 48kHz .wav. ### Supported Tasks and Leaderboards - audio-classification: The dataset can be used to train a model for Audio Classification tasks, which consists in predict the latent emotion presented on the audios. ### Languages The audios available in the dataset are in English spoken by actors in a neutral North American accent. ## Dataset Structure ### Data Instances [Needs More Information] ### Data Fields [Needs More Information] ### Data Splits [Needs More Information] ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information The RAVDESS is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, CC BY-NC-SA 4.0 Commercial licenses for the RAVDESS can also be purchased. For more information, please visit our license fee page, or contact us at ravdess@gmail.com. ### Citation Information Livingstone SR, Russo FA (2018) The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. PLoS ONE 13(5): e0196391. https://doi.org/10.1371/journal.pone.0196391.
CountFloyd/bark-german-semantic-wav-training	--- language: - de ---
AdapterOcean/data-standardized_cluster_23_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: 7951640 num_examples: 6750 download_size: 3438336 dataset_size: 7951640 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "data-standardized_cluster_23_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
indiejoseph/wikipedia-en-filtered	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 49741517 num_examples: 17260 download_size: 27011805 dataset_size: 49741517 language: - en --- # Dataset Card for "wikipedia-en-filtered" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mask-distilled-one-sec-cv12/chunk_0	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1165136164 num_examples: 228817 download_size: 1184952464 dataset_size: 1165136164 --- # Dataset Card for "chunk_0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
PDBEurope/protein_chain_conformational_states	--- license: cc-by-4.0 language: - en size_categories: - 10K<n<100K task_categories: - feature-extraction tags: - Structural biology - Bioinformatics - Machine learning - Conformation - Conformational state - Monomeric - Training data - Benchmark - Manually curated pretty_name: Curated dataset of protein chain conformational states --- ## Schema description: The manually curated dataset of open-closed monomers is included here as `benchmarking_monomeric_open_closed_conformers.csv`. Column descriptions: ## Schema description: The manually curated dataset of open-closed monomers is included here as `benchmarking_monomeric_open_closed_conformers.csv`. Column descriptions: - `UNP_ACC` \| UniProt accession code - `UNP_START` \| Start of UniProt sequence for given PDBe entries - `UNP_END` \| End of UniProt sequence for given PDBe entries - `PDBe_ID` \| Protein Data Bank code - `CHAIN_ID` \| Author declared chain ID (`char`) - `label_asym_id` \| Programmatically assigned chain ID (`char`) - `CONFORMER_ID` \| Unique code for PDBe entries with distinct conformation, corresponding to a given UniProt accession - `CONFORMER_DESCR` \| Short description of conformation, based on depositor's assessment of the protein/conformation - `LIT_CONFIRMED` \| True/false value based on whether a publication (scientific literature) was available for manually curating clusters. NB: Clusters with 0 in this field should be used with caution. - `ALT_CONFORMER_ID` \| Where the publication for a structure is currently outstanding, an executive decision on the conformation classification is made. Where the literature is not explicit on the features of a given conformation, the second most suitable `CONFORMER_ID` is provided in this column. Blank cells have no other likely conformation assignmnt and are therefore the same as in `CONFORMER_ID`. - `ALT_CONFORMER_DESCR` \| Description for conformation in alternative conformation ID. ## Curation process As of 09 Mar 2022, a manually curated dataset of monomeric protein conformations has been collated, containing 'open'-'closed' pairs as well as intermediary states defined by the authors of the entry. 1. The PDBe was queried, through its Oracle DB, to find PDBe entries with 100 % sequence identity for a UniProt segment in both 'open' and 'closed' conformations, as stated in the entry's `TITLE` field. The query used: ``` select b.accession, b.unp_start, b.unp_end, a.id, a.title, d.id, d.title from entry a, unp_entity b, unp_entity c, entry d, pdb_assembly e where a.title like ‘%open%’ and d.title like ‘%close%’ and a.id = b.entry_id and d.id = c.entry_id and a.id != d.id and b.accession = c.accession and b.unp_start = c.unp_start and b.unp_end = c.unp_end and a.id = e.entry_id and e.type = ‘homo’ and e.name = ‘monomer’ ``` was written by Dr Sameer Velankar. 2. These results were cleaned to remove entries with 'open' or 'close' substrings in their `TITLE` fields that did not refer to conformation. The 'open' substring often appeared in ligand names in the entries' `TITLE` field, such as in dichlorido(1,3-dimethylbenzimidaz ol-2-ylidene)(eta5-pentamethylcyclopentadienyl)rhodium(III) and 'close' in terms like discloses. 3. All remaining entries were then manually curated by investigating each PDBe entry's corresponding publication, where available. 1. Additional PDBe entries submitted by the authors, which were missed in the original search due to a lack of 'open' or 'close' substrings in their `TITLE` field but stated as fitting one of the states in the publication, were added. 2. For some UniProt accessions, intermediary conformations were reported by the authors and these were noted in the dataset under the `CONFORMER_DESCR` column. 3. Entries deposited in monomeric form but solved as a multimeric complex were also removed. 4. PDBe entries, now clustered by author-stated conformation, were cross-referenced against the PDBe-KB's existing clustering algorithm (available on the [Aggregate Views of Proteins](https://www.ebi.ac.uk/pdbe/pdbe-kb/protein) page) to assess current conformer clustering success. These results are currently awaiting publication. ### Curation process outline <img src="http://ftp.ebi.ac.uk/pub/databases/pdbe-kb/benchmarking/distinct-monomer-conformers/work_progress_flowdiagram_200pc.png" alt="Curation flow diagram"> ### Dataset summary <img src="http://ftp.ebi.ac.uk/pub/databases/pdbe-kb/benchmarking/distinct-monomer-conformers/summary_data_visualisation.png" alt="Benchmark dataset summary graphs">
Back-up/facebook_comment_augmentation-v2	--- dataset_info: features: - name: id dtype: string - name: text dtype: string - name: hash dtype: int64 splits: - name: train num_bytes: 213595318.3206353 num_examples: 1328546 download_size: 119399417 dataset_size: 213595318.3206353 configs: - config_name: default data_files: - split: train path: data/train-* ---
Tohrumi/iwslt15_fuzzy_1000_train_samples	--- dataset_info: features: - name: id dtype: int64 - name: translation struct: - name: en dtype: string - name: vi dtype: string splits: - name: train num_bytes: 636042.8958904734 num_examples: 1000 - name: test num_bytes: 329197 num_examples: 1268 download_size: 574472 dataset_size: 965239.8958904734 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
anhtu12st/papers	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 45435 num_examples: 155 download_size: 28085 dataset_size: 45435 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "papers" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
japanese-asr/whisper_transcriptions.reazonspeech.all_22	--- dataset_info: config_name: all features: - name: name dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 30475531164.0 num_examples: 267733 download_size: 30239263328 dataset_size: 30475531164.0 configs: - config_name: all data_files: - split: train path: all/train-* ---
mlabonne/truthy-dpo-v0.1	--- language: - en dataset_info: features: - name: id dtype: string - name: source dtype: string - name: system dtype: string - name: question dtype: string - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 1344072 num_examples: 1016 download_size: 652993 dataset_size: 1344072 configs: - config_name: default data_files: - split: train path: data/train-* ---
fhaddad/autotrain-data-fhdd_arabic_chatbot	--- language: - en - ar task_categories: - translation --- # AutoTrain Dataset for project: fhdd_arabic_chatbot ## Dataset Description This dataset has been automatically processed by AutoTrain for project fhdd_arabic_chatbot. ### Languages The BCP-47 code for the dataset's language is en2ar. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_sourceLang": "ara", "feat_targetlang": "eng", "target": "\u064a\u0646\u0628\u063a\u064a \u0623\u0646 \u062a\u064f\u0638\u0647\u0631 \u0627\u0644\u0646\u0651\u0633\u0627\u0621 \u0648\u062c\u0648\u0647\u0647\u0646\u0651.", "source": "Women should have their faces visible." }, { "feat_sourceLang": "ara", "feat_targetlang": "eng", "target": "\u0623\u062a\u062f\u0631\u0633 \u0627\u0644\u0625\u0646\u062c\u0644\u064a\u0632\u064a\u0629\u061f", "source": "Do you study English?" } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_sourceLang": "Value(dtype='string', id=None)", "feat_targetlang": "Value(dtype='string', id=None)", "target": "Value(dtype='string', id=None)", "source": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 15622 \| \| valid \| 3906 \|
anan-2024/twitter_dataset_1713142048	--- 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: 192326 num_examples: 521 download_size: 106584 dataset_size: 192326 configs: - config_name: default data_files: - split: train path: data/train-* ---
datasets-examples/doc-formats-csv-3	--- configs: - config_name: default data_files: "data.csv" delimiter: "\|" header: 1 names: ["kind", "sound"] size_categories: - n<1K --- # [doc] formats - csv - 3 This dataset contains one csv file at the root: - [data.csv](./data.csv) ```csv # ignored comment col1\|col2 dog\|woof cat\|meow pokemon\|pika human\|hello ``` We define the config name in the YAML config, as well as the exact location of the file, the separator as `"\|"`, the name of the columns, and the number of rows to ignore (the row #1 is a row of column headers, that will be replaced by the `names` option, and the row #0 is ignored). The reference for the options is the [documentation of pandas.read_csv()](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html). ```yaml --- configs: - config_name: default data_files: "data.csv" delimiter: "\|" header: 1 names: ["kind", "sound"] size_categories: - n<1K --- ```
fathyshalab/massive_social-de-DE	--- dataset_info: features: - name: id dtype: string - name: locale dtype: string - name: partition dtype: string - name: scenario dtype: class_label: names: '0': social '1': transport '2': calendar '3': play '4': news '5': datetime '6': recommendation '7': email '8': iot '9': general '10': audio '11': lists '12': qa '13': cooking '14': takeaway '15': music '16': alarm '17': weather - name: intent dtype: class_label: names: '0': datetime_query '1': iot_hue_lightchange '2': transport_ticket '3': takeaway_query '4': qa_stock '5': general_greet '6': recommendation_events '7': music_dislikeness '8': iot_wemo_off '9': cooking_recipe '10': qa_currency '11': transport_traffic '12': general_quirky '13': weather_query '14': audio_volume_up '15': email_addcontact '16': takeaway_order '17': email_querycontact '18': iot_hue_lightup '19': recommendation_locations '20': play_audiobook '21': lists_createoradd '22': news_query '23': alarm_query '24': iot_wemo_on '25': general_joke '26': qa_definition '27': social_query '28': music_settings '29': audio_volume_other '30': calendar_remove '31': iot_hue_lightdim '32': calendar_query '33': email_sendemail '34': iot_cleaning '35': audio_volume_down '36': play_radio '37': cooking_query '38': datetime_convert '39': qa_maths '40': iot_hue_lightoff '41': iot_hue_lighton '42': transport_query '43': music_likeness '44': email_query '45': play_music '46': audio_volume_mute '47': social_post '48': alarm_set '49': qa_factoid '50': calendar_set '51': play_game '52': alarm_remove '53': lists_remove '54': transport_taxi '55': recommendation_movies '56': iot_coffee '57': music_query '58': play_podcasts '59': lists_query - name: text dtype: string - name: annot_utt dtype: string - name: worker_id dtype: string - name: slot_method sequence: - name: slot dtype: string - name: method dtype: string - name: judgments sequence: - name: worker_id dtype: string - name: intent_score dtype: int8 - name: slots_score dtype: int8 - name: grammar_score dtype: int8 - name: spelling_score dtype: int8 - name: language_identification dtype: string - name: label_name dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 129790 num_examples: 391 - name: validation num_bytes: 22472 num_examples: 68 - name: test num_bytes: 34107 num_examples: 106 download_size: 70328 dataset_size: 186369 --- # Dataset Card for "massive_social-de-DE" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
316usman/thematic2aembed	--- license: bsd dataset_info: features: - name: text dtype: string - name: thematic dtype: string - name: sub-thematic dtype: string - name: country dtype: string - name: document_url dtype: string - name: source_url dtype: string splits: - name: train num_bytes: 691745022 num_examples: 908625 download_size: 205106568 dataset_size: 691745022 configs: - config_name: default data_files: - split: train path: data/train-* ---
gilsonk12/Rastreando	--- license: openrail ---
shreyasharma/sentence_eval_aa2	--- dataset_info: features: - name: declarativized dtype: string - name: correct dtype: bool splits: - name: train num_bytes: 35463 num_examples: 615 - name: validation num_bytes: 18279 num_examples: 315 - name: test num_bytes: 17185 num_examples: 300 download_size: 56380 dataset_size: 70927 --- # Dataset Card for "sentence_eval_aa2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
RikeshSilwal/nepali_corpora	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1725683703 num_examples: 3253409 download_size: 496020433 dataset_size: 1725683703 configs: - config_name: default data_files: - split: train path: data/train-* ---
yankihue/tweets-turkish	--- language: - tr ---
taspecustu/Nanachi	--- license: cc-by-4.0 ---
ikala/tmmluplus	--- license: other license_name: creative-commons-by-nc task_categories: - question-answering language: - zh tags: - traditional chinese - finance - medical - taiwan - benchmark - zh-tw - zh-hant pretty_name: tmmlu++ size_categories: - 100K<n<1M configs: - config_name: engineering_math data_files: - split: train path: "data/engineering_math_dev.csv" - split: validation path: "data/engineering_math_val.csv" - split: test path: "data/engineering_math_test.csv" - config_name: dentistry data_files: - split: train path: "data/dentistry_dev.csv" - split: validation path: "data/dentistry_val.csv" - split: test path: "data/dentistry_test.csv" - config_name: traditional_chinese_medicine_clinical_medicine data_files: - split: train path: "data/traditional_chinese_medicine_clinical_medicine_dev.csv" - split: validation path: "data/traditional_chinese_medicine_clinical_medicine_val.csv" - split: test path: "data/traditional_chinese_medicine_clinical_medicine_test.csv" - config_name: clinical_psychology data_files: - split: train path: "data/clinical_psychology_dev.csv" - split: validation path: "data/clinical_psychology_val.csv" - split: test path: "data/clinical_psychology_test.csv" - config_name: technical data_files: - split: train path: "data/technical_dev.csv" - split: validation path: "data/technical_val.csv" - split: test path: "data/technical_test.csv" - config_name: culinary_skills data_files: - split: train path: "data/culinary_skills_dev.csv" - split: validation path: "data/culinary_skills_val.csv" - split: test path: "data/culinary_skills_test.csv" - config_name: mechanical data_files: - split: train path: "data/mechanical_dev.csv" - split: validation path: "data/mechanical_val.csv" - split: test path: "data/mechanical_test.csv" - config_name: logic_reasoning data_files: - split: train path: "data/logic_reasoning_dev.csv" - split: validation path: "data/logic_reasoning_val.csv" - split: test path: "data/logic_reasoning_test.csv" - config_name: real_estate data_files: - split: train path: "data/real_estate_dev.csv" - split: validation path: "data/real_estate_val.csv" - split: test path: "data/real_estate_test.csv" - config_name: general_principles_of_law data_files: - split: train path: "data/general_principles_of_law_dev.csv" - split: validation path: "data/general_principles_of_law_val.csv" - split: test path: "data/general_principles_of_law_test.csv" - config_name: finance_banking data_files: - split: train path: "data/finance_banking_dev.csv" - split: validation path: "data/finance_banking_val.csv" - split: test path: "data/finance_banking_test.csv" - config_name: anti_money_laundering data_files: - split: train path: "data/anti_money_laundering_dev.csv" - split: validation path: "data/anti_money_laundering_val.csv" - split: test path: "data/anti_money_laundering_test.csv" - config_name: ttqav2 data_files: - split: train path: "data/ttqav2_dev.csv" - split: validation path: "data/ttqav2_val.csv" - split: test path: "data/ttqav2_test.csv" - config_name: marketing_management data_files: - split: train path: "data/marketing_management_dev.csv" - split: validation path: "data/marketing_management_val.csv" - split: test path: "data/marketing_management_test.csv" - config_name: business_management data_files: - split: train path: "data/business_management_dev.csv" - split: validation path: "data/business_management_val.csv" - split: test path: "data/business_management_test.csv" - config_name: organic_chemistry data_files: - split: train path: "data/organic_chemistry_dev.csv" - split: validation path: "data/organic_chemistry_val.csv" - split: test path: "data/organic_chemistry_test.csv" - config_name: advance_chemistry data_files: - split: train path: "data/advance_chemistry_dev.csv" - split: validation path: "data/advance_chemistry_val.csv" - split: test path: "data/advance_chemistry_test.csv" - config_name: physics data_files: - split: train path: "data/physics_dev.csv" - split: validation path: "data/physics_val.csv" - split: test path: "data/physics_test.csv" - config_name: secondary_physics data_files: - split: train path: "data/secondary_physics_dev.csv" - split: validation path: "data/secondary_physics_val.csv" - split: test path: "data/secondary_physics_test.csv" - config_name: human_behavior data_files: - split: train path: "data/human_behavior_dev.csv" - split: validation path: "data/human_behavior_val.csv" - split: test path: "data/human_behavior_test.csv" - config_name: national_protection data_files: - split: train path: "data/national_protection_dev.csv" - split: validation path: "data/national_protection_val.csv" - split: test path: "data/national_protection_test.csv" - config_name: jce_humanities data_files: - split: train path: "data/jce_humanities_dev.csv" - split: validation path: "data/jce_humanities_val.csv" - split: test path: "data/jce_humanities_test.csv" - config_name: politic_science data_files: - split: train path: "data/politic_science_dev.csv" - split: validation path: "data/politic_science_val.csv" - split: test path: "data/politic_science_test.csv" - config_name: agriculture data_files: - split: train path: "data/agriculture_dev.csv" - split: validation path: "data/agriculture_val.csv" - split: test path: "data/agriculture_test.csv" - config_name: official_document_management data_files: - split: train path: "data/official_document_management_dev.csv" - split: validation path: "data/official_document_management_val.csv" - split: test path: "data/official_document_management_test.csv" - config_name: financial_analysis data_files: - split: train path: "data/financial_analysis_dev.csv" - split: validation path: "data/financial_analysis_val.csv" - split: test path: "data/financial_analysis_test.csv" - config_name: pharmacy data_files: - split: train path: "data/pharmacy_dev.csv" - split: validation path: "data/pharmacy_val.csv" - split: test path: "data/pharmacy_test.csv" - config_name: educational_psychology data_files: - split: train path: "data/educational_psychology_dev.csv" - split: validation path: "data/educational_psychology_val.csv" - split: test path: "data/educational_psychology_test.csv" - config_name: statistics_and_machine_learning data_files: - split: train path: "data/statistics_and_machine_learning_dev.csv" - split: validation path: "data/statistics_and_machine_learning_val.csv" - split: test path: "data/statistics_and_machine_learning_test.csv" - config_name: management_accounting data_files: - split: train path: "data/management_accounting_dev.csv" - split: validation path: "data/management_accounting_val.csv" - split: test path: "data/management_accounting_test.csv" - config_name: introduction_to_law data_files: - split: train path: "data/introduction_to_law_dev.csv" - split: validation path: "data/introduction_to_law_val.csv" - split: test path: "data/introduction_to_law_test.csv" - config_name: computer_science data_files: - split: train path: "data/computer_science_dev.csv" - split: validation path: "data/computer_science_val.csv" - split: test path: "data/computer_science_test.csv" - config_name: veterinary_pathology data_files: - split: train path: "data/veterinary_pathology_dev.csv" - split: validation path: "data/veterinary_pathology_val.csv" - split: test path: "data/veterinary_pathology_test.csv" - config_name: accounting data_files: - split: train path: "data/accounting_dev.csv" - split: validation path: "data/accounting_val.csv" - split: test path: "data/accounting_test.csv" - config_name: fire_science data_files: - split: train path: "data/fire_science_dev.csv" - split: validation path: "data/fire_science_val.csv" - split: test path: "data/fire_science_test.csv" - config_name: optometry data_files: - split: train path: "data/optometry_dev.csv" - split: validation path: "data/optometry_val.csv" - split: test path: "data/optometry_test.csv" - config_name: insurance_studies data_files: - split: train path: "data/insurance_studies_dev.csv" - split: validation path: "data/insurance_studies_val.csv" - split: test path: "data/insurance_studies_test.csv" - config_name: pharmacology data_files: - split: train path: "data/pharmacology_dev.csv" - split: validation path: "data/pharmacology_val.csv" - split: test path: "data/pharmacology_test.csv" - config_name: taxation data_files: - split: train path: "data/taxation_dev.csv" - split: validation path: "data/taxation_val.csv" - split: test path: "data/taxation_test.csv" - config_name: trust_practice data_files: - split: train path: "data/trust_practice_dev.csv" - split: validation path: "data/trust_practice_val.csv" - split: test path: "data/trust_practice_test.csv" - config_name: geography_of_taiwan data_files: - split: train path: "data/geography_of_taiwan_dev.csv" - split: validation path: "data/geography_of_taiwan_val.csv" - split: test path: "data/geography_of_taiwan_test.csv" - config_name: physical_education data_files: - split: train path: "data/physical_education_dev.csv" - split: validation path: "data/physical_education_val.csv" - split: test path: "data/physical_education_test.csv" - config_name: auditing data_files: - split: train path: "data/auditing_dev.csv" - split: validation path: "data/auditing_val.csv" - split: test path: "data/auditing_test.csv" - config_name: administrative_law data_files: - split: train path: "data/administrative_law_dev.csv" - split: validation path: "data/administrative_law_val.csv" - split: test path: "data/administrative_law_test.csv" - config_name: education_(profession_level) data_files: - split: train path: "data/education_(profession_level)_dev.csv" - split: validation path: "data/education_(profession_level)_val.csv" - split: test path: "data/education_(profession_level)_test.csv" - config_name: economics data_files: - split: train path: "data/economics_dev.csv" - split: validation path: "data/economics_val.csv" - split: test path: "data/economics_test.csv" - config_name: veterinary_pharmacology data_files: - split: train path: "data/veterinary_pharmacology_dev.csv" - split: validation path: "data/veterinary_pharmacology_val.csv" - split: test path: "data/veterinary_pharmacology_test.csv" - config_name: nautical_science data_files: - split: train path: "data/nautical_science_dev.csv" - split: validation path: "data/nautical_science_val.csv" - split: test path: "data/nautical_science_test.csv" - config_name: occupational_therapy_for_psychological_disorders data_files: - split: train path: "data/occupational_therapy_for_psychological_disorders_dev.csv" - split: validation path: "data/occupational_therapy_for_psychological_disorders_val.csv" - split: test path: "data/occupational_therapy_for_psychological_disorders_test.csv" - config_name: basic_medical_science data_files: - split: train path: "data/basic_medical_science_dev.csv" - split: validation path: "data/basic_medical_science_val.csv" - split: test path: "data/basic_medical_science_test.csv" - config_name: macroeconomics data_files: - split: train path: "data/macroeconomics_dev.csv" - split: validation path: "data/macroeconomics_val.csv" - split: test path: "data/macroeconomics_test.csv" - config_name: trade data_files: - split: train path: "data/trade_dev.csv" - split: validation path: "data/trade_val.csv" - split: test path: "data/trade_test.csv" - config_name: chinese_language_and_literature data_files: - split: train path: "data/chinese_language_and_literature_dev.csv" - split: validation path: "data/chinese_language_and_literature_val.csv" - split: test path: "data/chinese_language_and_literature_test.csv" - config_name: tve_design data_files: - split: train path: "data/tve_design_dev.csv" - split: validation path: "data/tve_design_val.csv" - split: test path: "data/tve_design_test.csv" - config_name: junior_science_exam data_files: - split: train path: "data/junior_science_exam_dev.csv" - split: validation path: "data/junior_science_exam_val.csv" - split: test path: "data/junior_science_exam_test.csv" - config_name: junior_math_exam data_files: - split: train path: "data/junior_math_exam_dev.csv" - split: validation path: "data/junior_math_exam_val.csv" - split: test path: "data/junior_math_exam_test.csv" - config_name: junior_chinese_exam data_files: - split: train path: "data/junior_chinese_exam_dev.csv" - split: validation path: "data/junior_chinese_exam_val.csv" - split: test path: "data/junior_chinese_exam_test.csv" - config_name: junior_social_studies data_files: - split: train path: "data/junior_social_studies_dev.csv" - split: validation path: "data/junior_social_studies_val.csv" - split: test path: "data/junior_social_studies_test.csv" - config_name: tve_mathematics data_files: - split: train path: "data/tve_mathematics_dev.csv" - split: validation path: "data/tve_mathematics_val.csv" - split: test path: "data/tve_mathematics_test.csv" - config_name: tve_chinese_language data_files: - split: train path: "data/tve_chinese_language_dev.csv" - split: validation path: "data/tve_chinese_language_val.csv" - split: test path: "data/tve_chinese_language_test.csv" - config_name: tve_natural_sciences data_files: - split: train path: "data/tve_natural_sciences_dev.csv" - split: validation path: "data/tve_natural_sciences_val.csv" - split: test path: "data/tve_natural_sciences_test.csv" - config_name: junior_chemistry data_files: - split: train path: "data/junior_chemistry_dev.csv" - split: validation path: "data/junior_chemistry_val.csv" - split: test path: "data/junior_chemistry_test.csv" - config_name: music data_files: - split: train path: "data/music_dev.csv" - split: validation path: "data/music_val.csv" - split: test path: "data/music_test.csv" - config_name: education data_files: - split: train path: "data/education_dev.csv" - split: validation path: "data/education_val.csv" - split: test path: "data/education_test.csv" - config_name: three_principles_of_people data_files: - split: train path: "data/three_principles_of_people_dev.csv" - split: validation path: "data/three_principles_of_people_val.csv" - split: test path: "data/three_principles_of_people_test.csv" - config_name: taiwanese_hokkien data_files: - split: train path: "data/taiwanese_hokkien_dev.csv" - split: validation path: "data/taiwanese_hokkien_val.csv" - split: test path: "data/taiwanese_hokkien_test.csv" --- # TMMLU+ : Large scale traditional chinese massive multitask language understanding <p align="center"> <img src="https://huggingface.co/datasets/ikala/tmmluplus/resolve/main/cover.png" alt="A close-up image of a neat paper note with a white background. The text 'TMMLU+' is written horizontally across the center of the note in bold, black. Join us to work in multimodal LLM : https://ikala.ai/recruit/" style="max-width: 400" width=400 /> </p> We present TMMLU+, a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset featuring 66 subjects, ranging from elementary to professional level. The TMMLU+ dataset is six times larger and contains more balanced subjects compared to its predecessor, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We have included benchmark results in TMMLU+ from closed-source models and 20 open-weight Chinese large language models, with parameters ranging from 1.8B to 72B. The benchmark results show that Traditional Chinese variants still lag behind those trained on major Simplified Chinese models. ```python from datasets import load_dataset task_list = [ 'engineering_math', 'dentistry', 'traditional_chinese_medicine_clinical_medicine', 'clinical_psychology', 'technical', 'culinary_skills', 'mechanical', 'logic_reasoning', 'real_estate', 'general_principles_of_law', 'finance_banking', 'anti_money_laundering', 'ttqav2', 'marketing_management', 'business_management', 'organic_chemistry', 'advance_chemistry', 'physics', 'secondary_physics', 'human_behavior', 'national_protection', 'jce_humanities', 'politic_science', 'agriculture', 'official_document_management', 'financial_analysis', 'pharmacy', 'educational_psychology', 'statistics_and_machine_learning', 'management_accounting', 'introduction_to_law', 'computer_science', 'veterinary_pathology', 'accounting', 'fire_science', 'optometry', 'insurance_studies', 'pharmacology', 'taxation', 'trust_practice', 'geography_of_taiwan', 'physical_education', 'auditing', 'administrative_law', 'education_(profession_level)', 'economics', 'veterinary_pharmacology', 'nautical_science', 'occupational_therapy_for_psychological_disorders', 'basic_medical_science', 'macroeconomics', 'trade', 'chinese_language_and_literature', 'tve_design', 'junior_science_exam', 'junior_math_exam', 'junior_chinese_exam', 'junior_social_studies', 'tve_mathematics', 'tve_chinese_language', 'tve_natural_sciences', 'junior_chemistry', 'music', 'education', 'three_principles_of_people', 'taiwanese_hokkien' ] for task in task_list: val = load_dataset('ikala/tmmluplus', task)['validation'] dev = load_dataset('ikala/tmmluplus', task)['train'] test = load_dataset('ikala/tmmluplus', task)['test'] ``` For each dataset split ```python for row in test: print(row) break >> Dataset({ features: ['question', 'A', 'B', 'C', 'D', 'answer'], num_rows: 11 }) ``` Statistic on all four categories : STEM, Social Science, Humanities, Other \| Category \| Test \| Dev \| Validation \| \|----------------------------------\|-------\|------\|------------\| \| STEM \| 3458 \| 70 \| 385 \| \| Social Sciences \| 5958 \| 90 \| 665 \| \| Humanities \| 1763 \| 35 \| 197 \| \| Other (Business, Health, Misc.) \| 8939 \| 135 \| 995 \| \| Total \| 20118 \| 330 \| 2242 \| ## Benchmark on direct prompting \| model \| STEM \| Social Science \| Humanities \| Other \| Average \| \|------------\|------------\|------------\|------------\|------------\|------------\| \| [Qwen/Qwen-72B](https://huggingface.co/Qwen/Qwen-72B) \| 61.12 \| 71.65 \| 63.00 \| 61.31 \|64.27\| \| gpt-4-0613 \| 60.36 \| 67.36 \| 56.03 \| 57.62 \|60.34\| \| [Qwen/Qwen-72B-Chat](https://huggingface.co/Qwen/Qwen-72B-Chat) \| 55.15 \| 66.20 \| 55.65 \| 57.19 \|58.55\| \| [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) \| 46.94 \| 56.69 \| 49.43 \| 48.81 \|50.47\| \| Gemini-pro \| 45.38 \| 57.29 \| 48.80 \| 48.21 \|49.92\| \| [01-ai/Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat) \| 40.24 \| 56.77 \| 53.99 \| 47.58 \|49.64\| \| [Qwen/Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat) \| 43.86 \| 53.29 \| 44.78 \| 45.13 \|46.77\| \| [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat) \| 39.62 \| 50.24 \| 44.44 \| 44.26 \|44.64\| \| Claude-1.3 \| 42.65 \| 49.33 \| 42.16 \| 44.14 \|44.57\| \| gpt-3.5-turbo-0613 \| 41.56 \| 46.72 \| 36.73 \| 42.03 \|41.76\| \| [CausalLM/14B](https://huggingface.co/CausalLM/14B) \| 39.83 \| 44.50 \| 39.61 \| 41.97 \|41.48\| \| [Skywork/Skywork-13B-base](https://huggingface.co/Skywork/Skywork-13B-base) \| 36.93 \| 47.27 \| 41.04 \| 40.10 \|41.33\| \| [Qwen/Qwen-7B](https://huggingface.co/Qwen/Qwen-7B) \| 37.53 \| 45.48 \| 38.09 \| 38.96 \|40.01\| \| [Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) \| 33.32 \| 44.64 \| 40.27 \| 39.89 \|39.53\| \| [vivo-ai/BlueLM-7B-Base](https://huggingface.co/vivo-ai/BlueLM-7B-Base) \| 33.94 \| 41.52 \| 37.38 \| 38.74 \|37.90\| \| [baichuan-inc/Baichuan2-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat) \| 29.64 \| 43.73 \| 37.36 \| 39.88 \|37.65\| \| [Qwen/Qwen-1_8B](https://huggingface.co/Qwen/Qwen-1_8B) \| 32.65 \| 38.95 \| 38.34 \| 35.27 \|36.30\| \| Claude-2 \| 39.65 \| 39.09 \| 28.59 \| 37.47 \|36.20\| \| [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) \| 31.05 \| 39.31 \| 35.64 \| 35.60 \|35.40\| \| [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat) \| 29.82 \| 42.29 \| 34.24 \| 34.31 \|35.17\| \| [CausalLM/7B](https://huggingface.co/CausalLM/7B) \| 31.03 \| 38.17 \| 35.87 \| 35.39 \|35.11\| \| [Azure99/blossom-v3_1-mistral-7b](https://huggingface.co/Azure99/blossom-v3_1-mistral-7b) \| 32.80 \| 36.91 \| 32.36 \| 34.53 \|34.15\| \| [microsoft/Orca-2-13b](https://huggingface.co/microsoft/Orca-2-13b) \| 24.69 \| 39.18 \| 33.60 \| 31.99 \|32.37\| \| [Qwen/Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat) \| 26.60 \| 36.36 \| 31.81 \| 31.96 \|31.68\| \| [TigerResearch/tigerbot-13b-chat-v3](https://huggingface.co/TigerResearch/tigerbot-13b-chat-v3) \| 24.73 \| 29.63 \| 25.72 \| 27.22 \|26.82\| \| [hongyin/mistral-7b-80k](https://huggingface.co/hongyin/mistral-7b-80k) \| 24.26 \| 23.76 \| 22.56 \| 24.57 \|23.79\| \| [deepseek-ai/deepseek-llm-67b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat) \| 19.10 \| 26.06 \| 21.51 \| 21.77 \|22.11\| \| [yentinglin/Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) \| 18.53 \| 27.65 \| 17.77 \| 21.49 \|21.36\| \| [GeneZC/MiniChat-3B](https://huggingface.co/GeneZC/MiniChat-3B) \| 17.66 \| 23.35 \| 22.71 \| 20.34 \|21.02\| \| [LinkSoul/Chinese-Llama-2-7b](https://huggingface.co/LinkSoul/Chinese-Llama-2-7b) \| 16.55 \| 18.39 \| 12.97 \| 16.13 \|16.01\| \| [yentinglin/Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) \| 14.99 \| 16.23 \| 15.00 \| 16.22 \|15.61\| \| Claude-instant-1 \| 12.52 \| 17.13 \| 15.10 \| 13.57 \|14.58\| \| [FlagAlpha/Atom-7B](https://huggingface.co/FlagAlpha/Atom-7B) \| 5.60 \| 13.57 \| 7.71 \| 11.84 \|9.68\| Results via [ievals](https://github.com/iKala/ievals) ( settings : 0-shot direct answering ) # Citation ``` @article{ikala2024improved, title={An Improved Traditional Chinese Evaluation Suite for Foundation Model}, author={Tam, Zhi-Rui and Pai, Ya-Ting and Lee, Yen-Wei and Cheng, Sega and Shuai, Hong-Han}, journal={arXiv preprint arXiv:2403.01858}, year={2024} } ```
ealtan/MoodBooster	--- license: mit ---
kheopss/lettre_admin_f1.0_regenerated	--- dataset_info: features: - name: input dtype: string - name: response dtype: string - name: text dtype: string - name: text2 dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 4462522 num_examples: 697 download_size: 1690790 dataset_size: 4462522 configs: - config_name: default data_files: - split: train path: data/train-* ---
vitaliy-sharandin/pollution-krakow-no2-co	--- dataset_info: features: - name: NO2 dtype: float64 - name: CO dtype: float64 - name: dt dtype: timestamp[ns] splits: - name: train num_bytes: 6816 num_examples: 284 download_size: 9084 dataset_size: 6816 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "pollution-krakow-no2-co" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
natnitaract/SciBench-TruthfulQA-RAG	--- license: apache-2.0 task_categories: - multiple-choice ---
Falah/portrait_prompts	--- dataset_info: features: - name: prompts dtype: string splits: - name: train num_bytes: 22213518 num_examples: 100000 download_size: 2797158 dataset_size: 22213518 --- # Dataset Card for "portrait_prompts" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
MohammedNasri/163762AASRnoDiacs	--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 147266551704 num_examples: 153322 - name: test num_bytes: 10027423544 num_examples: 10440 download_size: 23754042731 dataset_size: 157293975248 --- # Dataset Card for "163762AASRnoDiacs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
rombodawg/code_instruct_alpaca_vicuna_wizardlm_56k_backup	--- license: other --- Backup of code_instruct_alpaca_vicuna_wizardlm used in rombodawg/MegaCodeTraining112k Link to the combined dataset bellow https://huggingface.co/datasets/rombodawg/MegaCodeTraining112k
open-llm-leaderboard/details_max-2022__test_mistral2	--- pretty_name: Evaluation run of max-2022/test_mistral2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [max-2022/test_mistral2](https://huggingface.co/max-2022/test_mistral2) 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_max-2022__test_mistral2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-11T22:17:01.815383](https://huggingface.co/datasets/open-llm-leaderboard/details_max-2022__test_mistral2/blob/main/results_2024-02-11T22-17-01.815383.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\": 0.24710575900369156,\n\ \ \"acc_stderr\": 0.03055560450787355,\n \"acc_norm\": 0.24800687316365916,\n\ \ \"acc_norm_stderr\": 0.0313664960522948,\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862666,\n \"mc2\": 0.490951583190258,\n\ \ \"mc2_stderr\": 0.016977888460336696\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.23037542662116042,\n \"acc_stderr\": 0.01230492841874761,\n\ \ \"acc_norm\": 0.2790102389078498,\n \"acc_norm_stderr\": 0.013106784883601338\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.2575184226249751,\n\ \ \"acc_stderr\": 0.004363736410689625,\n \"acc_norm\": 0.25323640709022105,\n\ \ \"acc_norm_stderr\": 0.004339764434219064\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036846,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n\ \ \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2074074074074074,\n\ \ \"acc_stderr\": 0.03502553170678318,\n \"acc_norm\": 0.2074074074074074,\n\ \ \"acc_norm_stderr\": 0.03502553170678318\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.03523807393012047,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.03523807393012047\n \ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.27,\n\ \ \"acc_stderr\": 0.0446196043338474,\n \"acc_norm\": 0.27,\n \ \ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.23773584905660378,\n \"acc_stderr\": 0.0261998088075619,\n\ \ \"acc_norm\": 0.23773584905660378,\n \"acc_norm_stderr\": 0.0261998088075619\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2013888888888889,\n\ \ \"acc_stderr\": 0.033536474697138406,\n \"acc_norm\": 0.2013888888888889,\n\ \ \"acc_norm_stderr\": 0.033536474697138406\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\"\ : 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.24,\n\ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.042923469599092816,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.042923469599092816\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.26011560693641617,\n\ \ \"acc_stderr\": 0.03345036916788991,\n \"acc_norm\": 0.26011560693641617,\n\ \ \"acc_norm_stderr\": 0.03345036916788991\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.04158307533083286,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.04158307533083286\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.3276595744680851,\n \"acc_stderr\": 0.03068302084323101,\n\ \ \"acc_norm\": 0.3276595744680851,\n \"acc_norm_stderr\": 0.03068302084323101\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813344,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813344\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.2206896551724138,\n \"acc_stderr\": 0.03455930201924812,\n\ \ \"acc_norm\": 0.2206896551724138,\n \"acc_norm_stderr\": 0.03455930201924812\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2566137566137566,\n \"acc_stderr\": 0.022494510767503154,\n \"\ acc_norm\": 0.2566137566137566,\n \"acc_norm_stderr\": 0.022494510767503154\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.03670066451047181,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.03670066451047181\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.23870967741935484,\n \"acc_stderr\": 0.024251071262208837,\n \"\ acc_norm\": 0.23870967741935484,\n \"acc_norm_stderr\": 0.024251071262208837\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.21182266009852216,\n \"acc_stderr\": 0.02874898368994106,\n \"\ acc_norm\": 0.21182266009852216,\n \"acc_norm_stderr\": 0.02874898368994106\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.2909090909090909,\n \"acc_stderr\": 0.03546563019624336,\n\ \ \"acc_norm\": 0.2909090909090909,\n \"acc_norm_stderr\": 0.03546563019624336\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.16161616161616163,\n \"acc_stderr\": 0.026225919863629283,\n \"\ acc_norm\": 0.16161616161616163,\n \"acc_norm_stderr\": 0.026225919863629283\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.3005181347150259,\n \"acc_stderr\": 0.0330881859441575,\n\ \ \"acc_norm\": 0.3005181347150259,\n \"acc_norm_stderr\": 0.0330881859441575\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.2153846153846154,\n \"acc_stderr\": 0.020843034557462878,\n\ \ \"acc_norm\": 0.2153846153846154,\n \"acc_norm_stderr\": 0.020843034557462878\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.25925925925925924,\n \"acc_stderr\": 0.02671924078371215,\n \ \ \"acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.02671924078371215\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.2184873949579832,\n \"acc_stderr\": 0.026841514322958934,\n\ \ \"acc_norm\": 0.2184873949579832,\n \"acc_norm_stderr\": 0.026841514322958934\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2052980132450331,\n \"acc_stderr\": 0.03297986648473834,\n \"\ acc_norm\": 0.2052980132450331,\n \"acc_norm_stderr\": 0.03297986648473834\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.26055045871559634,\n \"acc_stderr\": 0.018819182034850068,\n \"\ acc_norm\": 0.26055045871559634,\n \"acc_norm_stderr\": 0.018819182034850068\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.3055555555555556,\n \"acc_stderr\": 0.03141554629402543,\n \"\ acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.03141554629402543\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.3094170403587444,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.3094170403587444,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.29770992366412213,\n \"acc_stderr\": 0.040103589424622034,\n\ \ \"acc_norm\": 0.29770992366412213,\n \"acc_norm_stderr\": 0.040103589424622034\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.21487603305785125,\n \"acc_stderr\": 0.037494924487096966,\n \"\ acc_norm\": 0.21487603305785125,\n \"acc_norm_stderr\": 0.037494924487096966\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.04330043749650743,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.04330043749650743\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.20535714285714285,\n\ \ \"acc_stderr\": 0.03834241021419073,\n \"acc_norm\": 0.20535714285714285,\n\ \ \"acc_norm_stderr\": 0.03834241021419073\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.1650485436893204,\n \"acc_stderr\": 0.036756688322331886,\n\ \ \"acc_norm\": 0.1650485436893204,\n \"acc_norm_stderr\": 0.036756688322331886\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2692307692307692,\n\ \ \"acc_stderr\": 0.029058588303748842,\n \"acc_norm\": 0.2692307692307692,\n\ \ \"acc_norm_stderr\": 0.029058588303748842\n },\n \"harness\|hendrycksTest-medical_genetics\|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-miscellaneous\|5\": {\n \"acc\": 0.2515964240102171,\n\ \ \"acc_stderr\": 0.015517322365529627,\n \"acc_norm\": 0.2515964240102171,\n\ \ \"acc_norm_stderr\": 0.015517322365529627\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.23410404624277456,\n \"acc_stderr\": 0.02279711027807113,\n\ \ \"acc_norm\": 0.23410404624277456,\n \"acc_norm_stderr\": 0.02279711027807113\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2346368715083799,\n\ \ \"acc_stderr\": 0.014173044098303665,\n \"acc_norm\": 0.2346368715083799,\n\ \ \"acc_norm_stderr\": 0.014173044098303665\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.02380518652488815,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02380518652488815\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.22508038585209003,\n\ \ \"acc_stderr\": 0.023720088516179027,\n \"acc_norm\": 0.22508038585209003,\n\ \ \"acc_norm_stderr\": 0.023720088516179027\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2777777777777778,\n \"acc_stderr\": 0.024922001168886324,\n\ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.024922001168886324\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.2730496453900709,\n \"acc_stderr\": 0.026577860943307847,\n \ \ \"acc_norm\": 0.2730496453900709,\n \"acc_norm_stderr\": 0.026577860943307847\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.24771838331160365,\n\ \ \"acc_stderr\": 0.011025499291443737,\n \"acc_norm\": 0.24771838331160365,\n\ \ \"acc_norm_stderr\": 0.011025499291443737\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.2536764705882353,\n \"acc_stderr\": 0.026431329870789527,\n\ \ \"acc_norm\": 0.2536764705882353,\n \"acc_norm_stderr\": 0.026431329870789527\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.2630718954248366,\n \"acc_stderr\": 0.017812676542320657,\n \ \ \"acc_norm\": 0.2630718954248366,\n \"acc_norm_stderr\": 0.017812676542320657\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.2909090909090909,\n\ \ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.2909090909090909,\n\ \ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.2163265306122449,\n \"acc_stderr\": 0.026358916334904052,\n\ \ \"acc_norm\": 0.2163265306122449,\n \"acc_norm_stderr\": 0.026358916334904052\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.22388059701492538,\n\ \ \"acc_stderr\": 0.029475250236017176,\n \"acc_norm\": 0.22388059701492538,\n\ \ \"acc_norm_stderr\": 0.029475250236017176\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.30120481927710846,\n\ \ \"acc_stderr\": 0.0357160923005348,\n \"acc_norm\": 0.30120481927710846,\n\ \ \"acc_norm_stderr\": 0.0357160923005348\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.2982456140350877,\n \"acc_stderr\": 0.03508771929824563,\n\ \ \"acc_norm\": 0.2982456140350877,\n \"acc_norm_stderr\": 0.03508771929824563\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862666,\n \"mc2\": 0.490951583190258,\n\ \ \"mc2_stderr\": 0.016977888460336696\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.48539857932123126,\n \"acc_stderr\": 0.014046492383275834\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/max-2022/test_mistral2 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_11T22_17_01.815383 path: - '/details_harness\|arc:challenge\|25_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-11T22-17-01.815383.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|gsm8k\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hellaswag\|10_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T22-17-01.815383.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-11T22-17-01.815383.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '/details_harness\|winogrande\|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-11T22-17-01.815383.parquet' - config_name: results data_files: - split: 2024_02_11T22_17_01.815383 path: - results_2024-02-11T22-17-01.815383.parquet - split: latest path: - results_2024-02-11T22-17-01.815383.parquet --- # Dataset Card for Evaluation run of max-2022/test_mistral2 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [max-2022/test_mistral2](https://huggingface.co/max-2022/test_mistral2) 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_max-2022__test_mistral2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-11T22:17:01.815383](https://huggingface.co/datasets/open-llm-leaderboard/details_max-2022__test_mistral2/blob/main/results_2024-02-11T22-17-01.815383.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": 0.24710575900369156, "acc_stderr": 0.03055560450787355, "acc_norm": 0.24800687316365916, "acc_norm_stderr": 0.0313664960522948, "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862666, "mc2": 0.490951583190258, "mc2_stderr": 0.016977888460336696 }, "harness\|arc:challenge\|25": { "acc": 0.23037542662116042, "acc_stderr": 0.01230492841874761, "acc_norm": 0.2790102389078498, "acc_norm_stderr": 0.013106784883601338 }, "harness\|hellaswag\|10": { "acc": 0.2575184226249751, "acc_stderr": 0.004363736410689625, "acc_norm": 0.25323640709022105, "acc_norm_stderr": 0.004339764434219064 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.2, "acc_stderr": 0.04020151261036846, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036846 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2074074074074074, "acc_stderr": 0.03502553170678318, "acc_norm": 0.2074074074074074, "acc_norm_stderr": 0.03502553170678318 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.25, "acc_stderr": 0.03523807393012047, "acc_norm": 0.25, "acc_norm_stderr": 0.03523807393012047 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.23773584905660378, "acc_stderr": 0.0261998088075619, "acc_norm": 0.23773584905660378, "acc_norm_stderr": 0.0261998088075619 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2013888888888889, "acc_stderr": 0.033536474697138406, "acc_norm": 0.2013888888888889, "acc_norm_stderr": 0.033536474697138406 }, "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": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.24, "acc_stderr": 0.042923469599092816, "acc_norm": 0.24, "acc_norm_stderr": 0.042923469599092816 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.26011560693641617, "acc_stderr": 0.03345036916788991, "acc_norm": 0.26011560693641617, "acc_norm_stderr": 0.03345036916788991 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.22549019607843138, "acc_stderr": 0.04158307533083286, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.04158307533083286 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3276595744680851, "acc_stderr": 0.03068302084323101, "acc_norm": 0.3276595744680851, "acc_norm_stderr": 0.03068302084323101 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813344, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813344 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.2206896551724138, "acc_stderr": 0.03455930201924812, "acc_norm": 0.2206896551724138, "acc_norm_stderr": 0.03455930201924812 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2566137566137566, "acc_stderr": 0.022494510767503154, "acc_norm": 0.2566137566137566, "acc_norm_stderr": 0.022494510767503154 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.21428571428571427, "acc_stderr": 0.03670066451047181, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.03670066451047181 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.23870967741935484, "acc_stderr": 0.024251071262208837, "acc_norm": 0.23870967741935484, "acc_norm_stderr": 0.024251071262208837 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.21182266009852216, "acc_stderr": 0.02874898368994106, "acc_norm": 0.21182266009852216, "acc_norm_stderr": 0.02874898368994106 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.2909090909090909, "acc_stderr": 0.03546563019624336, "acc_norm": 0.2909090909090909, "acc_norm_stderr": 0.03546563019624336 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.16161616161616163, "acc_stderr": 0.026225919863629283, "acc_norm": 0.16161616161616163, "acc_norm_stderr": 0.026225919863629283 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.3005181347150259, "acc_stderr": 0.0330881859441575, "acc_norm": 0.3005181347150259, "acc_norm_stderr": 0.0330881859441575 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.2153846153846154, "acc_stderr": 0.020843034557462878, "acc_norm": 0.2153846153846154, "acc_norm_stderr": 0.020843034557462878 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.25925925925925924, "acc_stderr": 0.02671924078371215, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.02671924078371215 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.2184873949579832, "acc_stderr": 0.026841514322958934, "acc_norm": 0.2184873949579832, "acc_norm_stderr": 0.026841514322958934 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2052980132450331, "acc_stderr": 0.03297986648473834, "acc_norm": 0.2052980132450331, "acc_norm_stderr": 0.03297986648473834 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.26055045871559634, "acc_stderr": 0.018819182034850068, "acc_norm": 0.26055045871559634, "acc_norm_stderr": 0.018819182034850068 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.3055555555555556, "acc_stderr": 0.03141554629402543, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.03141554629402543 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.3094170403587444, "acc_stderr": 0.03102441174057221, "acc_norm": 0.3094170403587444, "acc_norm_stderr": 0.03102441174057221 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.29770992366412213, "acc_stderr": 0.040103589424622034, "acc_norm": 0.29770992366412213, "acc_norm_stderr": 0.040103589424622034 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.21487603305785125, "acc_stderr": 0.037494924487096966, "acc_norm": 0.21487603305785125, "acc_norm_stderr": 0.037494924487096966 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.04330043749650743, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.04330043749650743 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.22085889570552147, "acc_stderr": 0.03259177392742178, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.03259177392742178 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.20535714285714285, "acc_stderr": 0.03834241021419073, "acc_norm": 0.20535714285714285, "acc_norm_stderr": 0.03834241021419073 }, "harness\|hendrycksTest-management\|5": { "acc": 0.1650485436893204, "acc_stderr": 0.036756688322331886, "acc_norm": 0.1650485436893204, "acc_norm_stderr": 0.036756688322331886 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.2692307692307692, "acc_stderr": 0.029058588303748842, "acc_norm": 0.2692307692307692, "acc_norm_stderr": 0.029058588303748842 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.2515964240102171, "acc_stderr": 0.015517322365529627, "acc_norm": 0.2515964240102171, "acc_norm_stderr": 0.015517322365529627 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.23410404624277456, "acc_stderr": 0.02279711027807113, "acc_norm": 0.23410404624277456, "acc_norm_stderr": 0.02279711027807113 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2346368715083799, "acc_stderr": 0.014173044098303665, "acc_norm": 0.2346368715083799, "acc_norm_stderr": 0.014173044098303665 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.2222222222222222, "acc_stderr": 0.02380518652488815, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.02380518652488815 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.22508038585209003, "acc_stderr": 0.023720088516179027, "acc_norm": 0.22508038585209003, "acc_norm_stderr": 0.023720088516179027 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.024922001168886324, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.024922001168886324 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.2730496453900709, "acc_stderr": 0.026577860943307847, "acc_norm": 0.2730496453900709, "acc_norm_stderr": 0.026577860943307847 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.24771838331160365, "acc_stderr": 0.011025499291443737, "acc_norm": 0.24771838331160365, "acc_norm_stderr": 0.011025499291443737 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.2536764705882353, "acc_stderr": 0.026431329870789527, "acc_norm": 0.2536764705882353, "acc_norm_stderr": 0.026431329870789527 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.2630718954248366, "acc_stderr": 0.017812676542320657, "acc_norm": 0.2630718954248366, "acc_norm_stderr": 0.017812676542320657 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.2909090909090909, "acc_stderr": 0.04350271442923243, "acc_norm": 0.2909090909090909, "acc_norm_stderr": 0.04350271442923243 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.2163265306122449, "acc_stderr": 0.026358916334904052, "acc_norm": 0.2163265306122449, "acc_norm_stderr": 0.026358916334904052 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.22388059701492538, "acc_stderr": 0.029475250236017176, "acc_norm": 0.22388059701492538, "acc_norm_stderr": 0.029475250236017176 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.30120481927710846, "acc_stderr": 0.0357160923005348, "acc_norm": 0.30120481927710846, "acc_norm_stderr": 0.0357160923005348 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.2982456140350877, "acc_stderr": 0.03508771929824563, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.03508771929824563 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862666, "mc2": 0.490951583190258, "mc2_stderr": 0.016977888460336696 }, "harness\|winogrande\|5": { "acc": 0.48539857932123126, "acc_stderr": 0.014046492383275834 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- 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hemanth955/Gold-alpaca-med-small-final	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: Input dtype: string - name: Output dtype: int64 - name: Instruction dtype: string - name: Text dtype: string splits: - name: train num_bytes: 48641940 num_examples: 27360 download_size: 10550533 dataset_size: 48641940 --- # Dataset Card for "Gold-alpaca-med-small-final" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k	--- pretty_name: Evaluation run of CallComply/SOLAR-10.7B-Instruct-v1.0-128k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CallComply/SOLAR-10.7B-Instruct-v1.0-128k](https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k)\ \ 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_CallComply__SOLAR-10.7B-Instruct-v1.0-128k\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-14T22:38:12.148949](https://huggingface.co/datasets/open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k/blob/main/results_2024-01-14T22-38-12.148949.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\": 0.5736345987046274,\n\ \ \"acc_stderr\": 0.033417579618165875,\n \"acc_norm\": 0.5822139213719528,\n\ \ \"acc_norm_stderr\": 0.03421698352385503,\n \"mc1\": 0.48592411260709917,\n\ \ \"mc1_stderr\": 0.017496563717042793,\n \"mc2\": 0.6542262778057006,\n\ \ \"mc2_stderr\": 0.015681013574816827\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6262798634812287,\n \"acc_stderr\": 0.014137708601759091,\n\ \ \"acc_norm\": 0.659556313993174,\n \"acc_norm_stderr\": 0.013847460518892973\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6415056761601274,\n\ \ \"acc_stderr\": 0.004785781979354868,\n \"acc_norm\": 0.8434574785899224,\n\ \ \"acc_norm_stderr\": 0.003626262805442223\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.562962962962963,\n\ \ \"acc_stderr\": 0.04284958639753401,\n \"acc_norm\": 0.562962962962963,\n\ \ \"acc_norm_stderr\": 0.04284958639753401\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.625,\n \"acc_stderr\": 0.039397364351956274,\n \ \ \"acc_norm\": 0.625,\n \"acc_norm_stderr\": 0.039397364351956274\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6188679245283019,\n \"acc_stderr\": 0.02989060968628664,\n\ \ \"acc_norm\": 0.6188679245283019,\n \"acc_norm_stderr\": 0.02989060968628664\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6527777777777778,\n\ \ \"acc_stderr\": 0.039812405437178615,\n \"acc_norm\": 0.6527777777777778,\n\ \ \"acc_norm_stderr\": 0.039812405437178615\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\": 0.48,\n\ \ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.48,\n \ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099522,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099522\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5659574468085107,\n \"acc_stderr\": 0.03240038086792747,\n\ \ \"acc_norm\": 0.5659574468085107,\n \"acc_norm_stderr\": 0.03240038086792747\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3508771929824561,\n\ \ \"acc_stderr\": 0.04489539350270699,\n \"acc_norm\": 0.3508771929824561,\n\ \ \"acc_norm_stderr\": 0.04489539350270699\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555497,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555497\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3412698412698413,\n \"acc_stderr\": 0.024419234966819064,\n \"\ acc_norm\": 0.3412698412698413,\n \"acc_norm_stderr\": 0.024419234966819064\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.35714285714285715,\n\ \ \"acc_stderr\": 0.04285714285714281,\n \"acc_norm\": 0.35714285714285715,\n\ \ \"acc_norm_stderr\": 0.04285714285714281\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.6387096774193548,\n\ \ \"acc_stderr\": 0.027327548447957543,\n \"acc_norm\": 0.6387096774193548,\n\ \ \"acc_norm_stderr\": 0.027327548447957543\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4088669950738916,\n \"acc_stderr\": 0.034590588158832314,\n\ \ \"acc_norm\": 0.4088669950738916,\n \"acc_norm_stderr\": 0.034590588158832314\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\ : 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6424242424242425,\n \"acc_stderr\": 0.03742597043806585,\n\ \ \"acc_norm\": 0.6424242424242425,\n \"acc_norm_stderr\": 0.03742597043806585\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7676767676767676,\n \"acc_stderr\": 0.03008862949021749,\n \"\ acc_norm\": 0.7676767676767676,\n \"acc_norm_stderr\": 0.03008862949021749\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.844559585492228,\n \"acc_stderr\": 0.02614848346915332,\n\ \ \"acc_norm\": 0.844559585492228,\n \"acc_norm_stderr\": 0.02614848346915332\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5769230769230769,\n \"acc_stderr\": 0.025049197876042338,\n\ \ \"acc_norm\": 0.5769230769230769,\n \"acc_norm_stderr\": 0.025049197876042338\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2814814814814815,\n \"acc_stderr\": 0.027420019350945284,\n \ \ \"acc_norm\": 0.2814814814814815,\n \"acc_norm_stderr\": 0.027420019350945284\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6302521008403361,\n \"acc_stderr\": 0.03135709599613591,\n \ \ \"acc_norm\": 0.6302521008403361,\n \"acc_norm_stderr\": 0.03135709599613591\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.763302752293578,\n \"acc_stderr\": 0.018224078117299106,\n \"\ acc_norm\": 0.763302752293578,\n \"acc_norm_stderr\": 0.018224078117299106\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4212962962962963,\n \"acc_stderr\": 0.03367462138896078,\n \"\ acc_norm\": 0.4212962962962963,\n \"acc_norm_stderr\": 0.03367462138896078\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7352941176470589,\n \"acc_stderr\": 0.030964517926923403,\n \"\ acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.030964517926923403\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7341772151898734,\n \"acc_stderr\": 0.02875679962965834,\n \ \ \"acc_norm\": 0.7341772151898734,\n \"acc_norm_stderr\": 0.02875679962965834\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6367713004484304,\n\ \ \"acc_stderr\": 0.032277904428505,\n \"acc_norm\": 0.6367713004484304,\n\ \ \"acc_norm_stderr\": 0.032277904428505\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6946564885496184,\n \"acc_stderr\": 0.040393149787245605,\n\ \ \"acc_norm\": 0.6946564885496184,\n \"acc_norm_stderr\": 0.040393149787245605\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8016528925619835,\n \"acc_stderr\": 0.03640118271990948,\n \"\ acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.03640118271990948\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7177914110429447,\n \"acc_stderr\": 0.03536117886664742,\n\ \ \"acc_norm\": 0.7177914110429447,\n \"acc_norm_stderr\": 0.03536117886664742\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.41964285714285715,\n\ \ \"acc_stderr\": 0.046840993210771065,\n \"acc_norm\": 0.41964285714285715,\n\ \ \"acc_norm_stderr\": 0.046840993210771065\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7475728155339806,\n \"acc_stderr\": 0.04301250399690878,\n\ \ \"acc_norm\": 0.7475728155339806,\n \"acc_norm_stderr\": 0.04301250399690878\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8205128205128205,\n\ \ \"acc_stderr\": 0.025140935950335445,\n \"acc_norm\": 0.8205128205128205,\n\ \ \"acc_norm_stderr\": 0.025140935950335445\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939098,\n \ \ \"acc_norm\": 0.63,\n \"acc_norm_stderr\": 0.04852365870939098\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7547892720306514,\n\ \ \"acc_stderr\": 0.015384352284543932,\n \"acc_norm\": 0.7547892720306514,\n\ \ \"acc_norm_stderr\": 0.015384352284543932\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6734104046242775,\n \"acc_stderr\": 0.025248264774242836,\n\ \ \"acc_norm\": 0.6734104046242775,\n \"acc_norm_stderr\": 0.025248264774242836\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.31620111731843575,\n\ \ \"acc_stderr\": 0.015551673652172544,\n \"acc_norm\": 0.31620111731843575,\n\ \ \"acc_norm_stderr\": 0.015551673652172544\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.630718954248366,\n \"acc_stderr\": 0.027634176689602653,\n\ \ \"acc_norm\": 0.630718954248366,\n \"acc_norm_stderr\": 0.027634176689602653\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6077170418006431,\n\ \ \"acc_stderr\": 0.027731258647011994,\n \"acc_norm\": 0.6077170418006431,\n\ \ \"acc_norm_stderr\": 0.027731258647011994\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6265432098765432,\n \"acc_stderr\": 0.026915003011380154,\n\ \ \"acc_norm\": 0.6265432098765432,\n \"acc_norm_stderr\": 0.026915003011380154\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4148936170212766,\n \"acc_stderr\": 0.029392236584612503,\n \ \ \"acc_norm\": 0.4148936170212766,\n \"acc_norm_stderr\": 0.029392236584612503\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.423728813559322,\n\ \ \"acc_stderr\": 0.012620785155885992,\n \"acc_norm\": 0.423728813559322,\n\ \ \"acc_norm_stderr\": 0.012620785155885992\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5073529411764706,\n \"acc_stderr\": 0.030369552523902173,\n\ \ \"acc_norm\": 0.5073529411764706,\n \"acc_norm_stderr\": 0.030369552523902173\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6045751633986928,\n \"acc_stderr\": 0.019780465954777518,\n \ \ \"acc_norm\": 0.6045751633986928,\n \"acc_norm_stderr\": 0.019780465954777518\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6181818181818182,\n\ \ \"acc_stderr\": 0.04653429807913508,\n \"acc_norm\": 0.6181818181818182,\n\ \ \"acc_norm_stderr\": 0.04653429807913508\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7142857142857143,\n \"acc_stderr\": 0.0289205832206756,\n\ \ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.0289205832206756\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.4975124378109453,\n\ \ \"acc_stderr\": 0.03535490150137288,\n \"acc_norm\": 0.4975124378109453,\n\ \ \"acc_norm_stderr\": 0.03535490150137288\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5,\n \ \ \"acc_stderr\": 0.03892494720807614,\n \"acc_norm\": 0.5,\n \"\ acc_norm_stderr\": 0.03892494720807614\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7485380116959064,\n \"acc_stderr\": 0.033275044238468436,\n\ \ \"acc_norm\": 0.7485380116959064,\n \"acc_norm_stderr\": 0.033275044238468436\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.48592411260709917,\n\ \ \"mc1_stderr\": 0.017496563717042793,\n \"mc2\": 0.6542262778057006,\n\ \ \"mc2_stderr\": 0.015681013574816827\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8050513022888713,\n \"acc_stderr\": 0.011134099415938256\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0712661106899166,\n \ \ \"acc_stderr\": 0.0070864621279544985\n }\n}\n```" repo_url: https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k 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_14T22_38_12.148949 path: - '/details_harness\|arc:challenge\|25_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-14T22-38-12.148949.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|gsm8k\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hellaswag\|10_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T22-38-12.148949.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-14T22-38-12.148949.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '/details_harness\|winogrande\|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-14T22-38-12.148949.parquet' - config_name: results data_files: - split: 2024_01_14T22_38_12.148949 path: - results_2024-01-14T22-38-12.148949.parquet - split: latest path: - results_2024-01-14T22-38-12.148949.parquet --- # Dataset Card for Evaluation run of CallComply/SOLAR-10.7B-Instruct-v1.0-128k <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [CallComply/SOLAR-10.7B-Instruct-v1.0-128k](https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k) 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_CallComply__SOLAR-10.7B-Instruct-v1.0-128k", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-14T22:38:12.148949](https://huggingface.co/datasets/open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k/blob/main/results_2024-01-14T22-38-12.148949.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": 0.5736345987046274, "acc_stderr": 0.033417579618165875, "acc_norm": 0.5822139213719528, "acc_norm_stderr": 0.03421698352385503, "mc1": 0.48592411260709917, "mc1_stderr": 0.017496563717042793, "mc2": 0.6542262778057006, "mc2_stderr": 0.015681013574816827 }, "harness\|arc:challenge\|25": { "acc": 0.6262798634812287, "acc_stderr": 0.014137708601759091, "acc_norm": 0.659556313993174, "acc_norm_stderr": 0.013847460518892973 }, "harness\|hellaswag\|10": { "acc": 0.6415056761601274, "acc_stderr": 0.004785781979354868, "acc_norm": 0.8434574785899224, "acc_norm_stderr": 0.003626262805442223 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.625, "acc_stderr": 0.039397364351956274, "acc_norm": 0.625, "acc_norm_stderr": 0.039397364351956274 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6188679245283019, "acc_stderr": 0.02989060968628664, "acc_norm": 0.6188679245283019, "acc_norm_stderr": 0.02989060968628664 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6527777777777778, "acc_stderr": 0.039812405437178615, "acc_norm": 0.6527777777777778, "acc_norm_stderr": 0.039812405437178615 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099522, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099522 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5659574468085107, "acc_stderr": 0.03240038086792747, "acc_norm": 0.5659574468085107, "acc_norm_stderr": 0.03240038086792747 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.3508771929824561, "acc_stderr": 0.04489539350270699, "acc_norm": 0.3508771929824561, "acc_norm_stderr": 0.04489539350270699 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555497, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555497 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3412698412698413, "acc_stderr": 0.024419234966819064, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.024419234966819064 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.35714285714285715, "acc_stderr": 0.04285714285714281, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.04285714285714281 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6387096774193548, "acc_stderr": 0.027327548447957543, "acc_norm": 0.6387096774193548, "acc_norm_stderr": 0.027327548447957543 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4088669950738916, "acc_stderr": 0.034590588158832314, "acc_norm": 0.4088669950738916, "acc_norm_stderr": 0.034590588158832314 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6424242424242425, "acc_stderr": 0.03742597043806585, "acc_norm": 0.6424242424242425, "acc_norm_stderr": 0.03742597043806585 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7676767676767676, "acc_stderr": 0.03008862949021749, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.03008862949021749 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.844559585492228, "acc_stderr": 0.02614848346915332, "acc_norm": 0.844559585492228, "acc_norm_stderr": 0.02614848346915332 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5769230769230769, "acc_stderr": 0.025049197876042338, "acc_norm": 0.5769230769230769, "acc_norm_stderr": 0.025049197876042338 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2814814814814815, "acc_stderr": 0.027420019350945284, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.027420019350945284 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6302521008403361, "acc_stderr": 0.03135709599613591, "acc_norm": 0.6302521008403361, "acc_norm_stderr": 0.03135709599613591 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.763302752293578, "acc_stderr": 0.018224078117299106, "acc_norm": 0.763302752293578, "acc_norm_stderr": 0.018224078117299106 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4212962962962963, "acc_stderr": 0.03367462138896078, "acc_norm": 0.4212962962962963, "acc_norm_stderr": 0.03367462138896078 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7352941176470589, "acc_stderr": 0.030964517926923403, "acc_norm": 0.7352941176470589, "acc_norm_stderr": 0.030964517926923403 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7341772151898734, "acc_stderr": 0.02875679962965834, "acc_norm": 0.7341772151898734, "acc_norm_stderr": 0.02875679962965834 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6367713004484304, "acc_stderr": 0.032277904428505, "acc_norm": 0.6367713004484304, "acc_norm_stderr": 0.032277904428505 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6946564885496184, "acc_stderr": 0.040393149787245605, "acc_norm": 0.6946564885496184, "acc_norm_stderr": 0.040393149787245605 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8016528925619835, "acc_stderr": 0.03640118271990948, "acc_norm": 0.8016528925619835, "acc_norm_stderr": 0.03640118271990948 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7177914110429447, "acc_stderr": 0.03536117886664742, "acc_norm": 0.7177914110429447, "acc_norm_stderr": 0.03536117886664742 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.41964285714285715, "acc_stderr": 0.046840993210771065, "acc_norm": 0.41964285714285715, "acc_norm_stderr": 0.046840993210771065 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7475728155339806, "acc_stderr": 0.04301250399690878, "acc_norm": 0.7475728155339806, "acc_norm_stderr": 0.04301250399690878 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8205128205128205, "acc_stderr": 0.025140935950335445, "acc_norm": 0.8205128205128205, "acc_norm_stderr": 0.025140935950335445 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.63, "acc_stderr": 0.04852365870939098, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939098 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7547892720306514, "acc_stderr": 0.015384352284543932, "acc_norm": 0.7547892720306514, "acc_norm_stderr": 0.015384352284543932 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6734104046242775, "acc_stderr": 0.025248264774242836, "acc_norm": 0.6734104046242775, "acc_norm_stderr": 0.025248264774242836 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.31620111731843575, "acc_stderr": 0.015551673652172544, "acc_norm": 0.31620111731843575, "acc_norm_stderr": 0.015551673652172544 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.630718954248366, "acc_stderr": 0.027634176689602653, "acc_norm": 0.630718954248366, "acc_norm_stderr": 0.027634176689602653 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6077170418006431, "acc_stderr": 0.027731258647011994, "acc_norm": 0.6077170418006431, "acc_norm_stderr": 0.027731258647011994 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6265432098765432, "acc_stderr": 0.026915003011380154, "acc_norm": 0.6265432098765432, "acc_norm_stderr": 0.026915003011380154 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4148936170212766, "acc_stderr": 0.029392236584612503, "acc_norm": 0.4148936170212766, "acc_norm_stderr": 0.029392236584612503 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.423728813559322, "acc_stderr": 0.012620785155885992, "acc_norm": 0.423728813559322, "acc_norm_stderr": 0.012620785155885992 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5073529411764706, "acc_stderr": 0.030369552523902173, "acc_norm": 0.5073529411764706, "acc_norm_stderr": 0.030369552523902173 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6045751633986928, "acc_stderr": 0.019780465954777518, "acc_norm": 0.6045751633986928, "acc_norm_stderr": 0.019780465954777518 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6181818181818182, "acc_stderr": 0.04653429807913508, "acc_norm": 0.6181818181818182, "acc_norm_stderr": 0.04653429807913508 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7142857142857143, "acc_stderr": 0.0289205832206756, "acc_norm": 0.7142857142857143, "acc_norm_stderr": 0.0289205832206756 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.4975124378109453, "acc_stderr": 0.03535490150137288, "acc_norm": 0.4975124378109453, "acc_norm_stderr": 0.03535490150137288 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5, "acc_stderr": 0.03892494720807614, "acc_norm": 0.5, "acc_norm_stderr": 0.03892494720807614 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7485380116959064, "acc_stderr": 0.033275044238468436, "acc_norm": 0.7485380116959064, "acc_norm_stderr": 0.033275044238468436 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.48592411260709917, "mc1_stderr": 0.017496563717042793, "mc2": 0.6542262778057006, "mc2_stderr": 0.015681013574816827 }, "harness\|winogrande\|5": { "acc": 0.8050513022888713, "acc_stderr": 0.011134099415938256 }, "harness\|gsm8k\|5": { "acc": 0.0712661106899166, "acc_stderr": 0.0070864621279544985 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section 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CyberHarem/ikebukuro_akiha_idolmastercinderellagirls	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of ikebukuro_akiha/池袋晶葉 (THE iDOLM@STER: Cinderella Girls) This is the dataset of ikebukuro_akiha/池袋晶葉 (THE iDOLM@STER: Cinderella Girls), containing 190 images and their tags. The core tags of this character are `brown_hair, glasses, brown_eyes, twintails, long_hair, semi-rimless_eyewear, bangs, pink-framed_eyewear, under-rim_eyewear, blunt_bangs, bow, ribbon`, 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 \| 190 \| 180.09 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 190 \| 125.54 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 443 \| 258.99 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 190 \| 165.75 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 443 \| 327.91 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/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/ikebukuro_akiha_idolmastercinderellagirls', 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 \| 6 \| ![](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, ponytail, ribbed_sweater, solo, turtleneck_sweater, labcoat, looking_at_viewer, simple_background, smile, white_background, large_breasts, red_sweater, blush, hair_bow, long_sleeves, sidelocks, skirt \| \| 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, solo, serafuku, skirt, labcoat, smile, blush, white_background \| \| 2 \| 5 \| ![](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, blue_sailor_collar, blue_skirt, labcoat, long_sleeves, looking_at_viewer, pleated_skirt, red_bow, simple_background, solo, hair_bow, serafuku, shirt, white_background, closed_mouth, grin, sitting \| \| 3 \| 11 \| ![](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, blue_skirt, blush, labcoat, long_sleeves, looking_at_viewer, open_clothes, pleated_skirt, solo, white_background, hair_ribbon, serafuku, simple_background, blue_sailor_collar, red_bow, red_ribbon, sidelocks, blue_shirt, smile, collarbone, v-shaped_eyebrows, closed_mouth, hand_up, red-framed_eyewear, signature, white_shirt \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, solo, black_thighhighs, grin, belt, labcoat, rabbit_ears \| \| 5 \| 5 \| ![](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, blush, looking_at_viewer, navel, nipples, solo, collarbone, pussy, red-framed_eyewear, small_breasts, completely_nude, depth_of_field, open_mouth, sidelocks, standing, sweat, :o, bar_censor, blurry_background, convenient_censoring, cowboy_shot, dutch_angle, groin, hair_bow, medium_breasts, onsen, rectangular_eyewear, red_bow, sitting, steam, v-shaped_eyebrows, very_long_hair \| \| 6 \| 7 \| ![](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, solo, collarbone, double_bun, midriff, necklace, sidelocks, blush, bracelet, looking_at_viewer, short_sleeves, blue_shorts, clothes_around_waist, clothes_writing, navel, off_shoulder, short_shorts, breasts, crop_top, denim_shorts, grin, hair_bow, hair_ribbon, star_(symbol), white_shirt, x_hair_ornament \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| ponytail \| ribbed_sweater \| solo \| turtleneck_sweater \| labcoat \| looking_at_viewer \| simple_background \| smile \| white_background \| large_breasts \| red_sweater \| blush \| hair_bow \| long_sleeves \| sidelocks \| skirt \| serafuku \| blue_sailor_collar \| blue_skirt \| pleated_skirt \| red_bow \| shirt \| closed_mouth \| grin \| sitting \| open_clothes \| hair_ribbon \| red_ribbon \| blue_shirt \| collarbone \| v-shaped_eyebrows \| hand_up \| red-framed_eyewear \| signature \| white_shirt \| black_thighhighs \| belt \| rabbit_ears \| navel \| nipples \| pussy \| small_breasts \| completely_nude \| depth_of_field \| open_mouth \| standing \| sweat \| :o \| bar_censor \| blurry_background \| convenient_censoring \| cowboy_shot \| dutch_angle \| groin \| medium_breasts \| onsen \| rectangular_eyewear \| steam \| very_long_hair \| double_bun \| midriff \| necklace \| bracelet \| short_sleeves \| blue_shorts \| clothes_around_waist \| clothes_writing \| off_shoulder \| short_shorts \| breasts \| crop_top \| denim_shorts \| star_(symbol) \| x_hair_ornament \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-----------\|:-----------------\|:-------\|:---------------------\|:----------\|:--------------------\|:--------------------\|:--------\|:-------------------\|:----------------\|:--------------\|:--------\|:-----------\|:---------------\|:------------\|:--------\|:-----------\|:---------------------\|:-------------\|:----------------\|:----------\|:--------\|:---------------\|:-------\|:----------\|:---------------\|:--------------\|:-------------\|:-------------\|:-------------\|:--------------------\|:----------\|:---------------------\|:------------\|:--------------\|:-------------------\|:-------\|:--------------\|:--------\|:----------\|:--------\|:----------------\|:------------------\|:-----------------\|:-------------\|:-----------\|:--------\|:-----\|:-------------\|:--------------------\|:-----------------------\|:--------------\|:--------------\|:--------\|:-----------------\|:--------\|:----------------------\|:--------\|:-----------------\|:-------------\|:----------\|:-----------\|:-----------\|:----------------\|:--------------\|:-----------------------\|:------------------\|:---------------\|:---------------\|:----------\|:-----------\|:---------------\|:----------------\|:------------------\| \| 0 \| 6 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 5 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 11 \| ![](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 \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| \| \| X \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 5 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| \| \| X \| \| \| X \| \| \| \| \| \| X \| X \| \| X \| \| \| \| \| \| X \| \| \| \| X \| \| \| \| \| X \| X \| \| X \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 7 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| X \| \| \| X \| \| \| X \| \| \| \| \| \| X \| X \| \| X \| \| \| \| \| \| \| \| \| X \| \| \| X \| \| \| X \| \| \| \| \| X \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
one-sec-cv12/chunk_57	--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 25320557952.0 num_examples: 263624 download_size: 23104462381 dataset_size: 25320557952.0 --- # Dataset Card for "chunk_57" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
yzhuang/metatree_fri_c3_1000_50	--- dataset_info: features: - name: id dtype: int64 - name: X sequence: float64 - name: y dtype: int64 splits: - name: train num_bytes: 304920 num_examples: 726 - name: validation num_bytes: 115080 num_examples: 274 download_size: 504483 dataset_size: 420000 --- # Dataset Card for "metatree_fri_c3_1000_50" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
lamini/lamini_docs	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 1846734.3 num_examples: 1260 - name: test num_bytes: 205192.7 num_examples: 140 download_size: 698607 dataset_size: 2051927.0 --- # Dataset Card for "lamini_docs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
sgjwong/ltedi23-models	--- license: cc-by-4.0 ---
Tuana/presidents	--- dataset_info: features: - name: id dtype: string - name: content dtype: string - name: content_type dtype: string - name: meta struct: - name: url dtype: string - name: _split_id dtype: int64 - name: id_hash_keys sequence: string - name: score dtype: 'null' - name: embedding dtype: 'null' splits: - name: train num_bytes: 9366886 num_examples: 5529 download_size: 4997888 dataset_size: 9366886 --- # Dataset Card for "presidents" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
hongboyang/LCSTS_instruction1	--- dataset_info: features: - name: INPUT dtype: string - name: TARGET dtype: string splits: - name: train num_bytes: 1128722053 num_examples: 2400591 download_size: 693529602 dataset_size: 1128722053 --- # Dataset Card for "LCSTS_instruction1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
autoevaluate/autoeval-staging-eval-Tristan__zero-shot-classification-large-test-Tristan__z-d81307-16956302	--- type: predictions tags: - autotrain - evaluation datasets: - Tristan/zero-shot-classification-large-test eval_info: task: text_zero_shot_classification model: Tristan/opt-66b-copy metrics: [] dataset_name: Tristan/zero-shot-classification-large-test dataset_config: Tristan--zero-shot-classification-large-test 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: Tristan/opt-66b-copy * Dataset: Tristan/zero-shot-classification-large-test * Config: Tristan--zero-shot-classification-large-test * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model.
furry-br/krystal	--- license: openrail ---
liyongsea/empty_function_jupyter	--- dataset_info: features: - name: path dtype: string - name: content_id dtype: string - name: detected_licenses sequence: string - name: license_type dtype: string - name: repo_name dtype: string - name: repo_url dtype: string - name: star_events_count dtype: int64 - name: fork_events_count dtype: int64 - name: gha_license_id dtype: string - name: gha_event_created_at dtype: timestamp[us] - name: gha_updated_at dtype: timestamp[us] - name: gha_language dtype: string - name: language dtype: string - name: is_generated dtype: bool - name: is_vendor dtype: bool - name: conversion_extension dtype: string - name: size dtype: int64 - name: script dtype: string - name: script_size dtype: int64 splits: - name: train num_bytes: 654648.6506 num_examples: 28 download_size: 292451 dataset_size: 654648.6506 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "empty_function_jupyter" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/lawine_sousounofrieren	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Lawine/ラヴィーネ (Sousou no Frieren) This is the dataset of Lawine/ラヴィーネ (Sousou no Frieren), containing 192 images and their tags. The core tags of this character are `long_hair, braid, blue_eyes, blunt_bangs, grey_hair, french_braid, brown_hair`, 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 \| 192 \| 124.24 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 1200 \| 192 \| 124.17 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 313 \| 191.07 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/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/lawine_sousounofrieren', 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 \| 13 \| ![](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, blue_capelet, blue_dress, long_sleeves, solo, holding_staff, closed_mouth, upper_body, blurry_background, frilled_capelet, outdoors \| \| 1 \| 14 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, holding_staff, long_sleeves, solo, blue_capelet, blue_dress, frilled_capelet, standing, outdoors, closed_mouth, white_thighhighs, cross-laced_footwear, cloudy_sky, very_long_hair, full_body, thigh_boots, tree \| \| 2 \| 9 \| ![](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, closed_mouth, expressionless, blue_capelet, solo, upper_body, blue_dress, outdoors, tree, looking_at_viewer, forest, frills \| \| 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, blue_capelet, blue_dress, frilled_capelet, long_sleeves, outdoors, solo, looking_at_viewer, open_mouth, closed_mouth, cloudy_sky \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, blue_capelet, closed_mouth, solo, blue_dress, frilled_dress, lace-up_boots, long_sleeves, standing, white_footwear, white_thighhighs, full_body, thigh_boots, frilled_capelet, outdoors, blurry, forest, looking_at_viewer \| \| 5 \| 8 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| 1girl, blue_dress, closed_mouth, long_sleeves, solo, low-tied_long_hair, very_long_hair, expressionless, frilled_capelet, frilled_dress, from_side, profile \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| blue_capelet, blue_dress, frilled_dress, long_sleeves, sitting_on_person, very_long_hair, 2girls, checkered_floor, frilled_capelet, solo_focus, white_thighhighs, green_shorts, thigh_boots, closed_mouth, low-tied_long_hair \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| blue_capelet \| blue_dress \| long_sleeves \| solo \| holding_staff \| closed_mouth \| upper_body \| blurry_background \| frilled_capelet \| outdoors \| standing \| white_thighhighs \| cross-laced_footwear \| cloudy_sky \| very_long_hair \| full_body \| thigh_boots \| tree \| expressionless \| looking_at_viewer \| forest \| frills \| open_mouth \| frilled_dress \| lace-up_boots \| white_footwear \| blurry \| low-tied_long_hair \| from_side \| profile \| sitting_on_person \| 2girls \| checkered_floor \| solo_focus \| green_shorts \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:---------------\|:-------------\|:---------------\|:-------\|:----------------\|:---------------\|:-------------\|:--------------------\|:------------------\|:-----------\|:-----------\|:-------------------\|:-----------------------\|:-------------\|:-----------------\|:------------\|:--------------\|:-------\|:-----------------\|:--------------------\|:---------\|:---------\|:-------------\|:----------------\|:----------------\|:-----------------\|:---------\|:---------------------\|:------------\|:----------\|:--------------------\|:---------\|:------------------\|:-------------\|:---------------\| \| 0 \| 13 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 14 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 9 \| ![](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 \| 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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 7 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| X \| X \| X \| X \| \| X \| \| \| X \| X \| X \| X \| \| \| \| X \| X \| \| \| X \| X \| \| \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| 5 \| 8 \| ![](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 \| \| \| \| \| \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| \| X \| X \| X \| \| \| X \| \| \| X \| \| \| X \| \| \| X \| \| X \| \| \| \| \| \| \| X \| \| \| \| X \| \| \| X \| X \| X \| X \| X \|
mar-yam1497/HotPotQA_Mistral_dataset_Top3k	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 7691946 num_examples: 3000 download_size: 3547124 dataset_size: 7691946 configs: - config_name: default data_files: - split: train path: data/train-* ---
jxie/bbbp	--- dataset_info: features: - name: index dtype: int64 - name: text dtype: string - name: label dtype: int64 splits: - name: train_0 num_bytes: 112140 num_examples: 1631 - name: val_0 num_bytes: 18772 num_examples: 204 - name: test_0 num_bytes: 15004 num_examples: 204 - name: train_1 num_bytes: 112140 num_examples: 1631 - name: val_1 num_bytes: 18772 num_examples: 204 - name: test_1 num_bytes: 15004 num_examples: 204 - name: train_2 num_bytes: 112140 num_examples: 1631 - name: val_2 num_bytes: 18772 num_examples: 204 - name: test_2 num_bytes: 15004 num_examples: 204 download_size: 218838 dataset_size: 437748 --- # Dataset Card for "bbbp" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ	--- pretty_name: Evaluation run of TheBloke/Genz-70b-GPTQ dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TheBloke/Genz-70b-GPTQ](https://huggingface.co/TheBloke/Genz-70b-GPTQ) 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_TheBloke__Genz-70b-GPTQ\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-31T00:30:34.342002](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ/blob/main/results_2023-08-31T00%3A30%3A34.342002.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\": 0.7017249416277331,\n\ \ \"acc_stderr\": 0.030832772804323012,\n \"acc_norm\": 0.70569345061239,\n\ \ \"acc_norm_stderr\": 0.03080075128019408,\n \"mc1\": 0.4320685434516524,\n\ \ \"mc1_stderr\": 0.01734120239498826,\n \"mc2\": 0.6228267270427654,\n\ \ \"mc2_stderr\": 0.014836432877772263\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6638225255972696,\n \"acc_stderr\": 0.013804855026205763,\n\ \ \"acc_norm\": 0.7107508532423208,\n \"acc_norm_stderr\": 0.013250012579393443\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.689205337582155,\n\ \ \"acc_stderr\": 0.004618730353217047,\n \"acc_norm\": 0.8764190400318662,\n\ \ \"acc_norm_stderr\": 0.0032843028764223\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.8223684210526315,\n \"acc_stderr\": 0.03110318238312338,\n\ \ \"acc_norm\": 0.8223684210526315,\n \"acc_norm_stderr\": 0.03110318238312338\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.76,\n\ \ \"acc_stderr\": 0.04292346959909284,\n \"acc_norm\": 0.76,\n \ \ \"acc_norm_stderr\": 0.04292346959909284\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.720754716981132,\n \"acc_stderr\": 0.027611163402399715,\n\ \ \"acc_norm\": 0.720754716981132,\n \"acc_norm_stderr\": 0.027611163402399715\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.032166008088022675,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.032166008088022675\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956911,\n \ \ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956911\n \ \ },\n \"harness\|hendrycksTest-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\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6473988439306358,\n\ \ \"acc_stderr\": 0.036430371689585475,\n \"acc_norm\": 0.6473988439306358,\n\ \ \"acc_norm_stderr\": 0.036430371689585475\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.676595744680851,\n \"acc_stderr\": 0.030579442773610337,\n\ \ \"acc_norm\": 0.676595744680851,\n \"acc_norm_stderr\": 0.030579442773610337\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.45614035087719296,\n\ \ \"acc_stderr\": 0.04685473041907789,\n \"acc_norm\": 0.45614035087719296,\n\ \ \"acc_norm_stderr\": 0.04685473041907789\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.04013124195424386,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.04013124195424386\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4417989417989418,\n \"acc_stderr\": 0.02557625706125384,\n \"\ acc_norm\": 0.4417989417989418,\n \"acc_norm_stderr\": 0.02557625706125384\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677172,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677172\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.8290322580645161,\n\ \ \"acc_stderr\": 0.02141724293632159,\n \"acc_norm\": 0.8290322580645161,\n\ \ \"acc_norm_stderr\": 0.02141724293632159\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036846,\n \"acc_norm\"\ : 0.8,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8545454545454545,\n \"acc_stderr\": 0.027530196355066573,\n\ \ \"acc_norm\": 0.8545454545454545,\n \"acc_norm_stderr\": 0.027530196355066573\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8686868686868687,\n \"acc_stderr\": 0.024063156416822523,\n \"\ acc_norm\": 0.8686868686868687,\n \"acc_norm_stderr\": 0.024063156416822523\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240528,\n\ \ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240528\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.7051282051282052,\n \"acc_stderr\": 0.023119362758232294,\n\ \ \"acc_norm\": 0.7051282051282052,\n \"acc_norm_stderr\": 0.023119362758232294\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.028406533090608463,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.028406533090608463\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.773109243697479,\n \"acc_stderr\": 0.027205371538279472,\n \ \ \"acc_norm\": 0.773109243697479,\n \"acc_norm_stderr\": 0.027205371538279472\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.5099337748344371,\n \"acc_stderr\": 0.04081677107248437,\n \"\ acc_norm\": 0.5099337748344371,\n \"acc_norm_stderr\": 0.04081677107248437\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8917431192660551,\n \"acc_stderr\": 0.013321348447611769,\n \"\ acc_norm\": 0.8917431192660551,\n \"acc_norm_stderr\": 0.013321348447611769\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.6018518518518519,\n \"acc_stderr\": 0.033384734032074016,\n \"\ acc_norm\": 0.6018518518518519,\n \"acc_norm_stderr\": 0.033384734032074016\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073312,\n \"\ acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073312\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640262,\n \ \ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640262\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.8116591928251121,\n\ \ \"acc_stderr\": 0.026241132996407252,\n \"acc_norm\": 0.8116591928251121,\n\ \ \"acc_norm_stderr\": 0.026241132996407252\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8396946564885496,\n \"acc_stderr\": 0.03217829420744633,\n\ \ \"acc_norm\": 0.8396946564885496,\n \"acc_norm_stderr\": 0.03217829420744633\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.859504132231405,\n \"acc_stderr\": 0.03172233426002157,\n \"acc_norm\"\ : 0.859504132231405,\n \"acc_norm_stderr\": 0.03172233426002157\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8240740740740741,\n\ \ \"acc_stderr\": 0.036809181416738807,\n \"acc_norm\": 0.8240740740740741,\n\ \ \"acc_norm_stderr\": 0.036809181416738807\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8159509202453987,\n \"acc_stderr\": 0.030446777687971726,\n\ \ \"acc_norm\": 0.8159509202453987,\n \"acc_norm_stderr\": 0.030446777687971726\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04745789978762494,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04745789978762494\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9102564102564102,\n\ \ \"acc_stderr\": 0.018724301741941642,\n \"acc_norm\": 0.9102564102564102,\n\ \ \"acc_norm_stderr\": 0.018724301741941642\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\": 0.8722860791826309,\n\ \ \"acc_stderr\": 0.011935626313999876,\n \"acc_norm\": 0.8722860791826309,\n\ \ \"acc_norm_stderr\": 0.011935626313999876\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.8005780346820809,\n \"acc_stderr\": 0.021511900654252562,\n\ \ \"acc_norm\": 0.8005780346820809,\n \"acc_norm_stderr\": 0.021511900654252562\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.5754189944134078,\n\ \ \"acc_stderr\": 0.01653117099327888,\n \"acc_norm\": 0.5754189944134078,\n\ \ \"acc_norm_stderr\": 0.01653117099327888\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7745098039215687,\n \"acc_stderr\": 0.02392915551735129,\n\ \ \"acc_norm\": 0.7745098039215687,\n \"acc_norm_stderr\": 0.02392915551735129\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7717041800643086,\n\ \ \"acc_stderr\": 0.023839303311398205,\n \"acc_norm\": 0.7717041800643086,\n\ \ \"acc_norm_stderr\": 0.023839303311398205\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8487654320987654,\n \"acc_stderr\": 0.019935086092149897,\n\ \ \"acc_norm\": 0.8487654320987654,\n \"acc_norm_stderr\": 0.019935086092149897\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5638297872340425,\n \"acc_stderr\": 0.029583452036284076,\n \ \ \"acc_norm\": 0.5638297872340425,\n \"acc_norm_stderr\": 0.029583452036284076\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5534550195567145,\n\ \ \"acc_stderr\": 0.012697046024399654,\n \"acc_norm\": 0.5534550195567145,\n\ \ \"acc_norm_stderr\": 0.012697046024399654\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.026679252270103135,\n\ \ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.026679252270103135\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7630718954248366,\n \"acc_stderr\": 0.017201662169789772,\n \ \ \"acc_norm\": 0.7630718954248366,\n \"acc_norm_stderr\": 0.017201662169789772\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7363636363636363,\n\ \ \"acc_stderr\": 0.04220224692971987,\n \"acc_norm\": 0.7363636363636363,\n\ \ \"acc_norm_stderr\": 0.04220224692971987\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.02560737598657916,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.02560737598657916\n },\n\ \ \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8606965174129353,\n\ \ \"acc_stderr\": 0.024484487162913973,\n \"acc_norm\": 0.8606965174129353,\n\ \ \"acc_norm_stderr\": 0.024484487162913973\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5180722891566265,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.5180722891566265,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.025172984350155754,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.025172984350155754\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4320685434516524,\n\ \ \"mc1_stderr\": 0.01734120239498826,\n \"mc2\": 0.6228267270427654,\n\ \ \"mc2_stderr\": 0.014836432877772263\n }\n}\n```" repo_url: https://huggingface.co/TheBloke/Genz-70b-GPTQ 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_31T00_30_34.342002 path: - '/details_harness\|arc:challenge\|25_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hellaswag\|10_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-31T00:30:34.342002.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_31T00_30_34.342002 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-31T00:30:34.342002.parquet' - config_name: results data_files: - split: 2023_08_31T00_30_34.342002 path: - results_2023-08-31T00:30:34.342002.parquet - split: latest path: - results_2023-08-31T00:30:34.342002.parquet --- # Dataset Card for Evaluation run of TheBloke/Genz-70b-GPTQ ## Dataset Description - Homepage: - Repository: https://huggingface.co/TheBloke/Genz-70b-GPTQ - 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 [TheBloke/Genz-70b-GPTQ](https://huggingface.co/TheBloke/Genz-70b-GPTQ) 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_TheBloke__Genz-70b-GPTQ", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-31T00:30:34.342002](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ/blob/main/results_2023-08-31T00%3A30%3A34.342002.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": 0.7017249416277331, "acc_stderr": 0.030832772804323012, "acc_norm": 0.70569345061239, "acc_norm_stderr": 0.03080075128019408, "mc1": 0.4320685434516524, "mc1_stderr": 0.01734120239498826, "mc2": 0.6228267270427654, "mc2_stderr": 0.014836432877772263 }, "harness\|arc:challenge\|25": { "acc": 0.6638225255972696, "acc_stderr": 0.013804855026205763, "acc_norm": 0.7107508532423208, "acc_norm_stderr": 0.013250012579393443 }, "harness\|hellaswag\|10": { "acc": 0.689205337582155, "acc_stderr": 0.004618730353217047, "acc_norm": 0.8764190400318662, "acc_norm_stderr": 0.0032843028764223 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.8223684210526315, "acc_stderr": 0.03110318238312338, "acc_norm": 0.8223684210526315, "acc_norm_stderr": 0.03110318238312338 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.76, "acc_stderr": 0.04292346959909284, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909284 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.720754716981132, "acc_stderr": 0.027611163402399715, "acc_norm": 0.720754716981132, "acc_norm_stderr": 0.027611163402399715 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8194444444444444, "acc_stderr": 0.032166008088022675, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.032166008088022675 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "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": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6473988439306358, "acc_stderr": 0.036430371689585475, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.036430371689585475 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.676595744680851, "acc_stderr": 0.030579442773610337, "acc_norm": 0.676595744680851, "acc_norm_stderr": 0.030579442773610337 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.45614035087719296, "acc_stderr": 0.04685473041907789, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.04685473041907789 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.6344827586206897, "acc_stderr": 0.04013124195424386, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.04013124195424386 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4417989417989418, "acc_stderr": 0.02557625706125384, "acc_norm": 0.4417989417989418, "acc_norm_stderr": 0.02557625706125384 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677172, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677172 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8290322580645161, "acc_stderr": 0.02141724293632159, "acc_norm": 0.8290322580645161, "acc_norm_stderr": 0.02141724293632159 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066573, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066573 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8686868686868687, "acc_stderr": 0.024063156416822523, "acc_norm": 0.8686868686868687, "acc_norm_stderr": 0.024063156416822523 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240528, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240528 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.7051282051282052, "acc_stderr": 0.023119362758232294, "acc_norm": 0.7051282051282052, "acc_norm_stderr": 0.023119362758232294 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.31851851851851853, "acc_stderr": 0.028406533090608463, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.028406533090608463 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.773109243697479, "acc_stderr": 0.027205371538279472, "acc_norm": 0.773109243697479, "acc_norm_stderr": 0.027205371538279472 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.5099337748344371, "acc_stderr": 0.04081677107248437, "acc_norm": 0.5099337748344371, "acc_norm_stderr": 0.04081677107248437 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8917431192660551, "acc_stderr": 0.013321348447611769, "acc_norm": 0.8917431192660551, "acc_norm_stderr": 0.013321348447611769 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.6018518518518519, "acc_stderr": 0.033384734032074016, "acc_norm": 0.6018518518518519, "acc_norm_stderr": 0.033384734032074016 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9313725490196079, "acc_stderr": 0.017744453647073312, "acc_norm": 0.9313725490196079, "acc_norm_stderr": 0.017744453647073312 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.9029535864978903, "acc_stderr": 0.019269323025640262, "acc_norm": 0.9029535864978903, "acc_norm_stderr": 0.019269323025640262 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.8116591928251121, "acc_stderr": 0.026241132996407252, "acc_norm": 0.8116591928251121, "acc_norm_stderr": 0.026241132996407252 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8396946564885496, "acc_stderr": 0.03217829420744633, "acc_norm": 0.8396946564885496, "acc_norm_stderr": 0.03217829420744633 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.859504132231405, "acc_stderr": 0.03172233426002157, "acc_norm": 0.859504132231405, "acc_norm_stderr": 0.03172233426002157 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8240740740740741, "acc_stderr": 0.036809181416738807, "acc_norm": 0.8240740740740741, "acc_norm_stderr": 0.036809181416738807 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.8159509202453987, "acc_stderr": 0.030446777687971726, "acc_norm": 0.8159509202453987, "acc_norm_stderr": 0.030446777687971726 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.5, "acc_stderr": 0.04745789978762494, "acc_norm": 0.5, "acc_norm_stderr": 0.04745789978762494 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8446601941747572, "acc_stderr": 0.03586594738573974, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.03586594738573974 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9102564102564102, "acc_stderr": 0.018724301741941642, "acc_norm": 0.9102564102564102, "acc_norm_stderr": 0.018724301741941642 }, "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": 0.8722860791826309, "acc_stderr": 0.011935626313999876, "acc_norm": 0.8722860791826309, "acc_norm_stderr": 0.011935626313999876 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.8005780346820809, "acc_stderr": 0.021511900654252562, "acc_norm": 0.8005780346820809, "acc_norm_stderr": 0.021511900654252562 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.5754189944134078, "acc_stderr": 0.01653117099327888, "acc_norm": 0.5754189944134078, "acc_norm_stderr": 0.01653117099327888 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7745098039215687, "acc_stderr": 0.02392915551735129, "acc_norm": 0.7745098039215687, "acc_norm_stderr": 0.02392915551735129 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7717041800643086, "acc_stderr": 0.023839303311398205, "acc_norm": 0.7717041800643086, "acc_norm_stderr": 0.023839303311398205 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8487654320987654, "acc_stderr": 0.019935086092149897, "acc_norm": 0.8487654320987654, "acc_norm_stderr": 0.019935086092149897 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5638297872340425, "acc_stderr": 0.029583452036284076, "acc_norm": 0.5638297872340425, "acc_norm_stderr": 0.029583452036284076 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.5534550195567145, "acc_stderr": 0.012697046024399654, "acc_norm": 0.5534550195567145, "acc_norm_stderr": 0.012697046024399654 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7389705882352942, "acc_stderr": 0.026679252270103135, "acc_norm": 0.7389705882352942, "acc_norm_stderr": 0.026679252270103135 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.7630718954248366, "acc_stderr": 0.017201662169789772, "acc_norm": 0.7630718954248366, "acc_norm_stderr": 0.017201662169789772 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7363636363636363, "acc_stderr": 0.04220224692971987, "acc_norm": 0.7363636363636363, "acc_norm_stderr": 0.04220224692971987 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.8, "acc_stderr": 0.02560737598657916, "acc_norm": 0.8, "acc_norm_stderr": 0.02560737598657916 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8606965174129353, "acc_stderr": 0.024484487162913973, "acc_norm": 0.8606965174129353, "acc_norm_stderr": 0.024484487162913973 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5180722891566265, "acc_stderr": 0.038899512528272166, "acc_norm": 0.5180722891566265, "acc_norm_stderr": 0.038899512528272166 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8771929824561403, "acc_stderr": 0.025172984350155754, "acc_norm": 0.8771929824561403, "acc_norm_stderr": 0.025172984350155754 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4320685434516524, "mc1_stderr": 0.01734120239498826, "mc2": 0.6228267270427654, "mc2_stderr": 0.014836432877772263 } } ``` ### 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]
joey234/mmlu-college_biology-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: 9147.1875 num_examples: 27 download_size: 7857 dataset_size: 9147.1875 --- # Dataset Card for "mmlu-college_biology-original-neg" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AdapterOcean/med_alpaca_standardized_cluster_59_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: 12541572 num_examples: 23244 download_size: 6485582 dataset_size: 12541572 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_59_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_jeiku__NarrativeNexus_7B	--- pretty_name: Evaluation run of jeiku/NarrativeNexus_7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [jeiku/NarrativeNexus_7B](https://huggingface.co/jeiku/NarrativeNexus_7B) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_jeiku__NarrativeNexus_7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-16T01:30:29.349287](https://huggingface.co/datasets/open-llm-leaderboard/details_jeiku__NarrativeNexus_7B/blob/main/results_2024-02-16T01-30-29.349287.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\": 0.6331502373053775,\n\ \ \"acc_stderr\": 0.032649477056743835,\n \"acc_norm\": 0.6360612367088411,\n\ \ \"acc_norm_stderr\": 0.03330403787596569,\n \"mc1\": 0.46878824969400246,\n\ \ \"mc1_stderr\": 0.017469364874577537,\n \"mc2\": 0.6394506791157332,\n\ \ \"mc2_stderr\": 0.015272071804569947\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6279863481228669,\n \"acc_stderr\": 0.01412459788184446,\n\ \ \"acc_norm\": 0.6612627986348123,\n \"acc_norm_stderr\": 0.01383056892797433\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6773551085441147,\n\ \ \"acc_stderr\": 0.004665327309399188,\n \"acc_norm\": 0.8573989245170285,\n\ \ \"acc_norm_stderr\": 0.003489509493001621\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6296296296296297,\n\ \ \"acc_stderr\": 0.041716541613545426,\n \"acc_norm\": 0.6296296296296297,\n\ \ \"acc_norm_stderr\": 0.041716541613545426\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\ \ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.54,\n\ \ \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n \ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322663,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322663\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\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.55,\n \ \ \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6358381502890174,\n\ \ \"acc_stderr\": 0.03669072477416907,\n \"acc_norm\": 0.6358381502890174,\n\ \ \"acc_norm_stderr\": 0.03669072477416907\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\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\": 0.5787234042553191,\n \"acc_stderr\": 0.03227834510146268,\n\ \ \"acc_norm\": 0.5787234042553191,\n \"acc_norm_stderr\": 0.03227834510146268\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.47368421052631576,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.47368421052631576,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.04113914981189261,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.04113914981189261\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3888888888888889,\n \"acc_stderr\": 0.025107425481137285,\n \"\ acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.025107425481137285\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677171,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677171\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.7645161290322581,\n \"acc_stderr\": 0.02413763242933771,\n \"\ acc_norm\": 0.7645161290322581,\n \"acc_norm_stderr\": 0.02413763242933771\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n \"\ acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.033175059300091805,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.033175059300091805\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\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015184,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015184\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\": 0.3888888888888889,\n \"acc_stderr\": 0.029723278961476664,\n \ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.029723278961476664\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6848739495798319,\n \"acc_stderr\": 0.030176808288974337,\n\ \ \"acc_norm\": 0.6848739495798319,\n \"acc_norm_stderr\": 0.030176808288974337\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8036697247706422,\n \"acc_stderr\": 0.01703071933915434,\n \"\ acc_norm\": 0.8036697247706422,\n \"acc_norm_stderr\": 0.01703071933915434\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.49074074074074076,\n \"acc_stderr\": 0.03409386946992699,\n \"\ acc_norm\": 0.49074074074074076,\n \"acc_norm_stderr\": 0.03409386946992699\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.028626547912437406,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.028626547912437406\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7552742616033755,\n \"acc_stderr\": 0.027985699387036423,\n \ \ \"acc_norm\": 0.7552742616033755,\n \"acc_norm_stderr\": 0.027985699387036423\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7099236641221374,\n \"acc_stderr\": 0.03980066246467765,\n\ \ \"acc_norm\": 0.7099236641221374,\n \"acc_norm_stderr\": 0.03980066246467765\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7851239669421488,\n \"acc_stderr\": 0.03749492448709695,\n \"\ acc_norm\": 0.7851239669421488,\n \"acc_norm_stderr\": 0.03749492448709695\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\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\": 0.4732142857142857,\n\ \ \"acc_stderr\": 0.047389751192741546,\n \"acc_norm\": 0.4732142857142857,\n\ \ \"acc_norm_stderr\": 0.047389751192741546\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.04354631077260595,\n\ \ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.04354631077260595\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406964,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406964\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8084291187739464,\n\ \ \"acc_stderr\": 0.014072859310451949,\n \"acc_norm\": 0.8084291187739464,\n\ \ \"acc_norm_stderr\": 0.014072859310451949\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.024946792225272314,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.024946792225272314\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4312849162011173,\n\ \ \"acc_stderr\": 0.016563829399047707,\n \"acc_norm\": 0.4312849162011173,\n\ \ \"acc_norm_stderr\": 0.016563829399047707\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7026143790849673,\n \"acc_stderr\": 0.02617390850671858,\n\ \ \"acc_norm\": 0.7026143790849673,\n \"acc_norm_stderr\": 0.02617390850671858\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6945337620578779,\n\ \ \"acc_stderr\": 0.026160584450140453,\n \"acc_norm\": 0.6945337620578779,\n\ \ \"acc_norm_stderr\": 0.026160584450140453\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6882716049382716,\n \"acc_stderr\": 0.025773111169630457,\n\ \ \"acc_norm\": 0.6882716049382716,\n \"acc_norm_stderr\": 0.025773111169630457\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4397163120567376,\n \"acc_stderr\": 0.02960991207559411,\n \ \ \"acc_norm\": 0.4397163120567376,\n \"acc_norm_stderr\": 0.02960991207559411\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4576271186440678,\n\ \ \"acc_stderr\": 0.012724296550980188,\n \"acc_norm\": 0.4576271186440678,\n\ \ \"acc_norm_stderr\": 0.012724296550980188\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\": 0.6160130718954249,\n \"acc_stderr\": 0.019675808135281508,\n \ \ \"acc_norm\": 0.6160130718954249,\n \"acc_norm_stderr\": 0.019675808135281508\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6909090909090909,\n\ \ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\ \ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.029504896454595957,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.029504896454595957\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8507462686567164,\n\ \ \"acc_stderr\": 0.02519692987482707,\n \"acc_norm\": 0.8507462686567164,\n\ \ \"acc_norm_stderr\": 0.02519692987482707\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4879518072289157,\n\ \ \"acc_stderr\": 0.0389136449583582,\n \"acc_norm\": 0.4879518072289157,\n\ \ \"acc_norm_stderr\": 0.0389136449583582\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8421052631578947,\n \"acc_stderr\": 0.027966785859160882,\n\ \ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.027966785859160882\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.46878824969400246,\n\ \ \"mc1_stderr\": 0.017469364874577537,\n \"mc2\": 0.6394506791157332,\n\ \ \"mc2_stderr\": 0.015272071804569947\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7900552486187845,\n \"acc_stderr\": 0.01144628062926263\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.5178165276724791,\n \ \ \"acc_stderr\": 0.013763738379867933\n }\n}\n```" repo_url: https://huggingface.co/jeiku/NarrativeNexus_7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|arc:challenge\|25_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-16T01-30-29.349287.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|gsm8k\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hellaswag\|10_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T01-30-29.349287.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T01-30-29.349287.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '/details_harness\|winogrande\|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-16T01-30-29.349287.parquet' - config_name: results data_files: - split: 2024_02_16T01_30_29.349287 path: - results_2024-02-16T01-30-29.349287.parquet - split: latest path: - results_2024-02-16T01-30-29.349287.parquet --- # Dataset Card for Evaluation run of jeiku/NarrativeNexus_7B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [jeiku/NarrativeNexus_7B](https://huggingface.co/jeiku/NarrativeNexus_7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_jeiku__NarrativeNexus_7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-16T01:30:29.349287](https://huggingface.co/datasets/open-llm-leaderboard/details_jeiku__NarrativeNexus_7B/blob/main/results_2024-02-16T01-30-29.349287.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": 0.6331502373053775, "acc_stderr": 0.032649477056743835, "acc_norm": 0.6360612367088411, "acc_norm_stderr": 0.03330403787596569, "mc1": 0.46878824969400246, "mc1_stderr": 0.017469364874577537, "mc2": 0.6394506791157332, "mc2_stderr": 0.015272071804569947 }, "harness\|arc:challenge\|25": { "acc": 0.6279863481228669, "acc_stderr": 0.01412459788184446, "acc_norm": 0.6612627986348123, "acc_norm_stderr": 0.01383056892797433 }, "harness\|hellaswag\|10": { "acc": 0.6773551085441147, "acc_stderr": 0.004665327309399188, "acc_norm": 0.8573989245170285, "acc_norm_stderr": 0.003489509493001621 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6296296296296297, "acc_stderr": 0.041716541613545426, "acc_norm": 0.6296296296296297, "acc_norm_stderr": 0.041716541613545426 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6776315789473685, "acc_stderr": 0.03803510248351585, "acc_norm": 0.6776315789473685, "acc_norm_stderr": 0.03803510248351585 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6943396226415094, "acc_stderr": 0.028353298073322663, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322663 }, "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": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6358381502890174, "acc_stderr": 0.03669072477416907, "acc_norm": 0.6358381502890174, "acc_norm_stderr": 0.03669072477416907 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "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": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.47368421052631576, "acc_stderr": 0.046970851366478626, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.046970851366478626 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5793103448275863, "acc_stderr": 0.04113914981189261, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.04113914981189261 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.025107425481137285, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.025107425481137285 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677171, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677171 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7645161290322581, "acc_stderr": 0.02413763242933771, "acc_norm": 0.7645161290322581, "acc_norm_stderr": 0.02413763242933771 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7636363636363637, "acc_stderr": 0.033175059300091805, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.033175059300091805 }, "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": 0.8601036269430051, "acc_stderr": 0.025033870583015184, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015184 }, "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": 0.3888888888888889, "acc_stderr": 0.029723278961476664, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.029723278961476664 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6848739495798319, "acc_stderr": 0.030176808288974337, "acc_norm": 0.6848739495798319, "acc_norm_stderr": 0.030176808288974337 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8036697247706422, "acc_stderr": 0.01703071933915434, "acc_norm": 0.8036697247706422, "acc_norm_stderr": 0.01703071933915434 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.49074074074074076, "acc_stderr": 0.03409386946992699, "acc_norm": 0.49074074074074076, "acc_norm_stderr": 0.03409386946992699 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7892156862745098, "acc_stderr": 0.028626547912437406, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.028626547912437406 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7552742616033755, "acc_stderr": 0.027985699387036423, "acc_norm": 0.7552742616033755, "acc_norm_stderr": 0.027985699387036423 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7099236641221374, "acc_stderr": 0.03980066246467765, "acc_norm": 0.7099236641221374, "acc_norm_stderr": 0.03980066246467765 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7851239669421488, "acc_stderr": 0.03749492448709695, "acc_norm": 0.7851239669421488, "acc_norm_stderr": 0.03749492448709695 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "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": 0.4732142857142857, "acc_stderr": 0.047389751192741546, "acc_norm": 0.4732142857142857, "acc_norm_stderr": 0.047389751192741546 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7378640776699029, "acc_stderr": 0.04354631077260595, "acc_norm": 0.7378640776699029, "acc_norm_stderr": 0.04354631077260595 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406964, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406964 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8084291187739464, "acc_stderr": 0.014072859310451949, "acc_norm": 0.8084291187739464, "acc_norm_stderr": 0.014072859310451949 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6878612716763006, "acc_stderr": 0.024946792225272314, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.024946792225272314 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4312849162011173, "acc_stderr": 0.016563829399047707, "acc_norm": 0.4312849162011173, "acc_norm_stderr": 0.016563829399047707 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7026143790849673, "acc_stderr": 0.02617390850671858, "acc_norm": 0.7026143790849673, "acc_norm_stderr": 0.02617390850671858 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6945337620578779, "acc_stderr": 0.026160584450140453, "acc_norm": 0.6945337620578779, "acc_norm_stderr": 0.026160584450140453 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6882716049382716, "acc_stderr": 0.025773111169630457, "acc_norm": 0.6882716049382716, "acc_norm_stderr": 0.025773111169630457 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4397163120567376, "acc_stderr": 0.02960991207559411, "acc_norm": 0.4397163120567376, "acc_norm_stderr": 0.02960991207559411 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4576271186440678, "acc_stderr": 0.012724296550980188, "acc_norm": 0.4576271186440678, "acc_norm_stderr": 0.012724296550980188 }, "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": 0.6160130718954249, "acc_stderr": 0.019675808135281508, "acc_norm": 0.6160130718954249, "acc_norm_stderr": 0.019675808135281508 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6909090909090909, "acc_stderr": 0.044262946482000985, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.044262946482000985 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6938775510204082, "acc_stderr": 0.029504896454595957, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.029504896454595957 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8507462686567164, "acc_stderr": 0.02519692987482707, "acc_norm": 0.8507462686567164, "acc_norm_stderr": 0.02519692987482707 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.87, "acc_stderr": 0.03379976689896309, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896309 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4879518072289157, "acc_stderr": 0.0389136449583582, "acc_norm": 0.4879518072289157, "acc_norm_stderr": 0.0389136449583582 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8421052631578947, "acc_stderr": 0.027966785859160882, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.027966785859160882 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.46878824969400246, "mc1_stderr": 0.017469364874577537, "mc2": 0.6394506791157332, "mc2_stderr": 0.015272071804569947 }, "harness\|winogrande\|5": { "acc": 0.7900552486187845, "acc_stderr": 0.01144628062926263 }, "harness\|gsm8k\|5": { "acc": 0.5178165276724791, "acc_stderr": 0.013763738379867933 } } ``` ## 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 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CyberHarem/spitfire_girlsfrontline	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of spitfire/Spitfire/喷火 (Girls' Frontline) This is the dataset of spitfire/Spitfire/喷火 (Girls' Frontline), containing 15 images and their tags. The core tags of this character are `long_hair, hat, green_eyes, top_hat, grey_hair, breasts, bangs, 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 \| 15 \| 20.18 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 15 \| 11.99 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 34 \| 22.67 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 15 \| 18.00 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 34 \| 30.82 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/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/spitfire_girlsfrontline', 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 \| 12 \| ![](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, looking_at_viewer, solo, black_gloves, dress, belt, handgun, necktie, bare_shoulders, boots, brown_hair, holding_gun, official_alternate_costume, pantyhose, small_breasts, thighhighs \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| looking_at_viewer \| solo \| black_gloves \| dress \| belt \| handgun \| necktie \| bare_shoulders \| boots \| brown_hair \| holding_gun \| official_alternate_costume \| pantyhose \| small_breasts \| thighhighs \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------------------\|:-------\|:---------------\|:--------\|:-------\|:----------\|:----------\|:-----------------\|:--------\|:-------------\|:--------------\|:-----------------------------\|:------------\|:----------------\|:-------------\| \| 0 \| 12 \| ![](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 \|
CyberHarem/moriyama_shiemi	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Moriyama Shiemi (青の祓魔師) This is the dataset of Moriyama Shiemi (青の祓魔師), containing 258 images and their tags. The core tags of this character are `blonde_hair, short_hair, green_eyes, hair_ornament, hair_flower, hairband`, 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 \| 258 \| 198.76 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 258 \| 160.38 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 434 \| 266.06 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 258 \| 190.14 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 434 \| 309.67 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/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/moriyama_shiemi', 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 \| 13 \| ![](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, school_uniform, skirt, solo, smile, flower, open_mouth, blush, bow, white_thighhighs, zettai_ryouiki \| \| 1 \| 5 \| ![](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, bow, open_mouth, smile, solo, school_uniform, hair_ribbon, ahoge, aqua_eyes, necktie \| \| 2 \| 18 \| ![](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, flower, kimono, smile, solo, open_mouth, blush \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| school_uniform \| skirt \| solo \| smile \| flower \| open_mouth \| blush \| bow \| white_thighhighs \| zettai_ryouiki \| hair_ribbon \| ahoge \| aqua_eyes \| necktie \| kimono \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-----------------\|:--------\|:-------\|:--------\|:---------\|:-------------\|:--------\|:------\|:-------------------\|:-----------------\|:--------------\|:--------\|:------------\|:----------\|:---------\| \| 0 \| 13 \| ![](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 \| \| \| \| \| \| \| 1 \| 5 \| ![](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 \| \| \| 2 \| 18 \| ![](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 \|
irds/neumarco_fa_dev_judged	--- pretty_name: '`neumarco/fa/dev/judged`' viewer: false source_datasets: ['irds/neumarco_fa', 'irds/neumarco_fa_dev'] task_categories: - text-retrieval --- # Dataset Card for `neumarco/fa/dev/judged` The `neumarco/fa/dev/judged` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/neumarco#neumarco/fa/dev/judged). # Data This dataset provides: - `queries` (i.e., topics); count=55,578 - For `docs`, use [`irds/neumarco_fa`](https://huggingface.co/datasets/irds/neumarco_fa) - For `qrels`, use [`irds/neumarco_fa_dev`](https://huggingface.co/datasets/irds/neumarco_fa_dev) ## Usage ```python from datasets import load_dataset queries = load_dataset('irds/neumarco_fa_dev_judged', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} ``` 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.
jp1924/JeollaSpeech	--- dataset_info: features: - name: id dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: standard_form dtype: string - name: dialect_form dtype: string - name: start dtype: float32 - name: end dtype: float32 - name: note dtype: string - name: eojeolList list: - name: id dtype: int8 - name: eojeol dtype: string - name: standard dtype: string - name: isDialect dtype: bool - name: speaker struct: - name: id dtype: string - name: name dtype: string - name: age dtype: string - name: occupation dtype: string - name: sex dtype: string - name: birthplace dtype: string - name: principal_residence dtype: string - name: current_residence dtype: string - name: education dtype: string - name: metadata struct: - name: title dtype: string - name: creator dtype: string - name: distributor dtype: string - name: year dtype: string - name: category dtype: string - name: annotation_level list: string - name: sampling dtype: string - name: author dtype: string - name: publisher dtype: string - name: date dtype: string - name: topic dtype: string splits: - name: train num_bytes: 520213137698.024 num_examples: 1988867 - name: validation num_bytes: 61448267920.464 num_examples: 275137 download_size: 557887316021 dataset_size: 581661405618.488 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
yzhuang/autotree_pmlb_10000_Hill_Valley_without_noise_sgosdt_l256_dim10_d3_sd0	--- dataset_info: features: - name: id dtype: int64 - name: input_x sequence: sequence: float32 - name: input_y sequence: sequence: float32 - name: input_y_clean sequence: sequence: float32 - name: rtg sequence: float64 - name: status sequence: sequence: float32 - name: split_threshold sequence: sequence: float32 - name: split_dimension sequence: int64 splits: - name: train num_bytes: 236440000 num_examples: 10000 - name: validation num_bytes: 236440000 num_examples: 10000 download_size: 179483399 dataset_size: 472880000 --- # Dataset Card for "autotree_pmlb_10000_Hill_Valley_without_noise_sgosdt_l256_dim10_d3_sd0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/yoroizuka_mizore_soundeuphonium	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Yoroizuka Mizore/鎧塚みぞれ/铠冢霙/のぞみぞ (Sound! Euphonium) This is the dataset of Yoroizuka Mizore/鎧塚みぞれ/铠冢霙/のぞみぞ (Sound! Euphonium), containing 228 images and their tags. The core tags of this character are `long_hair, blue_hair, red_eyes, black_hair`, 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 \| 228 \| 159.21 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 1200 \| 228 \| 159.12 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 400 \| 267.41 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/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/yoroizuka_mizore_soundeuphonium', 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 \| 6 \| ![](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, blue_sailor_collar, blurry_background, blush, kitauji_high_school_uniform, outdoors, serafuku, solo, white_shirt, blue_neckerchief, blue_skirt, closed_mouth, pleated_skirt, school_bag, short_sleeves, standing, tree, black_bag, looking_to_the_side \| \| 1 \| 15 \| ![](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) \| blush, kitauji_high_school_uniform, serafuku, 1girl, blue_sailor_collar, white_shirt, solo, indoors, parted_lips, open_mouth, blurry_background, closed_mouth, window \| \| 2 \| 12 \| ![](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) \| blue_sailor_collar, blush, kitauji_high_school_uniform, serafuku, white_shirt, 2girls, neckerchief, closed_mouth, looking_at_viewer, solo_focus, blurry \| \| 3 \| 11 \| ![](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) \| blue_neckerchief, blue_sailor_collar, kitauji_high_school_uniform, serafuku, short_sleeves, white_shirt, 2girls, blue_skirt, blush, indoors, pleated_skirt, brown_hair, chair, closed_mouth, sitting, solo_focus, classroom, instrument \| \| 4 \| 5 \| ![](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, blue_neckerchief, blue_sailor_collar, blush, chair, classroom, from_side, indoors, kitauji_high_school_uniform, serafuku, solo, white_shirt, window, closed_mouth, short_sleeves, sitting, blurry, flute, holding_instrument \| \| 5 \| 30 \| ![](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) \| kitauji_high_school_uniform, serafuku, 1girl, solo, white_sailor_collar, holding_instrument, brown_shirt, long_sleeves, playing_instrument, closed_mouth, blurry_background, blue_neckerchief \| \| 6 \| 5 \| ![](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, brown_shirt, brown_skirt, holding_instrument, kitauji_high_school_uniform, long_sleeves, pleated_skirt, serafuku, standing, white_sailor_collar, solo, blue_neckerchief, blush, from_side \| \| 7 \| 10 \| ![](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) \| blush, brown_shirt, closed_mouth, kitauji_high_school_uniform, serafuku, solo_focus, white_sailor_collar, blue_neckerchief, 2girls, long_sleeves, brown_skirt, blurry_background, pleated_skirt, sitting, socks \| \| 8 \| 12 \| ![](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) \| blush, school_uniform, 1girl, collared_shirt, green_jacket, red_bowtie, solo, white_shirt, closed_mouth, blazer, long_sleeves, looking_at_viewer \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| blue_sailor_collar \| blurry_background \| blush \| kitauji_high_school_uniform \| outdoors \| serafuku \| solo \| white_shirt \| blue_neckerchief \| blue_skirt \| closed_mouth \| pleated_skirt \| school_bag \| short_sleeves \| standing \| tree \| black_bag \| looking_to_the_side \| indoors \| parted_lips \| open_mouth \| window \| 2girls \| neckerchief \| looking_at_viewer \| solo_focus \| blurry \| brown_hair \| chair \| sitting \| classroom \| instrument \| from_side \| flute \| holding_instrument \| white_sailor_collar \| brown_shirt \| long_sleeves \| playing_instrument \| brown_skirt \| socks \| school_uniform \| collared_shirt \| green_jacket \| red_bowtie \| blazer \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:---------------------\|:--------------------\|:--------\|:------------------------------\|:-----------\|:-----------\|:-------\|:--------------\|:-------------------\|:-------------\|:---------------\|:----------------\|:-------------\|:----------------\|:-----------\|:-------\|:------------\|:----------------------\|:----------\|:--------------\|:-------------\|:---------\|:---------\|:--------------\|:--------------------\|:-------------\|:---------\|:-------------\|:--------\|:----------\|:------------\|:-------------\|:------------\|:--------\|:---------------------\|:----------------------\|:--------------\|:---------------\|:---------------------\|:--------------\|:--------\|:-----------------\|:-----------------\|:---------------\|:-------------\|:---------\| \| 0 \| 6 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 15 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 12 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 11 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| \| X \| \| X \| X \| \| X \| \| X \| X \| X \| X \| X \| \| X \| \| \| \| \| X \| \| \| \| X \| \| \| X \| \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 5 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 30 \| ![](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 \| \| \| \| \| \| \| \| \| 6 \| 5 \| ![](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 \| \| \| \| \| \| \| \| 7 \| 10 \| ![](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 \| \| \| \| \| \| \| 8 \| 12 \| ![](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 \|
chrisjay/crowd-speech-africa	--- extra_gated_prompt: "You agree to not attempt to determine the identity of individuals in this dataset" extra_gated_fields: Name: text Affiliation: text Email: text I agree to not attempt to determine the identity of speakers in this dataset: checkbox ---
ai-aerospace/ams_data_train_mistral_v0.1_100	--- license: apache-2.0 base-model: TheBloke/Llama-2-7B-Chat-GGUF --- Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF Format representative of mistral's instruct llms: * https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 * Example dataset: https://huggingface.co/datasets/centroIA/MistralInstructScenarios `<s>[INST] {prompt} [/INST]`
NicholasSynovic/Free-AutoTrain-VEAA	--- license: agpl-3.0 task_categories: - text-classification language: - en pretty_name: Victorian Era Authorship Attribution Data Set (For Free AutoTrain Account) size_categories: - 1K<n<10K source_datasets: - NicholasSynovic/Victorian-Era-Authorship-Attribution --- # Free AutoTrain VEAA > Victorian Era Authorship Attribution Data Set (For Free AutoTrain Account) ## About See the [original HF-hosted dataset](https://huggingface.co/datasets/NicholasSynovic/Victorian-Era-Authorship-Attribution) for more information. The code to generate this dataset came from this [GitHub Repo](https://github.com/NicholasSynovic/nlp-victorianAuthor).
gmongaras/BERT_Base_Cased_512_Dataset_Mapped	--- dataset_info: features: - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 52875464012.02522 num_examples: 136226984 download_size: 17583618282 dataset_size: 52875464012.02522 configs: - config_name: default data_files: - split: train path: data/train-* --- Dataset using the bert-cased tokenizer, cutoff sentences to 512 length (not sentence pairs), all sentence pairs extracted. Original datasets: https://huggingface.co/datasets/bookcorpus https://huggingface.co/datasets/wikipedia Variant: 20220301.en Mapped from: https://huggingface.co/datasets/gmongaras/BERT_Base_Cased_512_Dataset
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/245282ee	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 182 num_examples: 10 download_size: 1331 dataset_size: 182 --- # Dataset Card for "245282ee" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/linde_fireemblem	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of linde (Fire Emblem) This is the dataset of linde (Fire Emblem), containing 168 images and their tags. The core tags of this character are `brown_hair, long_hair, ponytail, brown_eyes, breasts, very_long_hair, large_breasts`, 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 \| 168 \| 187.80 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 168 \| 116.00 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 378 \| 232.24 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 168 \| 170.99 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 378 \| 310.53 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/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/linde_fireemblem', 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 \| 26 \| ![](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, solo, circlet, looking_at_viewer, cleavage, navel, smile, blush, hair_ornament, pink_bikini, open_mouth, simple_background \| \| 1 \| 5 \| ![](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, circlet, earrings, solo, blush, open_mouth, smile, looking_at_viewer, nipples, one_eye_closed \| \| 2 \| 9 \| ![](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, circlet, solo, smile, looking_at_viewer, bare_shoulders, blush, armlet, cleavage, open_mouth, pink_dress, medium_breasts \| \| 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, bare_shoulders, belt, full_body, hair_ornament, knee_boots, medium_breasts, side_slit, solo, white_dress, white_footwear, absurdly_long_hair, bangs, blush, collarbone, jewelry, long_dress, open_mouth, simple_background, sleeveless_dress, thighs, white_background, circlet, holding_book, leg_up, :d, armpits, hand_up, looking_at_viewer, open_book, pelvic_curtain \| \| 4 \| 25 \| ![](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, hetero, nipples, solo_focus, penis, blush, 1boy, sex, open_mouth, vaginal, circlet, mosaic_censoring, cum_in_pussy, spread_legs, nude, cum_on_body, facial, navel, tears \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| solo \| circlet \| looking_at_viewer \| cleavage \| navel \| smile \| blush \| hair_ornament \| pink_bikini \| open_mouth \| simple_background \| earrings \| nipples \| one_eye_closed \| bare_shoulders \| armlet \| pink_dress \| medium_breasts \| belt \| full_body \| knee_boots \| side_slit \| white_dress \| white_footwear \| absurdly_long_hair \| bangs \| collarbone \| jewelry \| long_dress \| sleeveless_dress \| thighs \| white_background \| holding_book \| leg_up \| :d \| armpits \| hand_up \| open_book \| pelvic_curtain \| hetero \| solo_focus \| penis \| 1boy \| sex \| vaginal \| mosaic_censoring \| cum_in_pussy \| spread_legs \| nude \| cum_on_body \| facial \| tears \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:----------\|:--------------------\|:-----------\|:--------\|:--------\|:--------\|:----------------\|:--------------\|:-------------\|:--------------------\|:-----------\|:----------\|:-----------------\|:-----------------\|:---------\|:-------------\|:-----------------\|:-------\|:------------\|:-------------\|:------------\|:--------------\|:-----------------\|:---------------------\|:--------\|:-------------\|:----------\|:-------------\|:-------------------\|:---------\|:-------------------\|:---------------\|:---------\|:-----\|:----------\|:----------\|:------------\|:-----------------\|:---------\|:-------------\|:--------\|:-------\|:------\|:----------\|:-------------------\|:---------------\|:--------------\|:-------\|:--------------\|:---------\|:--------\| \| 0 \| 26 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 5 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 9 \| ![](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 \| 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 \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 25 \| ![](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 \|
zirui3/cuad-instructions	--- license: cc-by-4.0 dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: text sequence: string - name: answer_start sequence: int64 - name: instruction dtype: string splits: - name: train num_bytes: 2933858226 num_examples: 44900 - name: test num_bytes: 397434014 num_examples: 8364 download_size: 6827533 dataset_size: 3331292240 ---
ChristophSchuhmann/OpenClip-B32-KNN-Captioner	--- license: apache-2.0 ---
KoziCreative/Testing	--- license: afl-3.0 ---
colkassad/map_navigation_v1	--- license: mit ---
open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1	--- pretty_name: Evaluation run of logicker/SkkuDS-DPO-72B-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [logicker/SkkuDS-DPO-72B-v1](https://huggingface.co/logicker/SkkuDS-DPO-72B-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-16T10:55:52.095277](https://huggingface.co/datasets/open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1/blob/main/results_2024-02-16T10-55-52.095277.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\": 0.7681185312998495,\n\ \ \"acc_stderr\": 0.02797672385731024,\n \"acc_norm\": 0.7728008468755523,\n\ \ \"acc_norm_stderr\": 0.02849748439769033,\n \"mc1\": 0.41370869033047736,\n\ \ \"mc1_stderr\": 0.0172408618120998,\n \"mc2\": 0.595432675425976,\n\ \ \"mc2_stderr\": 0.014511387340720846\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6271331058020477,\n \"acc_stderr\": 0.014131176760131172,\n\ \ \"acc_norm\": 0.659556313993174,\n \"acc_norm_stderr\": 0.013847460518892978\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6671977693686517,\n\ \ \"acc_stderr\": 0.004702533775930293,\n \"acc_norm\": 0.8599880501892053,\n\ \ \"acc_norm_stderr\": 0.0034629026011361893\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.7333333333333333,\n\ \ \"acc_stderr\": 0.038201699145179055,\n \"acc_norm\": 0.7333333333333333,\n\ \ \"acc_norm_stderr\": 0.038201699145179055\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.881578947368421,\n \"acc_stderr\": 0.026293995855474928,\n\ \ \"acc_norm\": 0.881578947368421,\n \"acc_norm_stderr\": 0.026293995855474928\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.8,\n\ \ \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.8,\n \ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.8226415094339623,\n \"acc_stderr\": 0.023508739218846934,\n\ \ \"acc_norm\": 0.8226415094339623,\n \"acc_norm_stderr\": 0.023508739218846934\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.9166666666666666,\n\ \ \"acc_stderr\": 0.023112508176051236,\n \"acc_norm\": 0.9166666666666666,\n\ \ \"acc_norm_stderr\": 0.023112508176051236\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.65,\n \"acc_stderr\": 0.04793724854411019,\n \"acc_norm\": 0.65,\n\ \ \"acc_norm_stderr\": 0.04793724854411019\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.7514450867052023,\n\ \ \"acc_stderr\": 0.03295304696818317,\n \"acc_norm\": 0.7514450867052023,\n\ \ \"acc_norm_stderr\": 0.03295304696818317\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.5490196078431373,\n \"acc_stderr\": 0.049512182523962604,\n\ \ \"acc_norm\": 0.5490196078431373,\n \"acc_norm_stderr\": 0.049512182523962604\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\ \ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.8042553191489362,\n \"acc_stderr\": 0.025937853139977148,\n\ \ \"acc_norm\": 0.8042553191489362,\n \"acc_norm_stderr\": 0.025937853139977148\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5877192982456141,\n\ \ \"acc_stderr\": 0.046306532033665956,\n \"acc_norm\": 0.5877192982456141,\n\ \ \"acc_norm_stderr\": 0.046306532033665956\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.7862068965517242,\n \"acc_stderr\": 0.03416520447747549,\n\ \ \"acc_norm\": 0.7862068965517242,\n \"acc_norm_stderr\": 0.03416520447747549\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.7116402116402116,\n \"acc_stderr\": 0.02333065405453588,\n \"\ acc_norm\": 0.7116402116402116,\n \"acc_norm_stderr\": 0.02333065405453588\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.5952380952380952,\n\ \ \"acc_stderr\": 0.04390259265377563,\n \"acc_norm\": 0.5952380952380952,\n\ \ \"acc_norm_stderr\": 0.04390259265377563\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.8838709677419355,\n \"acc_stderr\": 0.018225757949432306,\n \"\ acc_norm\": 0.8838709677419355,\n \"acc_norm_stderr\": 0.018225757949432306\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.6551724137931034,\n \"acc_stderr\": 0.03344283744280459,\n \"\ acc_norm\": 0.6551724137931034,\n \"acc_norm_stderr\": 0.03344283744280459\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.83,\n \"acc_stderr\": 0.03775251680686371,\n \"acc_norm\"\ : 0.83,\n \"acc_norm_stderr\": 0.03775251680686371\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8545454545454545,\n \"acc_stderr\": 0.027530196355066573,\n\ \ \"acc_norm\": 0.8545454545454545,\n \"acc_norm_stderr\": 0.027530196355066573\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.9343434343434344,\n \"acc_stderr\": 0.01764652667723333,\n \"\ acc_norm\": 0.9343434343434344,\n \"acc_norm_stderr\": 0.01764652667723333\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9896373056994818,\n \"acc_stderr\": 0.007308424386792194,\n\ \ \"acc_norm\": 0.9896373056994818,\n \"acc_norm_stderr\": 0.007308424386792194\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.8153846153846154,\n \"acc_stderr\": 0.01967163241310029,\n \ \ \"acc_norm\": 0.8153846153846154,\n \"acc_norm_stderr\": 0.01967163241310029\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.030485538042484616,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.030485538042484616\n },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\"\ : {\n \"acc\": 0.8445378151260504,\n \"acc_stderr\": 0.023536818625398904,\n\ \ \"acc_norm\": 0.8445378151260504,\n \"acc_norm_stderr\": 0.023536818625398904\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.5562913907284768,\n \"acc_stderr\": 0.04056527902281732,\n \"\ acc_norm\": 0.5562913907284768,\n \"acc_norm_stderr\": 0.04056527902281732\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.926605504587156,\n \"acc_stderr\": 0.011180976446357573,\n \"\ acc_norm\": 0.926605504587156,\n \"acc_norm_stderr\": 0.011180976446357573\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.6990740740740741,\n \"acc_stderr\": 0.03128039084329883,\n \"\ acc_norm\": 0.6990740740740741,\n \"acc_norm_stderr\": 0.03128039084329883\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073322,\n \"\ acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073322\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640273,\n \ \ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640273\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7982062780269058,\n\ \ \"acc_stderr\": 0.026936111912802273,\n \"acc_norm\": 0.7982062780269058,\n\ \ \"acc_norm_stderr\": 0.026936111912802273\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8702290076335878,\n \"acc_stderr\": 0.029473649496907065,\n\ \ \"acc_norm\": 0.8702290076335878,\n \"acc_norm_stderr\": 0.029473649496907065\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.9090909090909091,\n \"acc_stderr\": 0.026243194054073892,\n \"\ acc_norm\": 0.9090909090909091,\n \"acc_norm_stderr\": 0.026243194054073892\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8518518518518519,\n\ \ \"acc_stderr\": 0.03434300243630999,\n \"acc_norm\": 0.8518518518518519,\n\ \ \"acc_norm_stderr\": 0.03434300243630999\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8711656441717791,\n \"acc_stderr\": 0.02632138319878367,\n\ \ \"acc_norm\": 0.8711656441717791,\n \"acc_norm_stderr\": 0.02632138319878367\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.6607142857142857,\n\ \ \"acc_stderr\": 0.044939490686135404,\n \"acc_norm\": 0.6607142857142857,\n\ \ \"acc_norm_stderr\": 0.044939490686135404\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8640776699029126,\n \"acc_stderr\": 0.03393295729761011,\n\ \ \"acc_norm\": 0.8640776699029126,\n \"acc_norm_stderr\": 0.03393295729761011\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9401709401709402,\n\ \ \"acc_stderr\": 0.015537514263253874,\n \"acc_norm\": 0.9401709401709402,\n\ \ \"acc_norm_stderr\": 0.015537514263253874\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.86,\n \"acc_stderr\": 0.034873508801977725,\n \ \ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.034873508801977725\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.9144316730523627,\n\ \ \"acc_stderr\": 0.010002965568647285,\n \"acc_norm\": 0.9144316730523627,\n\ \ \"acc_norm_stderr\": 0.010002965568647285\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.8352601156069365,\n \"acc_stderr\": 0.019971040982442262,\n\ \ \"acc_norm\": 0.8352601156069365,\n \"acc_norm_stderr\": 0.019971040982442262\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.6424581005586593,\n\ \ \"acc_stderr\": 0.01602939447489489,\n \"acc_norm\": 0.6424581005586593,\n\ \ \"acc_norm_stderr\": 0.01602939447489489\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.8562091503267973,\n \"acc_stderr\": 0.020091188936043728,\n\ \ \"acc_norm\": 0.8562091503267973,\n \"acc_norm_stderr\": 0.020091188936043728\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.8295819935691319,\n\ \ \"acc_stderr\": 0.02135534302826405,\n \"acc_norm\": 0.8295819935691319,\n\ \ \"acc_norm_stderr\": 0.02135534302826405\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8611111111111112,\n \"acc_stderr\": 0.01924252622654454,\n\ \ \"acc_norm\": 0.8611111111111112,\n \"acc_norm_stderr\": 0.01924252622654454\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.624113475177305,\n \"acc_stderr\": 0.028893955412115882,\n \ \ \"acc_norm\": 0.624113475177305,\n \"acc_norm_stderr\": 0.028893955412115882\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.6140808344198174,\n\ \ \"acc_stderr\": 0.012433398911476134,\n \"acc_norm\": 0.6140808344198174,\n\ \ \"acc_norm_stderr\": 0.012433398911476134\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.8198529411764706,\n \"acc_stderr\": 0.023345163616544838,\n\ \ \"acc_norm\": 0.8198529411764706,\n \"acc_norm_stderr\": 0.023345163616544838\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.8088235294117647,\n \"acc_stderr\": 0.015908290136278067,\n \ \ \"acc_norm\": 0.8088235294117647,\n \"acc_norm_stderr\": 0.015908290136278067\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7363636363636363,\n\ \ \"acc_stderr\": 0.04220224692971987,\n \"acc_norm\": 0.7363636363636363,\n\ \ \"acc_norm_stderr\": 0.04220224692971987\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.8326530612244898,\n \"acc_stderr\": 0.02389714476891452,\n\ \ \"acc_norm\": 0.8326530612244898,\n \"acc_norm_stderr\": 0.02389714476891452\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.022076326101824667,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.022076326101824667\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.94,\n \"acc_stderr\": 0.023868325657594194,\n \ \ \"acc_norm\": 0.94,\n \"acc_norm_stderr\": 0.023868325657594194\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.572289156626506,\n\ \ \"acc_stderr\": 0.03851597683718533,\n \"acc_norm\": 0.572289156626506,\n\ \ \"acc_norm_stderr\": 0.03851597683718533\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8888888888888888,\n \"acc_stderr\": 0.024103384202072864,\n\ \ \"acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.024103384202072864\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.41370869033047736,\n\ \ \"mc1_stderr\": 0.0172408618120998,\n \"mc2\": 0.595432675425976,\n\ \ \"mc2_stderr\": 0.014511387340720846\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8263614838200474,\n \"acc_stderr\": 0.010646116480330996\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6588324488248674,\n \ \ \"acc_stderr\": 0.013059111935831497\n }\n}\n```" repo_url: https://huggingface.co/logicker/SkkuDS-DPO-72B-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|arc:challenge\|25_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-16T10-55-52.095277.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|gsm8k\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hellaswag\|10_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T10-55-52.095277.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T10-55-52.095277.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '/details_harness\|winogrande\|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-16T10-55-52.095277.parquet' - config_name: results data_files: - split: 2024_02_16T10_55_52.095277 path: - results_2024-02-16T10-55-52.095277.parquet - split: latest path: - results_2024-02-16T10-55-52.095277.parquet --- # Dataset Card for Evaluation run of logicker/SkkuDS-DPO-72B-v1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [logicker/SkkuDS-DPO-72B-v1](https://huggingface.co/logicker/SkkuDS-DPO-72B-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-16T10:55:52.095277](https://huggingface.co/datasets/open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1/blob/main/results_2024-02-16T10-55-52.095277.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": 0.7681185312998495, "acc_stderr": 0.02797672385731024, "acc_norm": 0.7728008468755523, "acc_norm_stderr": 0.02849748439769033, "mc1": 0.41370869033047736, "mc1_stderr": 0.0172408618120998, "mc2": 0.595432675425976, "mc2_stderr": 0.014511387340720846 }, "harness\|arc:challenge\|25": { "acc": 0.6271331058020477, "acc_stderr": 0.014131176760131172, "acc_norm": 0.659556313993174, "acc_norm_stderr": 0.013847460518892978 }, "harness\|hellaswag\|10": { "acc": 0.6671977693686517, "acc_stderr": 0.004702533775930293, "acc_norm": 0.8599880501892053, "acc_norm_stderr": 0.0034629026011361893 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.7333333333333333, "acc_stderr": 0.038201699145179055, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.038201699145179055 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.881578947368421, "acc_stderr": 0.026293995855474928, "acc_norm": 0.881578947368421, "acc_norm_stderr": 0.026293995855474928 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.8226415094339623, "acc_stderr": 0.023508739218846934, "acc_norm": 0.8226415094339623, "acc_norm_stderr": 0.023508739218846934 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.9166666666666666, "acc_stderr": 0.023112508176051236, "acc_norm": 0.9166666666666666, "acc_norm_stderr": 0.023112508176051236 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.65, "acc_stderr": 0.04793724854411019, "acc_norm": 0.65, "acc_norm_stderr": 0.04793724854411019 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818317, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818317 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.5490196078431373, "acc_stderr": 0.049512182523962604, "acc_norm": 0.5490196078431373, "acc_norm_stderr": 0.049512182523962604 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.8042553191489362, "acc_stderr": 0.025937853139977148, "acc_norm": 0.8042553191489362, "acc_norm_stderr": 0.025937853139977148 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5877192982456141, "acc_stderr": 0.046306532033665956, "acc_norm": 0.5877192982456141, "acc_norm_stderr": 0.046306532033665956 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.7862068965517242, "acc_stderr": 0.03416520447747549, "acc_norm": 0.7862068965517242, "acc_norm_stderr": 0.03416520447747549 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.7116402116402116, "acc_stderr": 0.02333065405453588, "acc_norm": 0.7116402116402116, "acc_norm_stderr": 0.02333065405453588 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.5952380952380952, "acc_stderr": 0.04390259265377563, "acc_norm": 0.5952380952380952, "acc_norm_stderr": 0.04390259265377563 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8838709677419355, "acc_stderr": 0.018225757949432306, "acc_norm": 0.8838709677419355, "acc_norm_stderr": 0.018225757949432306 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.6551724137931034, "acc_stderr": 0.03344283744280459, "acc_norm": 0.6551724137931034, "acc_norm_stderr": 0.03344283744280459 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066573, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066573 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.9343434343434344, "acc_stderr": 0.01764652667723333, "acc_norm": 0.9343434343434344, "acc_norm_stderr": 0.01764652667723333 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9896373056994818, "acc_stderr": 0.007308424386792194, "acc_norm": 0.9896373056994818, "acc_norm_stderr": 0.007308424386792194 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.8153846153846154, "acc_stderr": 0.01967163241310029, "acc_norm": 0.8153846153846154, "acc_norm_stderr": 0.01967163241310029 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.5, "acc_stderr": 0.030485538042484616, "acc_norm": 0.5, "acc_norm_stderr": 0.030485538042484616 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.8445378151260504, "acc_stderr": 0.023536818625398904, "acc_norm": 0.8445378151260504, "acc_norm_stderr": 0.023536818625398904 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.5562913907284768, "acc_stderr": 0.04056527902281732, "acc_norm": 0.5562913907284768, "acc_norm_stderr": 0.04056527902281732 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.926605504587156, "acc_stderr": 0.011180976446357573, "acc_norm": 0.926605504587156, "acc_norm_stderr": 0.011180976446357573 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.6990740740740741, "acc_stderr": 0.03128039084329883, "acc_norm": 0.6990740740740741, "acc_norm_stderr": 0.03128039084329883 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9313725490196079, "acc_stderr": 0.017744453647073322, "acc_norm": 0.9313725490196079, "acc_norm_stderr": 0.017744453647073322 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.9029535864978903, "acc_stderr": 0.019269323025640273, "acc_norm": 0.9029535864978903, "acc_norm_stderr": 0.019269323025640273 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7982062780269058, "acc_stderr": 0.026936111912802273, "acc_norm": 0.7982062780269058, "acc_norm_stderr": 0.026936111912802273 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8702290076335878, "acc_stderr": 0.029473649496907065, "acc_norm": 0.8702290076335878, "acc_norm_stderr": 0.029473649496907065 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.9090909090909091, "acc_stderr": 0.026243194054073892, "acc_norm": 0.9090909090909091, "acc_norm_stderr": 0.026243194054073892 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8518518518518519, "acc_stderr": 0.03434300243630999, "acc_norm": 0.8518518518518519, "acc_norm_stderr": 0.03434300243630999 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.8711656441717791, "acc_stderr": 0.02632138319878367, "acc_norm": 0.8711656441717791, "acc_norm_stderr": 0.02632138319878367 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.6607142857142857, "acc_stderr": 0.044939490686135404, "acc_norm": 0.6607142857142857, "acc_norm_stderr": 0.044939490686135404 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8640776699029126, "acc_stderr": 0.03393295729761011, "acc_norm": 0.8640776699029126, "acc_norm_stderr": 0.03393295729761011 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9401709401709402, "acc_stderr": 0.015537514263253874, "acc_norm": 0.9401709401709402, "acc_norm_stderr": 0.015537514263253874 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.86, "acc_stderr": 0.034873508801977725, "acc_norm": 0.86, "acc_norm_stderr": 0.034873508801977725 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.9144316730523627, "acc_stderr": 0.010002965568647285, "acc_norm": 0.9144316730523627, "acc_norm_stderr": 0.010002965568647285 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.8352601156069365, "acc_stderr": 0.019971040982442262, "acc_norm": 0.8352601156069365, "acc_norm_stderr": 0.019971040982442262 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.6424581005586593, "acc_stderr": 0.01602939447489489, "acc_norm": 0.6424581005586593, "acc_norm_stderr": 0.01602939447489489 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.8562091503267973, "acc_stderr": 0.020091188936043728, "acc_norm": 0.8562091503267973, "acc_norm_stderr": 0.020091188936043728 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.8295819935691319, "acc_stderr": 0.02135534302826405, "acc_norm": 0.8295819935691319, "acc_norm_stderr": 0.02135534302826405 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8611111111111112, "acc_stderr": 0.01924252622654454, "acc_norm": 0.8611111111111112, "acc_norm_stderr": 0.01924252622654454 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.624113475177305, "acc_stderr": 0.028893955412115882, "acc_norm": 0.624113475177305, "acc_norm_stderr": 0.028893955412115882 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.6140808344198174, "acc_stderr": 0.012433398911476134, "acc_norm": 0.6140808344198174, "acc_norm_stderr": 0.012433398911476134 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.8198529411764706, "acc_stderr": 0.023345163616544838, "acc_norm": 0.8198529411764706, "acc_norm_stderr": 0.023345163616544838 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.8088235294117647, "acc_stderr": 0.015908290136278067, "acc_norm": 0.8088235294117647, "acc_norm_stderr": 0.015908290136278067 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7363636363636363, "acc_stderr": 0.04220224692971987, "acc_norm": 0.7363636363636363, "acc_norm_stderr": 0.04220224692971987 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.8326530612244898, "acc_stderr": 0.02389714476891452, "acc_norm": 0.8326530612244898, "acc_norm_stderr": 0.02389714476891452 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8905472636815921, "acc_stderr": 0.022076326101824667, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.022076326101824667 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.94, "acc_stderr": 0.023868325657594194, "acc_norm": 0.94, "acc_norm_stderr": 0.023868325657594194 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.572289156626506, "acc_stderr": 0.03851597683718533, "acc_norm": 0.572289156626506, "acc_norm_stderr": 0.03851597683718533 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8888888888888888, "acc_stderr": 0.024103384202072864, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.024103384202072864 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.41370869033047736, "mc1_stderr": 0.0172408618120998, "mc2": 0.595432675425976, "mc2_stderr": 0.014511387340720846 }, "harness\|winogrande\|5": { "acc": 0.8263614838200474, "acc_stderr": 0.010646116480330996 }, "harness\|gsm8k\|5": { "acc": 0.6588324488248674, "acc_stderr": 0.013059111935831497 } } ``` ## 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]

autoevaluate/autoeval-eval-futin__feed-top_en-c0540d-2175569969

--- type: predictions tags: - autotrain - evaluation datasets: - futin/feed eval_info: task: text_zero_shot_classification model: facebook/opt-66b metrics: [] dataset_name: futin/feed dataset_config: top_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-66b * Dataset: futin/feed * Config: top_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.

proserve/medical-instruct-mixer-v2

--- dataset_info: features: - name: content dtype: string splits: - name: train num_bytes: 463565438.0 num_examples: 482593 - name: test num_bytes: 74684196.0 num_examples: 40159 download_size: 278795913 dataset_size: 538249634.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

Ti-Ma/wikipedia_2018

--- license: cc-by-sa-3.0 ---

lim4349/korquad

--- dataset_info: features: - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: id dtype: string - name: answers struct: - name: text sequence: string - name: answer_start sequence: int64 splits: - name: train num_bytes: 75266074 num_examples: 54366 - name: validation num_bytes: 8358264 num_examples: 6041 download_size: 51472501 dataset_size: 83624338 --- # Dataset Card for "korquad" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

mstz/vertebral_column

--- language: - en tags: - vertebral_column - tabular_classification - binary_classification - UCI pretty_name: Vertebral Column size_categories: - n<1K task_categories: - tabular-classification configs: - vertebral license: cc --- # Vertebral Column The [Vertebral Column dataset](https://archive.ics.uci.edu/ml/datasets/vertebral+column) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets). # Configurations and tasks | **Configuration** | **Task** | **Description** | |-------------------|---------------------------|-------------------------| | abnormal | Binary classification | Is the spine abnormal?| # Usage ```python from datasets import load_dataset dataset = load_dataset("mstz/vertebral_column")["train"] ```

torchgeo/l8biome

--- task_categories: - image-segmentation tags: - climate pretty_name: L8 Biome size_categories: - n<1K license: cc0-1.0 --- Redistribution of data from https://landsat.usgs.gov/landsat-8-cloud-cover-assessment-validation-data, masks modified to add georeferencing metadata. Landsat Data Distribution Policy: https://www.usgs.gov/media/files/landsat-data-distribution-policy

akahana/oscar-unshuffled_deduplicated_id_10k

--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 18527241 num_examples: 10000 download_size: 10371685 dataset_size: 18527241 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "oscar-unshuffled_deduplicated_id_10k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Kaludi/data-food-category-classification

--- task_categories: - image-classification --- # Dataset for project: food-category-classification ## Dataset Description This dataset is for project food-category-classification. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "image": "<512x512 RGB PIL image>", "target": 0 }, { "image": "<512x512 RGB PIL image>", "target": 0 } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "image": "Image(decode=True, id=None)", "target": "ClassLabel(names=['Bread', 'Dairy product', 'Dessert', 'Egg', 'Fried food', 'Meat', 'Noodles-Pasta', 'Rice', 'Seafood', 'Soup', 'Vegetable-Fruit'], 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 | 1210 | | valid | 275 |

EkBass/fin-eng-dataset

--- license: gpl-3.0 task_categories: - translation language: - fi - en tags: - text - translation - finnish - english pretty_name: fin-eng-dataset-6k --- # fin-eng-dataset # Updated 29th October 2023 New version. Covers around 30K individual words and around 10K sentences, phrases etc. # Updated 19th September 2023 New version. Over 20K unique words and over 2K sentences/paragraphs fin-eng versions. # Updated 10th September 2023 Updated version. Around 15K different words and a couple of thousands of sentences, paragraphs, quots, questions and answers. # English The file fine-eng-dataset.json contains over 9000 individual Finnish words with their English translations. Since some of the words are names of places, people, etc., the exact number of Finnish words is unknown. Part of the data includes a list of Finnish words along with their English translations. However, the majority of the data consists of Finnish sentences, questions, statements, etc., that have been translated into English. The data begins with a list of the thousand most common Finnish words with their translations. Following that are sentences, including quotes from Martti Ahtisaari, Public Domain books like "Open Life," Maila Talvio's "The Destruction of Dark Cabin," as well as sentences from free novellas "Midsummer Gift for Readers" and "Erotic Novella: Towards Malaysia." In addition, sentences, quotes from movies, basic sentences produced by artificial intelligence, personal messages, etc., have been added, totaling over a thousand entries. Random paragraphs from Finnish Wikipedia's "random article" have also been included. The work is intended to continue indefinitely. Help is needed; please contact krisu.virtanen@gmail.com. # Suomeksi fine-eng-dataset.json sisältää yli 9000 yksittäistä suomenkielistä sanaa englanninkielisenä käännöksenään. Koska osa sanoista on paikkojen-, ihmisten-, jne, nimiä niin tarkkaa määrää suomenkielisestä sanoista ei tiedetä. Osassa dataa on syötetty lista suomenkielisiä sanoja sekä niiden englanninkieliset käännökset. Suurin osa datasta on kuitenkin suomenkielisiä lauseita, kysymyksiä, toteamuksia jne. jotka on käännetty englanniksi. Data alkaa luettelolla tuhannesta yleisimmästä suomenkilisestä sanasta käännöksineen. Tämän jälkeen tulee lauseita, mm. lainauksia Martti Ahtesaaresta, Public Domain kirjoista "Avoin Elämä", Maila Talvion "Pimeänpirtin hävitys", sekä lauseita ilmaisista novelleista "Juhannustalahja lukijoille" ja "Erottiinen novelli: Kohti Malesiaa". Lisäksi on syötetty lauseita, lainauksia elokuvista, tekoälyn tuottamia peruslauseita, omia viestejä jne. kaiken kaikkiaan yli tuhannen kappaleen verran sekä otettu satunnaisia kappaleita suomenkielisestä wikipediasta "satunnainen artikkeli". Tarkoitus on jatkaa työtä toistaiseksi. Apua tarvitaan, ota yhteyttä krisu.virtanen@gmail.com

open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5

--- pretty_name: Evaluation run of BFauber/lora_llama2-13b_10e5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BFauber/lora_llama2-13b_10e5](https://huggingface.co/BFauber/lora_llama2-13b_10e5)\ \ 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_BFauber__lora_llama2-13b_10e5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-10T01:54:15.995961](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5/blob/main/results_2024-02-10T01-54-15.995961.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\": 0.5557440720682312,\n\ \ \"acc_stderr\": 0.03358121479787839,\n \"acc_norm\": 0.5618325027332456,\n\ \ \"acc_norm_stderr\": 0.03430489410692684,\n \"mc1\": 0.2607099143206854,\n\ \ \"mc1_stderr\": 0.015368841620766373,\n \"mc2\": 0.37646299641377995,\n\ \ \"mc2_stderr\": 0.013743052527776188\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5614334470989761,\n \"acc_stderr\": 0.014500682618212864,\n\ \ \"acc_norm\": 0.5921501706484642,\n \"acc_norm_stderr\": 0.014361097288449703\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.616211909978092,\n\ \ \"acc_stderr\": 0.004853134271547769,\n \"acc_norm\": 0.8241386178052181,\n\ \ \"acc_norm_stderr\": 0.003799241408502968\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\": 0.5407407407407407,\n\ \ \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.5407407407407407,\n\ \ \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5328947368421053,\n \"acc_stderr\": 0.04060127035236397,\n\ \ \"acc_norm\": 0.5328947368421053,\n \"acc_norm_stderr\": 0.04060127035236397\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.53,\n\ \ \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.630188679245283,\n \"acc_stderr\": 0.029711421880107933,\n\ \ \"acc_norm\": 0.630188679245283,\n \"acc_norm_stderr\": 0.029711421880107933\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5972222222222222,\n\ \ \"acc_stderr\": 0.04101405519842426,\n \"acc_norm\": 0.5972222222222222,\n\ \ \"acc_norm_stderr\": 0.04101405519842426\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.47,\n\ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5491329479768786,\n\ \ \"acc_stderr\": 0.0379401267469703,\n \"acc_norm\": 0.5491329479768786,\n\ \ \"acc_norm_stderr\": 0.0379401267469703\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.043364327079931785,\n\ \ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.043364327079931785\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.41702127659574467,\n \"acc_stderr\": 0.03223276266711712,\n\ \ \"acc_norm\": 0.41702127659574467,\n \"acc_norm_stderr\": 0.03223276266711712\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.30701754385964913,\n\ \ \"acc_stderr\": 0.043391383225798615,\n \"acc_norm\": 0.30701754385964913,\n\ \ \"acc_norm_stderr\": 0.043391383225798615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\ \ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3333333333333333,\n \"acc_stderr\": 0.024278568024307702,\n \"\ acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.024278568024307702\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3253968253968254,\n\ \ \"acc_stderr\": 0.041905964388711366,\n \"acc_norm\": 0.3253968253968254,\n\ \ \"acc_norm_stderr\": 0.041905964388711366\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.048523658709391,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.048523658709391\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6838709677419355,\n\ \ \"acc_stderr\": 0.026450874489042774,\n \"acc_norm\": 0.6838709677419355,\n\ \ \"acc_norm_stderr\": 0.026450874489042774\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.458128078817734,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\"\ : 0.58,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6303030303030303,\n \"acc_stderr\": 0.03769430314512566,\n\ \ \"acc_norm\": 0.6303030303030303,\n \"acc_norm_stderr\": 0.03769430314512566\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6818181818181818,\n \"acc_stderr\": 0.0331847733384533,\n \"acc_norm\"\ : 0.6818181818181818,\n \"acc_norm_stderr\": 0.0331847733384533\n },\n\ \ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \ \ \"acc\": 0.8082901554404145,\n \"acc_stderr\": 0.02840895362624527,\n\ \ \"acc_norm\": 0.8082901554404145,\n \"acc_norm_stderr\": 0.02840895362624527\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5076923076923077,\n \"acc_stderr\": 0.02534800603153477,\n \ \ \"acc_norm\": 0.5076923076923077,\n \"acc_norm_stderr\": 0.02534800603153477\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5546218487394958,\n \"acc_stderr\": 0.032284106267163895,\n\ \ \"acc_norm\": 0.5546218487394958,\n \"acc_norm_stderr\": 0.032284106267163895\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7504587155963303,\n \"acc_stderr\": 0.018553897629501617,\n \"\ acc_norm\": 0.7504587155963303,\n \"acc_norm_stderr\": 0.018553897629501617\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\"\ : 0.75,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.7130801687763713,\n \"acc_stderr\": 0.02944377302259469,\n\ \ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.02944377302259469\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6457399103139013,\n\ \ \"acc_stderr\": 0.032100621541349864,\n \"acc_norm\": 0.6457399103139013,\n\ \ \"acc_norm_stderr\": 0.032100621541349864\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6412213740458015,\n \"acc_stderr\": 0.04206739313864908,\n\ \ \"acc_norm\": 0.6412213740458015,\n \"acc_norm_stderr\": 0.04206739313864908\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.039418975265163025,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.039418975265163025\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6687116564417178,\n \"acc_stderr\": 0.03697983910025588,\n\ \ \"acc_norm\": 0.6687116564417178,\n \"acc_norm_stderr\": 0.03697983910025588\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.30357142857142855,\n\ \ \"acc_stderr\": 0.043642261558410445,\n \"acc_norm\": 0.30357142857142855,\n\ \ \"acc_norm_stderr\": 0.043642261558410445\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\": 0.8076923076923077,\n\ \ \"acc_stderr\": 0.025819233256483717,\n \"acc_norm\": 0.8076923076923077,\n\ \ \"acc_norm_stderr\": 0.025819233256483717\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7420178799489144,\n\ \ \"acc_stderr\": 0.01564583018834895,\n \"acc_norm\": 0.7420178799489144,\n\ \ \"acc_norm_stderr\": 0.01564583018834895\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6473988439306358,\n \"acc_stderr\": 0.025722802200895806,\n\ \ \"acc_norm\": 0.6473988439306358,\n \"acc_norm_stderr\": 0.025722802200895806\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.264804469273743,\n\ \ \"acc_stderr\": 0.014756906483260666,\n \"acc_norm\": 0.264804469273743,\n\ \ \"acc_norm_stderr\": 0.014756906483260666\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6339869281045751,\n \"acc_stderr\": 0.027582811415159607,\n\ \ \"acc_norm\": 0.6339869281045751,\n \"acc_norm_stderr\": 0.027582811415159607\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6559485530546624,\n\ \ \"acc_stderr\": 0.026981478043648036,\n \"acc_norm\": 0.6559485530546624,\n\ \ \"acc_norm_stderr\": 0.026981478043648036\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6358024691358025,\n \"acc_stderr\": 0.026774929899722327,\n\ \ \"acc_norm\": 0.6358024691358025,\n \"acc_norm_stderr\": 0.026774929899722327\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.425531914893617,\n \"acc_stderr\": 0.029494827600144373,\n \ \ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.029494827600144373\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4230769230769231,\n\ \ \"acc_stderr\": 0.012618204066588392,\n \"acc_norm\": 0.4230769230769231,\n\ \ \"acc_norm_stderr\": 0.012618204066588392\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5147058823529411,\n \"acc_stderr\": 0.03035969707904612,\n\ \ \"acc_norm\": 0.5147058823529411,\n \"acc_norm_stderr\": 0.03035969707904612\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.5506535947712419,\n \"acc_stderr\": 0.02012376652802727,\n \ \ \"acc_norm\": 0.5506535947712419,\n \"acc_norm_stderr\": 0.02012376652802727\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6454545454545455,\n\ \ \"acc_stderr\": 0.045820048415054174,\n \"acc_norm\": 0.6454545454545455,\n\ \ \"acc_norm_stderr\": 0.045820048415054174\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6163265306122448,\n \"acc_stderr\": 0.03113088039623593,\n\ \ \"acc_norm\": 0.6163265306122448,\n \"acc_norm_stderr\": 0.03113088039623593\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.746268656716418,\n\ \ \"acc_stderr\": 0.03076944496729602,\n \"acc_norm\": 0.746268656716418,\n\ \ \"acc_norm_stderr\": 0.03076944496729602\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.463855421686747,\n\ \ \"acc_stderr\": 0.03882310850890593,\n \"acc_norm\": 0.463855421686747,\n\ \ \"acc_norm_stderr\": 0.03882310850890593\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2607099143206854,\n\ \ \"mc1_stderr\": 0.015368841620766373,\n \"mc2\": 0.37646299641377995,\n\ \ \"mc2_stderr\": 0.013743052527776188\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7695343330702447,\n \"acc_stderr\": 0.011835872164836671\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.221379833206975,\n \ \ \"acc_stderr\": 0.01143600000425351\n }\n}\n```" repo_url: https://huggingface.co/BFauber/lora_llama2-13b_10e5 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_10T01_54_15.995961 path: - '**/details_harness|arc:challenge|25_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-10T01-54-15.995961.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|gsm8k|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hellaswag|10_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-54-15.995961.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-54-15.995961.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T01-54-15.995961.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_10T01_54_15.995961 path: - '**/details_harness|winogrande|5_2024-02-10T01-54-15.995961.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-10T01-54-15.995961.parquet' - config_name: results data_files: - split: 2024_02_10T01_54_15.995961 path: - results_2024-02-10T01-54-15.995961.parquet - split: latest path: - results_2024-02-10T01-54-15.995961.parquet --- # Dataset Card for Evaluation run of BFauber/lora_llama2-13b_10e5  Dataset automatically created during the evaluation run of model [BFauber/lora_llama2-13b_10e5](https://huggingface.co/BFauber/lora_llama2-13b_10e5) 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_BFauber__lora_llama2-13b_10e5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-10T01:54:15.995961](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5/blob/main/results_2024-02-10T01-54-15.995961.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": 0.5557440720682312, "acc_stderr": 0.03358121479787839, "acc_norm": 0.5618325027332456, "acc_norm_stderr": 0.03430489410692684, "mc1": 0.2607099143206854, "mc1_stderr": 0.015368841620766373, "mc2": 0.37646299641377995, "mc2_stderr": 0.013743052527776188 }, "harness|arc:challenge|25": { "acc": 0.5614334470989761, "acc_stderr": 0.014500682618212864, "acc_norm": 0.5921501706484642, "acc_norm_stderr": 0.014361097288449703 }, "harness|hellaswag|10": { "acc": 0.616211909978092, "acc_stderr": 0.004853134271547769, "acc_norm": 0.8241386178052181, "acc_norm_stderr": 0.003799241408502968 }, "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": 0.5407407407407407, "acc_stderr": 0.04304979692464242, "acc_norm": 0.5407407407407407, "acc_norm_stderr": 0.04304979692464242 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5328947368421053, "acc_stderr": 0.04060127035236397, "acc_norm": 0.5328947368421053, "acc_norm_stderr": 0.04060127035236397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.630188679245283, "acc_stderr": 0.029711421880107933, "acc_norm": 0.630188679245283, "acc_norm_stderr": 0.029711421880107933 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5972222222222222, "acc_stderr": 0.04101405519842426, "acc_norm": 0.5972222222222222, "acc_norm_stderr": 0.04101405519842426 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5491329479768786, "acc_stderr": 0.0379401267469703, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.0379401267469703 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.41702127659574467, "acc_stderr": 0.03223276266711712, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.03223276266711712 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 0.043391383225798615, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.043391383225798615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.024278568024307702, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.024278568024307702 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3253968253968254, "acc_stderr": 0.041905964388711366, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.041905964388711366 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6838709677419355, "acc_stderr": 0.026450874489042774, "acc_norm": 0.6838709677419355, "acc_norm_stderr": 0.026450874489042774 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785741, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6303030303030303, "acc_stderr": 0.03769430314512566, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.03769430314512566 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6818181818181818, "acc_stderr": 0.0331847733384533, "acc_norm": 0.6818181818181818, "acc_norm_stderr": 0.0331847733384533 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8082901554404145, "acc_stderr": 0.02840895362624527, "acc_norm": 0.8082901554404145, "acc_norm_stderr": 0.02840895362624527 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5076923076923077, "acc_stderr": 0.02534800603153477, "acc_norm": 0.5076923076923077, "acc_norm_stderr": 0.02534800603153477 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340492, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340492 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.5546218487394958, "acc_stderr": 0.032284106267163895, "acc_norm": 0.5546218487394958, "acc_norm_stderr": 0.032284106267163895 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.7504587155963303, "acc_stderr": 0.018553897629501617, "acc_norm": 0.7504587155963303, "acc_norm_stderr": 0.018553897629501617 }, "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": 0.75, "acc_stderr": 0.03039153369274154, "acc_norm": 0.75, "acc_norm_stderr": 0.03039153369274154 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7130801687763713, "acc_stderr": 0.02944377302259469, "acc_norm": 0.7130801687763713, "acc_norm_stderr": 0.02944377302259469 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6457399103139013, "acc_stderr": 0.032100621541349864, "acc_norm": 0.6457399103139013, "acc_norm_stderr": 0.032100621541349864 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.6412213740458015, "acc_stderr": 0.04206739313864908, "acc_norm": 0.6412213740458015, "acc_norm_stderr": 0.04206739313864908 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7520661157024794, "acc_stderr": 0.039418975265163025, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.039418975265163025 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.6687116564417178, "acc_stderr": 0.03697983910025588, "acc_norm": 0.6687116564417178, "acc_norm_stderr": 0.03697983910025588 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.30357142857142855, "acc_stderr": 0.043642261558410445, "acc_norm": 0.30357142857142855, "acc_norm_stderr": 0.043642261558410445 }, "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": 0.8076923076923077, "acc_stderr": 0.025819233256483717, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.025819233256483717 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7420178799489144, "acc_stderr": 0.01564583018834895, "acc_norm": 0.7420178799489144, "acc_norm_stderr": 0.01564583018834895 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6473988439306358, "acc_stderr": 0.025722802200895806, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.025722802200895806 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.264804469273743, "acc_stderr": 0.014756906483260666, "acc_norm": 0.264804469273743, "acc_norm_stderr": 0.014756906483260666 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6339869281045751, "acc_stderr": 0.027582811415159607, "acc_norm": 0.6339869281045751, "acc_norm_stderr": 0.027582811415159607 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6559485530546624, "acc_stderr": 0.026981478043648036, "acc_norm": 0.6559485530546624, "acc_norm_stderr": 0.026981478043648036 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6358024691358025, "acc_stderr": 0.026774929899722327, "acc_norm": 0.6358024691358025, "acc_norm_stderr": 0.026774929899722327 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.425531914893617, "acc_stderr": 0.029494827600144373, "acc_norm": 0.425531914893617, "acc_norm_stderr": 0.029494827600144373 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4230769230769231, "acc_stderr": 0.012618204066588392, "acc_norm": 0.4230769230769231, "acc_norm_stderr": 0.012618204066588392 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5147058823529411, "acc_stderr": 0.03035969707904612, "acc_norm": 0.5147058823529411, "acc_norm_stderr": 0.03035969707904612 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.5506535947712419, "acc_stderr": 0.02012376652802727, "acc_norm": 0.5506535947712419, "acc_norm_stderr": 0.02012376652802727 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6454545454545455, "acc_stderr": 0.045820048415054174, "acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6163265306122448, "acc_stderr": 0.03113088039623593, "acc_norm": 0.6163265306122448, "acc_norm_stderr": 0.03113088039623593 }, "harness|hendrycksTest-sociology|5": { "acc": 0.746268656716418, "acc_stderr": 0.03076944496729602, "acc_norm": 0.746268656716418, "acc_norm_stderr": 0.03076944496729602 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness|hendrycksTest-virology|5": { "acc": 0.463855421686747, "acc_stderr": 0.03882310850890593, "acc_norm": 0.463855421686747, "acc_norm_stderr": 0.03882310850890593 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness|truthfulqa:mc|0": { "mc1": 0.2607099143206854, "mc1_stderr": 0.015368841620766373, "mc2": 0.37646299641377995, "mc2_stderr": 0.013743052527776188 }, "harness|winogrande|5": { "acc": 0.7695343330702447, "acc_stderr": 0.011835872164836671 }, "harness|gsm8k|5": { "acc": 0.221379833206975, "acc_stderr": 0.01143600000425351 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

CyberHarem/sona_leagueoflegends

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sona (League of Legends) This is the dataset of sona (League of Legends), containing 500 images and their tags. The core tags of this character are `long_hair, twintails, breasts, large_breasts, blue_hair, blue_eyes, very_long_hair, aqua_hair, hair_ornament, multicolored_hair, gradient_hair`, 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 | 748.13 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 500 | 425.57 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 1150 | 860.62 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 500 | 658.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1150 | 1.20 GiB | [Download](https://huggingface.co/datasets/CyberHarem/sona_leagueoflegends/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/sona_leagueoflegends', 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 | 20 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, bare_shoulders, cleavage, solo, instrument, dress, lips | | 1 | 8 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, bare_shoulders, cleavage, collarbone, solo, upper_body, bangs, blush, looking_at_viewer, simple_background, white_background, closed_mouth, low_neckline, smile, blue_dress | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, cleavage, necklace, solo, star_(symbol), midriff, navel, earrings, fingerless_gloves, looking_at_viewer, bra, green_gloves, purple_hair, smile | | 3 | 6 | ![](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, nipples, nude, pussy, solo, aqua_eyes, blush, looking_at_viewer, navel, on_back, uncensored, bed_sheet, green_eyes, smile | | 4 | 10 | ![](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) | 1boy, 1girl, hetero, nipples, solo_focus, penis, blush, cum, nude, collarbone, huge_breasts, paizuri, bare_shoulders, blonde_hair, male_pubic_hair, parted_lips, smile, uncensored | | 5 | 5 | ![](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, black_panties, looking_at_viewer, solo, black_bra, black_thighhighs, blonde_hair, garter_belt, garter_straps, blush, cleavage, collarbone, huge_breasts, skindentation, ass, bare_shoulders, curvy, hair_between_eyes, lingerie, looking_back, navel, open_mouth, parted_lips, simple_background, thick_thighs, thigh_gap, underwear_only | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bare_shoulders | cleavage | solo | instrument | dress | lips | collarbone | upper_body | bangs | blush | looking_at_viewer | simple_background | white_background | closed_mouth | low_neckline | smile | blue_dress | necklace | star_(symbol) | midriff | navel | earrings | fingerless_gloves | bra | green_gloves | purple_hair | nipples | nude | pussy | aqua_eyes | on_back | uncensored | bed_sheet | green_eyes | 1boy | hetero | solo_focus | penis | cum | huge_breasts | paizuri | blonde_hair | male_pubic_hair | parted_lips | black_panties | black_bra | black_thighhighs | garter_belt | garter_straps | skindentation | ass | curvy | hair_between_eyes | lingerie | looking_back | open_mouth | thick_thighs | thigh_gap | underwear_only | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------------|:-----------|:-------|:-------------|:--------|:-------|:-------------|:-------------|:--------|:--------|:--------------------|:--------------------|:-------------------|:---------------|:---------------|:--------|:-------------|:-----------|:----------------|:----------|:--------|:-----------|:--------------------|:------|:---------------|:--------------|:----------|:-------|:--------|:------------|:----------|:-------------|:------------|:-------------|:-------|:---------|:-------------|:--------|:------|:---------------|:----------|:--------------|:------------------|:--------------|:----------------|:------------|:-------------------|:--------------|:----------------|:----------------|:------|:--------|:--------------------|:-----------|:---------------|:-------------|:---------------|:------------|:-----------------| | 0 | 20 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 8 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | | X | X | | | | | | | | X | | | | | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 6 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 10 | ![](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 | | | | | | | | | | | | | | | | | 5 | 5 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | X | X | X | X | | | | X | | | X | X | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | X | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf

--- pretty_name: Evaluation run of ehartford/CodeLlama-34b-Python-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ehartford/CodeLlama-34b-Python-hf](https://huggingface.co/ehartford/CodeLlama-34b-Python-hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 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_ehartford__CodeLlama-34b-Python-hf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T22:02:41.600326](https://huggingface.co/datasets/open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf/blob/main/results_2023-09-17T22-02-41.600326.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0012583892617449664,\n\ \ \"em_stderr\": 0.00036305608931190325,\n \"f1\": 0.0019200922818791944,\n\ \ \"f1_stderr\": 0.0004138356823487018,\n \"acc\": 0.3307024467245462,\n\ \ \"acc_stderr\": 0.006650084932921209\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0012583892617449664,\n \"em_stderr\": 0.00036305608931190325,\n\ \ \"f1\": 0.0019200922818791944,\n \"f1_stderr\": 0.0004138356823487018\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.6614048934490924,\n\ \ \"acc_stderr\": 0.013300169865842417\n }\n}\n```" repo_url: https://huggingface.co/ehartford/CodeLlama-34b-Python-hf 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_26T01_57_15.339948 path: - '**/details_harness|arc:challenge|25_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-26T01:57:15.339948.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T22_02_41.600326 path: - '**/details_harness|drop|3_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '**/details_harness|drop|3_2023-09-17T22-02-41.600326.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T22_02_41.600326 path: - '**/details_harness|gsm8k|5_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-09-17T22-02-41.600326.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hellaswag|10_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-26T01:57:15.339948.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-management|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T01:57:15.339948.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_26T01_57_15.339948 path: - '**/details_harness|truthfulqa:mc|0_2023-08-26T01:57:15.339948.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-26T01:57:15.339948.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T22_02_41.600326 path: - '**/details_harness|winogrande|5_2023-09-17T22-02-41.600326.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-09-17T22-02-41.600326.parquet' - config_name: results data_files: - split: 2023_08_26T01_57_15.339948 path: - results_2023-08-26T01:57:15.339948.parquet - split: 2023_09_17T22_02_41.600326 path: - results_2023-09-17T22-02-41.600326.parquet - split: latest path: - results_2023-09-17T22-02-41.600326.parquet --- # Dataset Card for Evaluation run of ehartford/CodeLlama-34b-Python-hf ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/ehartford/CodeLlama-34b-Python-hf - **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 [ehartford/CodeLlama-34b-Python-hf](https://huggingface.co/ehartford/CodeLlama-34b-Python-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 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_ehartford__CodeLlama-34b-Python-hf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T22:02:41.600326](https://huggingface.co/datasets/open-llm-leaderboard/details_ehartford__CodeLlama-34b-Python-hf/blob/main/results_2023-09-17T22-02-41.600326.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190325, "f1": 0.0019200922818791944, "f1_stderr": 0.0004138356823487018, "acc": 0.3307024467245462, "acc_stderr": 0.006650084932921209 }, "harness|drop|3": { "em": 0.0012583892617449664, "em_stderr": 0.00036305608931190325, "f1": 0.0019200922818791944, "f1_stderr": 0.0004138356823487018 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness|winogrande|5": { "acc": 0.6614048934490924, "acc_stderr": 0.013300169865842417 } } ``` ### 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]

erfanzar/UltraChat-Mini

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: dialog sequence: string - name: user sequence: string - name: assistant sequence: string - name: system dtype: string - name: id dtype: int64 - name: llama2_prompt dtype: string splits: - name: train num_bytes: 6005323184 num_examples: 239641 download_size: 2964129142 dataset_size: 6005323184 --- # Dataset Card for "UltraChat-Mini" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

adityarra07/test_ds_uwb_atc_noise_trial

--- dataset_info: features: - name: audio struct: - name: array sequence: float32 - name: path dtype: 'null' - name: sampling_rate dtype: int64 - name: transcription dtype: string - name: id dtype: string splits: - name: train num_bytes: 684273363.9015728 num_examples: 3000 - name: test num_bytes: 22809112.13005243 num_examples: 100 download_size: 709812743 dataset_size: 707082476.0316253 --- # Dataset Card for "test_ds_uwb_atc_noise_trial" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

enoahjr/twitter_dataset_1713189012

--- 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: 992034 num_examples: 2929 download_size: 542763 dataset_size: 992034 configs: - config_name: default data_files: - split: train path: data/train-* ---

liuyanchen1015/VALUE_mrpc_lexical

--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: test num_bytes: 402763 num_examples: 1493 - name: train num_bytes: 849076 num_examples: 3134 - name: validation num_bytes: 97832 num_examples: 360 download_size: 921493 dataset_size: 1349671 --- # Dataset Card for "VALUE_mrpc_lexical" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Areeb123/drug_reviews

--- license: mit task_categories: - text-classification language: - en tags: - medical size_categories: - 1M<n<10M ---

aintech/vdf_wolt_food

--- tags: - vdf - vector-io - vector-dataset - vector-embeddings --- This is a dataset created using [vector-io](https://github.com/ai-northstar-tech/vector-io)

tramzel/fndds

--- license: unknown ---

RuudVelo/my_awesome_new_bike

--- license: apache-2.0 dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 29796713.0 num_examples: 10 download_size: 26771158 dataset_size: 29796713.0 ---

betterMateusz/SAT_Writting_Reading_Assessment_Question_Bank

--- language: - en license: mit dataset_info: features: - name: id dtype: string - name: passage dtype: string - name: question dtype: string - name: choice_A dtype: string - name: choice_B dtype: string - name: choice_C dtype: string - name: choice_D dtype: string - name: correct_answer dtype: string - name: rationale dtype: string - name: difficulty dtype: string - name: domain dtype: string splits: - name: train num_bytes: 706258.0 num_examples: 397 download_size: 346011 dataset_size: 706258.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for SAT Reading and Writing Dataset This dataset card aims to be a base template for the SAT Reading and Writing Dataset, optimized for use with Hugging Face's datasets library. ## Dataset Details ### Dataset Description This dataset contains SAT Reading and Writing assessment questions sourced from the College Board's SAT Suite Question Bank, intended for use in training and evaluating Language Models like LLMs. - **Curated by:** College Board - **License:** Creative Commons Attribution-ShareAlike 4.0 International License ### Dataset Sources - **Repository:** [College Board SAT Suite Question Bank](https://satsuitequestionbank.collegeboard.org/) ## Uses ### Direct Use The dataset can be used for SAT exam preparation and educational purposes. It is suitable for training and evaluating Language Models for SAT-style reading comprehension and writing tasks. ## Dataset Structure The dataset contains questions with passages, choices, correct answers, and rationales, making it ideal for training and evaluating Language Models on SAT-style reading comprehension and writing tasks. ## Dataset Creation ### Curation Rationale The dataset was created to provide a resource for students preparing for the SAT exam and for researchers and developers working on Natural Language Processing tasks related to standardized testing. ### Source Data #### Data Collection and Processing The questions were extracted from the College Board SAT Suite Question Bank using automated scraping and filtering processes. #### Who are the source data producers? The College Board is the producer of the source data. ## Bias, Risks, and Limitations Users should be aware of the limitations of using this dataset for predicting SAT scores and should use it in conjunction with other resources for a comprehensive SAT preparation. ### Recommendations Users should use this dataset as a supplementary resource for SAT exam preparation and as a benchmark for evaluating the performance of Language Models on SAT-style reading comprehension and writing tasks. ## Citation **APA:** College Board. SAT Reading and Writing Dataset. Retrieved from [College Board SAT Suite Question Bank](https://satsuitequestionbank.collegeboard.org/)

YBXL/JAMA_Reasoning_test_Rare_test

--- dataset_info: features: - name: id dtype: string - name: query dtype: string - name: answer dtype: string splits: - name: train num_bytes: 334270 num_examples: 250 - name: valid num_bytes: 334270 num_examples: 250 - name: test num_bytes: 334270 num_examples: 250 download_size: 474801 dataset_size: 1002810 configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* ---

jlbaker361/actstu-dream-50

--- dataset_info: features: - name: image dtype: image - name: prompt dtype: string - name: seed dtype: int64 - name: steps dtype: int64 splits: - name: train num_bytes: 29844939.0 num_examples: 28 download_size: 29847370 dataset_size: 29844939.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

halaction/atm-data-transformers

--- license: openrail ---

allenai/ms2_dense_max

--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - apache-2.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - extended|other-MS^2 - extended|other-Cochrane task_categories: - summarization - text2text-generation paperswithcode_id: multi-document-summarization pretty_name: MSLR Shared Task --- This is a copy of the [MS^2](https://huggingface.co/datasets/allenai/mslr2022) dataset, except the input source documents of its `validation` split have been replaced by a __dense__ retriever. The retrieval pipeline used: - __query__: The `background` field of each example - __corpus__: The union of all documents in the `train`, `validation` and `test` splits. A document is the concatenation of the `title` and `abstract`. - __retriever__: [`facebook/contriever-msmarco`](https://huggingface.co/facebook/contriever-msmarco) via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) with default settings - __top-k strategy__: `"max"`, i.e. the number of documents retrieved, `k`, is set as the maximum number of documents seen across examples in this dataset, in this case `k==25` Retrieval results on the `train` set: | Recall@100 | Rprec | Precision@k | Recall@k | | ----------- | ----------- | ----------- | ----------- | | 0.4764 | 0.2395 | 0.1932 | 0.2895 | Retrieval results on the `validation` set: | Recall@100 | Rprec | Precision@k | Recall@k | | ----------- | ----------- | ----------- | ----------- | | 0.4364 | 0.2125 | 0.1823 | 0.2524 | Retrieval results on the `test` set: | Recall@100 | Rprec | Precision@k | Recall@k | | ----------- | ----------- | ----------- | ----------- | | 0.4481 | 0.2224 | 0.1943 | 0.2567 |

ParallelnoMinded/promo_squad_ru

--- license: apache-2.0 ---

kailasv/ArtWhisperer

--- license: mit configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: user_id dtype: string - name: target_id dtype: string - name: target_image dtype: image - name: target_positive_prompt dtype: string - name: target_negative_prompt dtype: string - name: target_image_embedding sequence: - name: value dtype: float32 - name: target_positive_text_embedding sequence: - name: value dtype: float32 - name: target_negative_text_embedding sequence: - name: value dtype: float32 - name: Famous person? dtype: bool - name: Famous landmark? dtype: bool - name: Manmade? dtype: bool - name: People? dtype: bool - name: Real image? dtype: bool - name: AI image? dtype: bool - name: Art? dtype: bool - name: Nature? dtype: bool - name: City? dtype: bool - name: Fantasy? dtype: bool - name: Sci-fi or space? dtype: bool - name: generated_image dtype: image - name: generated_positive_prompt dtype: string - name: generated_negative_prompt dtype: string - name: generated_image_embedding sequence: - name: value dtype: float32 - name: generated_positive_text_embedding sequence: - name: value dtype: float32 - name: generated_negative_text_embedding sequence: - name: value dtype: float32 - name: ai_model_name dtype: string - name: trajectory_index dtype: int32 - name: score dtype: int32 - name: human_rating dtype: float32 - name: time_taken dtype: duration[s] - name: filtered_image dtype: bool splits: - name: train num_bytes: 5743017316.686 num_examples: 51026 - name: validation num_bytes: 475257048.94 num_examples: 4572 download_size: 2185134483 dataset_size: 6218274365.625999 ---

A2H0H0R1/Animal-nutrition-pair

--- dataset_info: features: - name: question dtype: string - name: response_j dtype: string - name: response_k dtype: string splits: - name: train num_bytes: 10252777 num_examples: 5027 download_size: 4012629 dataset_size: 10252777 configs: - config_name: default data_files: - split: train path: data/train-* ---

blanchon/FAIR1M_Small_Caption

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 5528315890.896 num_examples: 22312 download_size: 5560660833 dataset_size: 5528315890.896 configs: - config_name: default data_files: - split: train path: data/train-* ---

sdmattpotter/hftest61223

--- license: mit ---

DjSteker/dataset_ham_spam

--- dataset_info: features: - name: IsSpam struct: - name: '0' dtype: string - name: Text struct: - name: '0' dtype: string splits: - name: train num_bytes: 385 num_examples: 1 download_size: 3829 dataset_size: 385 configs: - config_name: default data_files: - split: train path: data/train-* ---

ziozzang/deepl-trans-IT-KO

--- task_categories: - translation language: - ko - it --- This dataset is some wikipedia article with DeepL translation, auto-aggregated. # String/Corpus pairs From IT/Italian to KO/Korean. # Quality Filtering - Stripping whole HTML tags. - removed references and annotation mark. - Filtered by string length. --- The strings/corpus are aggregated from wikipedia(pt) using DeepL translated. whole data collected by Jioh L. Jung<ziozzang@gmail.com> license: mit ---

M-A-D/Mixed-Arabic-Dataset-Main

--- language: - ar task_categories: - conversational - text-generation - text2text-generation - translation - summarization pretty_name: MAD configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: GenId dtype: int64 - name: SubId dtype: int64 - name: DatasetName dtype: string - name: DatasetLink dtype: string - name: Text dtype: string - name: MetaData struct: - name: AboutAuthor dtype: string - name: AboutBook dtype: string - name: Author dtype: string - name: AuthorName dtype: string - name: BookLink dtype: string - name: BookName dtype: string - name: ChapterLink dtype: string - name: ChapterName dtype: string - name: Tags dtype: float64 - name: __index_level_0__ dtype: float64 - name: created_date dtype: string - name: deleted dtype: bool - name: detoxify dtype: 'null' - name: emojis struct: - name: count sequence: int32 - name: name sequence: string - name: id dtype: string - name: labels struct: - name: count sequence: int32 - name: name sequence: string - name: value sequence: float64 - name: lang dtype: string - name: message_id dtype: string - name: message_tree_id dtype: string - name: model_name dtype: 'null' - name: parent_id dtype: string - name: query_id dtype: string - name: rank dtype: float64 - name: review_count dtype: float64 - name: review_result dtype: bool - name: role dtype: string - name: synthetic dtype: bool - name: title dtype: string - name: tree_state dtype: string - name: url dtype: string - name: user_id dtype: string - name: ConcatenatedText dtype: int64 - name: __index_level_0__ dtype: float64 splits: - name: train num_bytes: 1990497610 num_examples: 131393 download_size: 790648134 dataset_size: 1990497610 --- # Dataset Card for "Mixed-Arabic-Dataset" ## Mixed Arabic Datasets (MAD) The Mixed Arabic Datasets (MAD) project provides a comprehensive collection of diverse Arabic-language datasets, sourced from various repositories, platforms, and domains. These datasets cover a wide range of text types, including books, articles, Wikipedia content, stories, and more. ### MAD Repo vs. MAD Main #### MAD Repo - **Versatility**: In the MAD Repository (MAD Repo), datasets are made available in their original, native form. Researchers and practitioners can selectively download specific datasets that align with their specific interests or requirements. - **Independent Access**: Each dataset is self-contained, enabling users to work with individual datasets independently, allowing for focused analyses and experiments. #### MAD Main or simply MAD - **Unified Dataframe**: MAD Main represents a harmonized and unified dataframe, incorporating all datasets from the MAD Repository. It provides a seamless and consolidated view of the entire MAD collection, making it convenient for comprehensive analyses and applications. - **Holistic Perspective**: Researchers can access a broad spectrum of Arabic-language content within a single dataframe, promoting holistic exploration and insights across diverse text sources. ### Why MAD Main? - **Efficiency**: Working with MAD Main streamlines the data acquisition process by consolidating multiple datasets into one structured dataframe. This is particularly beneficial for large-scale projects or studies requiring diverse data sources. - **Interoperability**: With MAD Main, the datasets are integrated into a standardized format, enhancing interoperability and compatibility with a wide range of data processing and analysis tools. - **Meta-Analysis**: Researchers can conduct comprehensive analyses, such as cross-domain studies, trend analyses, or comparative studies, by leveraging the combined richness of all MAD datasets. ### Getting Started - To access individual datasets in their original form, refer to the MAD Repository ([Link to MAD Repo](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo)). - For a unified view of all datasets, conveniently organized in a dataframe, you are here in the right place. ```python from datasets import load_dataset dataset = load_dataset("M-A-D/Mixed-Arabic-Dataset-Main") ``` ### Join Us on Discord For discussions, contributions, and community interactions, join us on Discord! [![Discord](https://img.shields.io/discord/798499298231726101?label=Join%20us%20on%20Discord&logo=discord&logoColor=white&style=for-the-badge)](https://discord.gg/2NpJ9JGm) ### How to Contribute Want to contribute to the Mixed Arabic Datasets project? Follow our comprehensive guide on Google Colab for step-by-step instructions: [Contribution Guide](https://colab.research.google.com/drive/1w7_7lL6w7nM9DcDmTZe1Vfiwkio6SA-w?usp=sharing). **Note**: If you'd like to test a contribution before submitting it, feel free to do so on the [MAD Test Dataset](https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Dataset-test). ## Citation ``` @dataset{ title = {Mixed Arabic Datasets (MAD)}, author = {MAD Community}, howpublished = {Dataset}, url = {https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo}, year = {2023}, } ```

ImruQays/Alukah-Arabic

--- language: - ar license: cc-by-4.0 --- # Introduction This dataset is a comprehensive collection of articles sourced from the Alukah website, a renowned platform offering extensive content primarily in Arabic. Alukah is known for its high-quality Arabic prose, significantly surpassing the standard found in contemporary media outlets. The majority of the articles are contributed by Muslim scholars, encompassing a wide range of topics related to Islam and the Muslim community. The dataset also includes a valuable section on fatwas, which could be instrumental in developing question-answer datasets for Islamic jurisprudence. ## Dataset Details ### Dataset Description  - **Language(s) (NLP):** [Arabic, minor content in other languages] - **License:** [Refer to [Alukah terms of use](https://www.alukah.net/pages/terms_of_use.aspx)] ### Dataset Sources  - **Website:** [https://www.alukah.net/] ## Uses The Alukah Arabic Articles Collection is particularly suitable for training large language models (LLMs) in Arabic. It offers a refined variant of the language that stands in contrast to the more commonly found less sophisticated forms in modern media. This dataset is an invaluable resource for: - Language Model Training: Enriching LLMs with high-quality Arabic data, enhancing their understanding and generation capabilities in the language. - Islamic Content Analysis: Providing a rich source of Islamic scholarly articles for research and analysis in religious studies, cultural studies, and linguistics. - Historical and Cultural Research: The dataset can be used as a reference for studying the evolution of Arabic language usage in scholarly contexts. ## Dataset Structure The dataset is organized into 9 files, each representing a distinct section of the Alukah website. It is important to note the potential for duplicate articles across these files, as some topics may overlap. ## Quality of Arabic Writing While the articles on Alukah showcase a superior level of Arabic compared to contemporary writings, it's important to acknowledge that even these articles may not fully match the exemplary standards of classical Arabic literature. For enthusiasts and researchers aiming to explore the pinnacle of Arabic literary excellence, it is recommended to refer to works that are over 200 years old or consult the book "العرنجية" for further insights into the nuances of high-quality Arabic prose.

ehcalabres/ravdess_speech

--- annotations_creators: - no-annotation language_creators: - found language: - en license: - cc-by-nc-sa-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - audio-classification task_ids: - speech-emotion-recognition --- # Dataset Card for ravdess_speech ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - **Homepage:** [Needs More Information] - **Repository:** https://zenodo.org/record/1188976#.YUS4MrozZdS - **Paper:** https://doi.org/10.1371/journal.pone.0196391 - **Leaderboard:** [Needs More Information] - **Point of Contact:** ravdess@gmail.com ### Dataset Summary The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) contains 24 professional actors (12 female, 12 male), vocalizing two lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. The conditions of the audio files are: 16bit, 48kHz .wav. ### Supported Tasks and Leaderboards - audio-classification: The dataset can be used to train a model for Audio Classification tasks, which consists in predict the latent emotion presented on the audios. ### Languages The audios available in the dataset are in English spoken by actors in a neutral North American accent. ## Dataset Structure ### Data Instances [Needs More Information] ### Data Fields [Needs More Information] ### Data Splits [Needs More Information] ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information The RAVDESS is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, CC BY-NC-SA 4.0 Commercial licenses for the RAVDESS can also be purchased. For more information, please visit our license fee page, or contact us at ravdess@gmail.com. ### Citation Information Livingstone SR, Russo FA (2018) The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. PLoS ONE 13(5): e0196391. https://doi.org/10.1371/journal.pone.0196391.

CountFloyd/bark-german-semantic-wav-training

--- language: - de ---

AdapterOcean/data-standardized_cluster_23_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: 7951640 num_examples: 6750 download_size: 3438336 dataset_size: 7951640 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "data-standardized_cluster_23_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

indiejoseph/wikipedia-en-filtered

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 49741517 num_examples: 17260 download_size: 27011805 dataset_size: 49741517 language: - en --- # Dataset Card for "wikipedia-en-filtered" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

mask-distilled-one-sec-cv12/chunk_0

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1165136164 num_examples: 228817 download_size: 1184952464 dataset_size: 1165136164 --- # Dataset Card for "chunk_0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

PDBEurope/protein_chain_conformational_states

--- license: cc-by-4.0 language: - en size_categories: - 10K<n<100K task_categories: - feature-extraction tags: - Structural biology - Bioinformatics - Machine learning - Conformation - Conformational state - Monomeric - Training data - Benchmark - Manually curated pretty_name: Curated dataset of protein chain conformational states --- ## Schema description: The manually curated dataset of open-closed monomers is included here as `benchmarking_monomeric_open_closed_conformers.csv`. Column descriptions: ## Schema description: The manually curated dataset of open-closed monomers is included here as `benchmarking_monomeric_open_closed_conformers.csv`. Column descriptions: - **`UNP_ACC`** | UniProt accession code - **`UNP_START`** | Start of UniProt sequence for given PDBe entries - **`UNP_END`** | End of UniProt sequence for given PDBe entries - **`PDBe_ID`** | Protein Data Bank code - **`CHAIN_ID`** | Author declared chain ID (`char`) - **`label_asym_id`** | Programmatically assigned chain ID (`char`) - **`CONFORMER_ID`** | Unique code for PDBe entries with distinct conformation, corresponding to a given UniProt accession - **`CONFORMER_DESCR`** | Short description of conformation, based on depositor's assessment of the protein/conformation - **`LIT_CONFIRMED`** | True/false value based on whether a publication (scientific literature) was available for manually curating clusters. NB: Clusters with 0 in this field should be used with caution. - **`ALT_CONFORMER_ID`** | Where the publication for a structure is currently outstanding, an executive decision on the conformation classification is made. Where the literature is not explicit on the features of a given conformation, the second most suitable `CONFORMER_ID` is provided in this column. Blank cells have no other likely conformation assignmnt and are therefore the same as in `CONFORMER_ID`. - **`ALT_CONFORMER_DESCR`** | Description for conformation in alternative conformation ID. ## Curation process As of 09 Mar 2022, a manually curated dataset of monomeric protein conformations has been collated, containing 'open'-'closed' pairs as well as intermediary states defined by the authors of the entry. 1. The PDBe was queried, through its Oracle DB, to find PDBe entries with 100 % sequence identity for a UniProt segment in both 'open' and 'closed' conformations, as stated in the entry's `TITLE` field. The query used: ``` select b.accession, b.unp_start, b.unp_end, a.id, a.title, d.id, d.title from entry a, unp_entity b, unp_entity c, entry d, pdb_assembly e where a.title like ‘%open%’ and d.title like ‘%close%’ and a.id = b.entry_id and d.id = c.entry_id and a.id != d.id and b.accession = c.accession and b.unp_start = c.unp_start and b.unp_end = c.unp_end and a.id = e.entry_id and e.type = ‘homo’ and e.name = ‘monomer’ ``` was written by Dr Sameer Velankar. 2. These results were cleaned to remove entries with 'open' or 'close' substrings in their `TITLE` fields that did not refer to conformation. The 'open' substring often appeared in ligand names in the entries' `TITLE` field, such as in *dichlorido(1,3-dimethylbenzimidaz ol-2-ylidene)(eta5-pentamethylcycl**open**tadienyl)rhodium(III)* and 'close' in terms like *dis**close**s*. 3. All remaining entries were then manually curated by investigating each PDBe entry's corresponding publication, where available. 1. Additional PDBe entries submitted by the authors, which were missed in the original search due to a lack of 'open' or 'close' substrings in their `TITLE` field but stated as fitting one of the states in the publication, were added. 2. For some UniProt accessions, intermediary conformations were reported by the authors and these were noted in the dataset under the `CONFORMER_DESCR` column. 3. Entries deposited in monomeric form but solved as a multimeric complex were also removed. 4. PDBe entries, now clustered by author-stated conformation, were cross-referenced against the PDBe-KB's existing clustering algorithm (available on the [Aggregate Views of Proteins](https://www.ebi.ac.uk/pdbe/pdbe-kb/protein) page) to assess current conformer clustering success. These results are currently awaiting publication. ### Curation process outline <img src="http://ftp.ebi.ac.uk/pub/databases/pdbe-kb/benchmarking/distinct-monomer-conformers/work_progress_flowdiagram_200pc.png" alt="Curation flow diagram"> ### Dataset summary <img src="http://ftp.ebi.ac.uk/pub/databases/pdbe-kb/benchmarking/distinct-monomer-conformers/summary_data_visualisation.png" alt="Benchmark dataset summary graphs">

Back-up/facebook_comment_augmentation-v2

--- dataset_info: features: - name: id dtype: string - name: text dtype: string - name: hash dtype: int64 splits: - name: train num_bytes: 213595318.3206353 num_examples: 1328546 download_size: 119399417 dataset_size: 213595318.3206353 configs: - config_name: default data_files: - split: train path: data/train-* ---

Tohrumi/iwslt15_fuzzy_1000_train_samples

--- dataset_info: features: - name: id dtype: int64 - name: translation struct: - name: en dtype: string - name: vi dtype: string splits: - name: train num_bytes: 636042.8958904734 num_examples: 1000 - name: test num_bytes: 329197 num_examples: 1268 download_size: 574472 dataset_size: 965239.8958904734 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

anhtu12st/papers

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 45435 num_examples: 155 download_size: 28085 dataset_size: 45435 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "papers" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

japanese-asr/whisper_transcriptions.reazonspeech.all_22

--- dataset_info: config_name: all features: - name: name dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 30475531164.0 num_examples: 267733 download_size: 30239263328 dataset_size: 30475531164.0 configs: - config_name: all data_files: - split: train path: all/train-* ---

mlabonne/truthy-dpo-v0.1

--- language: - en dataset_info: features: - name: id dtype: string - name: source dtype: string - name: system dtype: string - name: question dtype: string - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 1344072 num_examples: 1016 download_size: 652993 dataset_size: 1344072 configs: - config_name: default data_files: - split: train path: data/train-* ---

fhaddad/autotrain-data-fhdd_arabic_chatbot

--- language: - en - ar task_categories: - translation --- # AutoTrain Dataset for project: fhdd_arabic_chatbot ## Dataset Description This dataset has been automatically processed by AutoTrain for project fhdd_arabic_chatbot. ### Languages The BCP-47 code for the dataset's language is en2ar. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_sourceLang": "ara", "feat_targetlang": "eng", "target": "\u064a\u0646\u0628\u063a\u064a \u0623\u0646 \u062a\u064f\u0638\u0647\u0631 \u0627\u0644\u0646\u0651\u0633\u0627\u0621 \u0648\u062c\u0648\u0647\u0647\u0646\u0651.", "source": "Women should have their faces visible." }, { "feat_sourceLang": "ara", "feat_targetlang": "eng", "target": "\u0623\u062a\u062f\u0631\u0633 \u0627\u0644\u0625\u0646\u062c\u0644\u064a\u0632\u064a\u0629\u061f", "source": "Do you study English?" } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_sourceLang": "Value(dtype='string', id=None)", "feat_targetlang": "Value(dtype='string', id=None)", "target": "Value(dtype='string', id=None)", "source": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 15622 | | valid | 3906 |

anan-2024/twitter_dataset_1713142048

--- 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: 192326 num_examples: 521 download_size: 106584 dataset_size: 192326 configs: - config_name: default data_files: - split: train path: data/train-* ---

datasets-examples/doc-formats-csv-3

--- configs: - config_name: default data_files: "data.csv" delimiter: "|" header: 1 names: ["kind", "sound"] size_categories: - n<1K --- # [doc] formats - csv - 3 This dataset contains one csv file at the root: - [data.csv](./data.csv) ```csv # ignored comment col1|col2 dog|woof cat|meow pokemon|pika human|hello ``` We define the config name in the YAML config, as well as the exact location of the file, the separator as `"|"`, the name of the columns, and the number of rows to ignore (the row #1 is a row of column headers, that will be replaced by the `names` option, and the row #0 is ignored). The reference for the options is the [documentation of pandas.read_csv()](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html). ```yaml --- configs: - config_name: default data_files: "data.csv" delimiter: "|" header: 1 names: ["kind", "sound"] size_categories: - n<1K --- ```

fathyshalab/massive_social-de-DE

--- dataset_info: features: - name: id dtype: string - name: locale dtype: string - name: partition dtype: string - name: scenario dtype: class_label: names: '0': social '1': transport '2': calendar '3': play '4': news '5': datetime '6': recommendation '7': email '8': iot '9': general '10': audio '11': lists '12': qa '13': cooking '14': takeaway '15': music '16': alarm '17': weather - name: intent dtype: class_label: names: '0': datetime_query '1': iot_hue_lightchange '2': transport_ticket '3': takeaway_query '4': qa_stock '5': general_greet '6': recommendation_events '7': music_dislikeness '8': iot_wemo_off '9': cooking_recipe '10': qa_currency '11': transport_traffic '12': general_quirky '13': weather_query '14': audio_volume_up '15': email_addcontact '16': takeaway_order '17': email_querycontact '18': iot_hue_lightup '19': recommendation_locations '20': play_audiobook '21': lists_createoradd '22': news_query '23': alarm_query '24': iot_wemo_on '25': general_joke '26': qa_definition '27': social_query '28': music_settings '29': audio_volume_other '30': calendar_remove '31': iot_hue_lightdim '32': calendar_query '33': email_sendemail '34': iot_cleaning '35': audio_volume_down '36': play_radio '37': cooking_query '38': datetime_convert '39': qa_maths '40': iot_hue_lightoff '41': iot_hue_lighton '42': transport_query '43': music_likeness '44': email_query '45': play_music '46': audio_volume_mute '47': social_post '48': alarm_set '49': qa_factoid '50': calendar_set '51': play_game '52': alarm_remove '53': lists_remove '54': transport_taxi '55': recommendation_movies '56': iot_coffee '57': music_query '58': play_podcasts '59': lists_query - name: text dtype: string - name: annot_utt dtype: string - name: worker_id dtype: string - name: slot_method sequence: - name: slot dtype: string - name: method dtype: string - name: judgments sequence: - name: worker_id dtype: string - name: intent_score dtype: int8 - name: slots_score dtype: int8 - name: grammar_score dtype: int8 - name: spelling_score dtype: int8 - name: language_identification dtype: string - name: label_name dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 129790 num_examples: 391 - name: validation num_bytes: 22472 num_examples: 68 - name: test num_bytes: 34107 num_examples: 106 download_size: 70328 dataset_size: 186369 --- # Dataset Card for "massive_social-de-DE" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

316usman/thematic2aembed

--- license: bsd dataset_info: features: - name: text dtype: string - name: thematic dtype: string - name: sub-thematic dtype: string - name: country dtype: string - name: document_url dtype: string - name: source_url dtype: string splits: - name: train num_bytes: 691745022 num_examples: 908625 download_size: 205106568 dataset_size: 691745022 configs: - config_name: default data_files: - split: train path: data/train-* ---

gilsonk12/Rastreando

--- license: openrail ---

shreyasharma/sentence_eval_aa2

--- dataset_info: features: - name: declarativized dtype: string - name: correct dtype: bool splits: - name: train num_bytes: 35463 num_examples: 615 - name: validation num_bytes: 18279 num_examples: 315 - name: test num_bytes: 17185 num_examples: 300 download_size: 56380 dataset_size: 70927 --- # Dataset Card for "sentence_eval_aa2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

RikeshSilwal/nepali_corpora

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1725683703 num_examples: 3253409 download_size: 496020433 dataset_size: 1725683703 configs: - config_name: default data_files: - split: train path: data/train-* ---

yankihue/tweets-turkish

--- language: - tr ---

taspecustu/Nanachi

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

ikala/tmmluplus

--- license: other license_name: creative-commons-by-nc task_categories: - question-answering language: - zh tags: - traditional chinese - finance - medical - taiwan - benchmark - zh-tw - zh-hant pretty_name: tmmlu++ size_categories: - 100K<n<1M configs: - config_name: engineering_math data_files: - split: train path: "data/engineering_math_dev.csv" - split: validation path: "data/engineering_math_val.csv" - split: test path: "data/engineering_math_test.csv" - config_name: dentistry data_files: - split: train path: "data/dentistry_dev.csv" - split: validation path: "data/dentistry_val.csv" - split: test path: "data/dentistry_test.csv" - config_name: traditional_chinese_medicine_clinical_medicine data_files: - split: train path: "data/traditional_chinese_medicine_clinical_medicine_dev.csv" - split: validation path: "data/traditional_chinese_medicine_clinical_medicine_val.csv" - split: test path: "data/traditional_chinese_medicine_clinical_medicine_test.csv" - config_name: clinical_psychology data_files: - split: train path: "data/clinical_psychology_dev.csv" - split: validation path: "data/clinical_psychology_val.csv" - split: test path: "data/clinical_psychology_test.csv" - config_name: technical data_files: - split: train path: "data/technical_dev.csv" - split: validation path: "data/technical_val.csv" - split: test path: "data/technical_test.csv" - config_name: culinary_skills data_files: - split: train path: "data/culinary_skills_dev.csv" - split: validation path: "data/culinary_skills_val.csv" - split: test path: "data/culinary_skills_test.csv" - config_name: mechanical data_files: - split: train path: "data/mechanical_dev.csv" - split: validation path: "data/mechanical_val.csv" - split: test path: "data/mechanical_test.csv" - config_name: logic_reasoning data_files: - split: train path: "data/logic_reasoning_dev.csv" - split: validation path: "data/logic_reasoning_val.csv" - split: test path: "data/logic_reasoning_test.csv" - config_name: real_estate data_files: - split: train path: "data/real_estate_dev.csv" - split: validation path: "data/real_estate_val.csv" - split: test path: "data/real_estate_test.csv" - config_name: general_principles_of_law data_files: - split: train path: "data/general_principles_of_law_dev.csv" - split: validation path: "data/general_principles_of_law_val.csv" - split: test path: "data/general_principles_of_law_test.csv" - config_name: finance_banking data_files: - split: train path: "data/finance_banking_dev.csv" - split: validation path: "data/finance_banking_val.csv" - split: test path: "data/finance_banking_test.csv" - config_name: anti_money_laundering data_files: - split: train path: "data/anti_money_laundering_dev.csv" - split: validation path: "data/anti_money_laundering_val.csv" - split: test path: "data/anti_money_laundering_test.csv" - config_name: ttqav2 data_files: - split: train path: "data/ttqav2_dev.csv" - split: validation path: "data/ttqav2_val.csv" - split: test path: "data/ttqav2_test.csv" - config_name: marketing_management data_files: - split: train path: "data/marketing_management_dev.csv" - split: validation path: "data/marketing_management_val.csv" - split: test path: "data/marketing_management_test.csv" - config_name: business_management data_files: - split: train path: "data/business_management_dev.csv" - split: validation path: "data/business_management_val.csv" - split: test path: "data/business_management_test.csv" - config_name: organic_chemistry data_files: - split: train path: "data/organic_chemistry_dev.csv" - split: validation path: "data/organic_chemistry_val.csv" - split: test path: "data/organic_chemistry_test.csv" - config_name: advance_chemistry data_files: - split: train path: "data/advance_chemistry_dev.csv" - split: validation path: "data/advance_chemistry_val.csv" - split: test path: "data/advance_chemistry_test.csv" - config_name: physics data_files: - split: train path: "data/physics_dev.csv" - split: validation path: "data/physics_val.csv" - split: test path: "data/physics_test.csv" - config_name: secondary_physics data_files: - split: train path: "data/secondary_physics_dev.csv" - split: validation path: "data/secondary_physics_val.csv" - split: test path: "data/secondary_physics_test.csv" - config_name: human_behavior data_files: - split: train path: "data/human_behavior_dev.csv" - split: validation path: "data/human_behavior_val.csv" - split: test path: "data/human_behavior_test.csv" - config_name: national_protection data_files: - split: train path: "data/national_protection_dev.csv" - split: validation path: "data/national_protection_val.csv" - split: test path: "data/national_protection_test.csv" - config_name: jce_humanities data_files: - split: train path: "data/jce_humanities_dev.csv" - split: validation path: "data/jce_humanities_val.csv" - split: test path: "data/jce_humanities_test.csv" - config_name: politic_science data_files: - split: train path: "data/politic_science_dev.csv" - split: validation path: "data/politic_science_val.csv" - split: test path: "data/politic_science_test.csv" - config_name: agriculture data_files: - split: train path: "data/agriculture_dev.csv" - split: validation path: "data/agriculture_val.csv" - split: test path: "data/agriculture_test.csv" - config_name: official_document_management data_files: - split: train path: "data/official_document_management_dev.csv" - split: validation path: "data/official_document_management_val.csv" - split: test path: "data/official_document_management_test.csv" - config_name: financial_analysis data_files: - split: train path: "data/financial_analysis_dev.csv" - split: validation path: "data/financial_analysis_val.csv" - split: test path: "data/financial_analysis_test.csv" - config_name: pharmacy data_files: - split: train path: "data/pharmacy_dev.csv" - split: validation path: "data/pharmacy_val.csv" - split: test path: "data/pharmacy_test.csv" - config_name: educational_psychology data_files: - split: train path: "data/educational_psychology_dev.csv" - split: validation path: "data/educational_psychology_val.csv" - split: test path: "data/educational_psychology_test.csv" - config_name: statistics_and_machine_learning data_files: - split: train path: "data/statistics_and_machine_learning_dev.csv" - split: validation path: "data/statistics_and_machine_learning_val.csv" - split: test path: "data/statistics_and_machine_learning_test.csv" - config_name: management_accounting data_files: - split: train path: "data/management_accounting_dev.csv" - split: validation path: "data/management_accounting_val.csv" - split: test path: "data/management_accounting_test.csv" - config_name: introduction_to_law data_files: - split: train path: "data/introduction_to_law_dev.csv" - split: validation path: "data/introduction_to_law_val.csv" - split: test path: "data/introduction_to_law_test.csv" - config_name: computer_science data_files: - split: train path: "data/computer_science_dev.csv" - split: validation path: "data/computer_science_val.csv" - split: test path: "data/computer_science_test.csv" - config_name: veterinary_pathology data_files: - split: train path: "data/veterinary_pathology_dev.csv" - split: validation path: "data/veterinary_pathology_val.csv" - split: test path: "data/veterinary_pathology_test.csv" - config_name: accounting data_files: - split: train path: "data/accounting_dev.csv" - split: validation path: "data/accounting_val.csv" - split: test path: "data/accounting_test.csv" - config_name: fire_science data_files: - split: train path: "data/fire_science_dev.csv" - split: validation path: "data/fire_science_val.csv" - split: test path: "data/fire_science_test.csv" - config_name: optometry data_files: - split: train path: "data/optometry_dev.csv" - split: validation path: "data/optometry_val.csv" - split: test path: "data/optometry_test.csv" - config_name: insurance_studies data_files: - split: train path: "data/insurance_studies_dev.csv" - split: validation path: "data/insurance_studies_val.csv" - split: test path: "data/insurance_studies_test.csv" - config_name: pharmacology data_files: - split: train path: "data/pharmacology_dev.csv" - split: validation path: "data/pharmacology_val.csv" - split: test path: "data/pharmacology_test.csv" - config_name: taxation data_files: - split: train path: "data/taxation_dev.csv" - split: validation path: "data/taxation_val.csv" - split: test path: "data/taxation_test.csv" - config_name: trust_practice data_files: - split: train path: "data/trust_practice_dev.csv" - split: validation path: "data/trust_practice_val.csv" - split: test path: "data/trust_practice_test.csv" - config_name: geography_of_taiwan data_files: - split: train path: "data/geography_of_taiwan_dev.csv" - split: validation path: "data/geography_of_taiwan_val.csv" - split: test path: "data/geography_of_taiwan_test.csv" - config_name: physical_education data_files: - split: train path: "data/physical_education_dev.csv" - split: validation path: "data/physical_education_val.csv" - split: test path: "data/physical_education_test.csv" - config_name: auditing data_files: - split: train path: "data/auditing_dev.csv" - split: validation path: "data/auditing_val.csv" - split: test path: "data/auditing_test.csv" - config_name: administrative_law data_files: - split: train path: "data/administrative_law_dev.csv" - split: validation path: "data/administrative_law_val.csv" - split: test path: "data/administrative_law_test.csv" - config_name: education_(profession_level) data_files: - split: train path: "data/education_(profession_level)_dev.csv" - split: validation path: "data/education_(profession_level)_val.csv" - split: test path: "data/education_(profession_level)_test.csv" - config_name: economics data_files: - split: train path: "data/economics_dev.csv" - split: validation path: "data/economics_val.csv" - split: test path: "data/economics_test.csv" - config_name: veterinary_pharmacology data_files: - split: train path: "data/veterinary_pharmacology_dev.csv" - split: validation path: "data/veterinary_pharmacology_val.csv" - split: test path: "data/veterinary_pharmacology_test.csv" - config_name: nautical_science data_files: - split: train path: "data/nautical_science_dev.csv" - split: validation path: "data/nautical_science_val.csv" - split: test path: "data/nautical_science_test.csv" - config_name: occupational_therapy_for_psychological_disorders data_files: - split: train path: "data/occupational_therapy_for_psychological_disorders_dev.csv" - split: validation path: "data/occupational_therapy_for_psychological_disorders_val.csv" - split: test path: "data/occupational_therapy_for_psychological_disorders_test.csv" - config_name: basic_medical_science data_files: - split: train path: "data/basic_medical_science_dev.csv" - split: validation path: "data/basic_medical_science_val.csv" - split: test path: "data/basic_medical_science_test.csv" - config_name: macroeconomics data_files: - split: train path: "data/macroeconomics_dev.csv" - split: validation path: "data/macroeconomics_val.csv" - split: test path: "data/macroeconomics_test.csv" - config_name: trade data_files: - split: train path: "data/trade_dev.csv" - split: validation path: "data/trade_val.csv" - split: test path: "data/trade_test.csv" - config_name: chinese_language_and_literature data_files: - split: train path: "data/chinese_language_and_literature_dev.csv" - split: validation path: "data/chinese_language_and_literature_val.csv" - split: test path: "data/chinese_language_and_literature_test.csv" - config_name: tve_design data_files: - split: train path: "data/tve_design_dev.csv" - split: validation path: "data/tve_design_val.csv" - split: test path: "data/tve_design_test.csv" - config_name: junior_science_exam data_files: - split: train path: "data/junior_science_exam_dev.csv" - split: validation path: "data/junior_science_exam_val.csv" - split: test path: "data/junior_science_exam_test.csv" - config_name: junior_math_exam data_files: - split: train path: "data/junior_math_exam_dev.csv" - split: validation path: "data/junior_math_exam_val.csv" - split: test path: "data/junior_math_exam_test.csv" - config_name: junior_chinese_exam data_files: - split: train path: "data/junior_chinese_exam_dev.csv" - split: validation path: "data/junior_chinese_exam_val.csv" - split: test path: "data/junior_chinese_exam_test.csv" - config_name: junior_social_studies data_files: - split: train path: "data/junior_social_studies_dev.csv" - split: validation path: "data/junior_social_studies_val.csv" - split: test path: "data/junior_social_studies_test.csv" - config_name: tve_mathematics data_files: - split: train path: "data/tve_mathematics_dev.csv" - split: validation path: "data/tve_mathematics_val.csv" - split: test path: "data/tve_mathematics_test.csv" - config_name: tve_chinese_language data_files: - split: train path: "data/tve_chinese_language_dev.csv" - split: validation path: "data/tve_chinese_language_val.csv" - split: test path: "data/tve_chinese_language_test.csv" - config_name: tve_natural_sciences data_files: - split: train path: "data/tve_natural_sciences_dev.csv" - split: validation path: "data/tve_natural_sciences_val.csv" - split: test path: "data/tve_natural_sciences_test.csv" - config_name: junior_chemistry data_files: - split: train path: "data/junior_chemistry_dev.csv" - split: validation path: "data/junior_chemistry_val.csv" - split: test path: "data/junior_chemistry_test.csv" - config_name: music data_files: - split: train path: "data/music_dev.csv" - split: validation path: "data/music_val.csv" - split: test path: "data/music_test.csv" - config_name: education data_files: - split: train path: "data/education_dev.csv" - split: validation path: "data/education_val.csv" - split: test path: "data/education_test.csv" - config_name: three_principles_of_people data_files: - split: train path: "data/three_principles_of_people_dev.csv" - split: validation path: "data/three_principles_of_people_val.csv" - split: test path: "data/three_principles_of_people_test.csv" - config_name: taiwanese_hokkien data_files: - split: train path: "data/taiwanese_hokkien_dev.csv" - split: validation path: "data/taiwanese_hokkien_val.csv" - split: test path: "data/taiwanese_hokkien_test.csv" --- # TMMLU+ : Large scale traditional chinese massive multitask language understanding <p align="center"> <img src="https://huggingface.co/datasets/ikala/tmmluplus/resolve/main/cover.png" alt="A close-up image of a neat paper note with a white background. The text 'TMMLU+' is written horizontally across the center of the note in bold, black. Join us to work in multimodal LLM : https://ikala.ai/recruit/" style="max-width: 400" width=400 /> </p> We present TMMLU+, a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset featuring 66 subjects, ranging from elementary to professional level. The TMMLU+ dataset is six times larger and contains more balanced subjects compared to its predecessor, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We have included benchmark results in TMMLU+ from closed-source models and 20 open-weight Chinese large language models, with parameters ranging from 1.8B to 72B. The benchmark results show that Traditional Chinese variants still lag behind those trained on major Simplified Chinese models. ```python from datasets import load_dataset task_list = [ 'engineering_math', 'dentistry', 'traditional_chinese_medicine_clinical_medicine', 'clinical_psychology', 'technical', 'culinary_skills', 'mechanical', 'logic_reasoning', 'real_estate', 'general_principles_of_law', 'finance_banking', 'anti_money_laundering', 'ttqav2', 'marketing_management', 'business_management', 'organic_chemistry', 'advance_chemistry', 'physics', 'secondary_physics', 'human_behavior', 'national_protection', 'jce_humanities', 'politic_science', 'agriculture', 'official_document_management', 'financial_analysis', 'pharmacy', 'educational_psychology', 'statistics_and_machine_learning', 'management_accounting', 'introduction_to_law', 'computer_science', 'veterinary_pathology', 'accounting', 'fire_science', 'optometry', 'insurance_studies', 'pharmacology', 'taxation', 'trust_practice', 'geography_of_taiwan', 'physical_education', 'auditing', 'administrative_law', 'education_(profession_level)', 'economics', 'veterinary_pharmacology', 'nautical_science', 'occupational_therapy_for_psychological_disorders', 'basic_medical_science', 'macroeconomics', 'trade', 'chinese_language_and_literature', 'tve_design', 'junior_science_exam', 'junior_math_exam', 'junior_chinese_exam', 'junior_social_studies', 'tve_mathematics', 'tve_chinese_language', 'tve_natural_sciences', 'junior_chemistry', 'music', 'education', 'three_principles_of_people', 'taiwanese_hokkien' ] for task in task_list: val = load_dataset('ikala/tmmluplus', task)['validation'] dev = load_dataset('ikala/tmmluplus', task)['train'] test = load_dataset('ikala/tmmluplus', task)['test'] ``` For each dataset split ```python for row in test: print(row) break >> Dataset({ features: ['question', 'A', 'B', 'C', 'D', 'answer'], num_rows: 11 }) ``` Statistic on all four categories : STEM, Social Science, Humanities, Other | Category | Test | Dev | Validation | |----------------------------------|-------|------|------------| | STEM | 3458 | 70 | 385 | | Social Sciences | 5958 | 90 | 665 | | Humanities | 1763 | 35 | 197 | | Other (Business, Health, Misc.) | 8939 | 135 | 995 | | **Total** | 20118 | 330 | 2242 | ## Benchmark on direct prompting | model | STEM | Social Science | Humanities | Other | Average | |------------|------------|------------|------------|------------|------------| | [Qwen/Qwen-72B](https://huggingface.co/Qwen/Qwen-72B) | 61.12 | 71.65 | 63.00 | 61.31 |64.27| | gpt-4-0613 | 60.36 | 67.36 | 56.03 | 57.62 |60.34| | [Qwen/Qwen-72B-Chat](https://huggingface.co/Qwen/Qwen-72B-Chat) | 55.15 | 66.20 | 55.65 | 57.19 |58.55| | [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) | 46.94 | 56.69 | 49.43 | 48.81 |50.47| | Gemini-pro | 45.38 | 57.29 | 48.80 | 48.21 |49.92| | [01-ai/Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat) | 40.24 | 56.77 | 53.99 | 47.58 |49.64| | [Qwen/Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat) | 43.86 | 53.29 | 44.78 | 45.13 |46.77| | [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat) | 39.62 | 50.24 | 44.44 | 44.26 |44.64| | Claude-1.3 | 42.65 | 49.33 | 42.16 | 44.14 |44.57| | gpt-3.5-turbo-0613 | 41.56 | 46.72 | 36.73 | 42.03 |41.76| | [CausalLM/14B](https://huggingface.co/CausalLM/14B) | 39.83 | 44.50 | 39.61 | 41.97 |41.48| | [Skywork/Skywork-13B-base](https://huggingface.co/Skywork/Skywork-13B-base) | 36.93 | 47.27 | 41.04 | 40.10 |41.33| | [Qwen/Qwen-7B](https://huggingface.co/Qwen/Qwen-7B) | 37.53 | 45.48 | 38.09 | 38.96 |40.01| | [Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) | 33.32 | 44.64 | 40.27 | 39.89 |39.53| | [vivo-ai/BlueLM-7B-Base](https://huggingface.co/vivo-ai/BlueLM-7B-Base) | 33.94 | 41.52 | 37.38 | 38.74 |37.90| | [baichuan-inc/Baichuan2-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat) | 29.64 | 43.73 | 37.36 | 39.88 |37.65| | [Qwen/Qwen-1_8B](https://huggingface.co/Qwen/Qwen-1_8B) | 32.65 | 38.95 | 38.34 | 35.27 |36.30| | Claude-2 | 39.65 | 39.09 | 28.59 | 37.47 |36.20| | [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) | 31.05 | 39.31 | 35.64 | 35.60 |35.40| | [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat) | 29.82 | 42.29 | 34.24 | 34.31 |35.17| | [CausalLM/7B](https://huggingface.co/CausalLM/7B) | 31.03 | 38.17 | 35.87 | 35.39 |35.11| | [Azure99/blossom-v3_1-mistral-7b](https://huggingface.co/Azure99/blossom-v3_1-mistral-7b) | 32.80 | 36.91 | 32.36 | 34.53 |34.15| | [microsoft/Orca-2-13b](https://huggingface.co/microsoft/Orca-2-13b) | 24.69 | 39.18 | 33.60 | 31.99 |32.37| | [Qwen/Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat) | 26.60 | 36.36 | 31.81 | 31.96 |31.68| | [TigerResearch/tigerbot-13b-chat-v3](https://huggingface.co/TigerResearch/tigerbot-13b-chat-v3) | 24.73 | 29.63 | 25.72 | 27.22 |26.82| | [hongyin/mistral-7b-80k](https://huggingface.co/hongyin/mistral-7b-80k) | 24.26 | 23.76 | 22.56 | 24.57 |23.79| | [deepseek-ai/deepseek-llm-67b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat) | 19.10 | 26.06 | 21.51 | 21.77 |22.11| | [yentinglin/Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) | 18.53 | 27.65 | 17.77 | 21.49 |21.36| | [GeneZC/MiniChat-3B](https://huggingface.co/GeneZC/MiniChat-3B) | 17.66 | 23.35 | 22.71 | 20.34 |21.02| | [LinkSoul/Chinese-Llama-2-7b](https://huggingface.co/LinkSoul/Chinese-Llama-2-7b) | 16.55 | 18.39 | 12.97 | 16.13 |16.01| | [yentinglin/Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) | 14.99 | 16.23 | 15.00 | 16.22 |15.61| | Claude-instant-1 | 12.52 | 17.13 | 15.10 | 13.57 |14.58| | [FlagAlpha/Atom-7B](https://huggingface.co/FlagAlpha/Atom-7B) | 5.60 | 13.57 | 7.71 | 11.84 |9.68| Results via [ievals](https://github.com/iKala/ievals) ( settings : 0-shot direct answering ) # Citation ``` @article{ikala2024improved, title={An Improved Traditional Chinese Evaluation Suite for Foundation Model}, author={Tam, Zhi-Rui and Pai, Ya-Ting and Lee, Yen-Wei and Cheng, Sega and Shuai, Hong-Han}, journal={arXiv preprint arXiv:2403.01858}, year={2024} } ```

ealtan/MoodBooster

--- license: mit ---

kheopss/lettre_admin_f1.0_regenerated

--- dataset_info: features: - name: input dtype: string - name: response dtype: string - name: text dtype: string - name: text2 dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 4462522 num_examples: 697 download_size: 1690790 dataset_size: 4462522 configs: - config_name: default data_files: - split: train path: data/train-* ---

vitaliy-sharandin/pollution-krakow-no2-co

--- dataset_info: features: - name: NO2 dtype: float64 - name: CO dtype: float64 - name: dt dtype: timestamp[ns] splits: - name: train num_bytes: 6816 num_examples: 284 download_size: 9084 dataset_size: 6816 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "pollution-krakow-no2-co" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

natnitaract/SciBench-TruthfulQA-RAG

--- license: apache-2.0 task_categories: - multiple-choice ---

Falah/portrait_prompts

--- dataset_info: features: - name: prompts dtype: string splits: - name: train num_bytes: 22213518 num_examples: 100000 download_size: 2797158 dataset_size: 22213518 --- # Dataset Card for "portrait_prompts" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

MohammedNasri/163762AASRnoDiacs

--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 147266551704 num_examples: 153322 - name: test num_bytes: 10027423544 num_examples: 10440 download_size: 23754042731 dataset_size: 157293975248 --- # Dataset Card for "163762AASRnoDiacs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

rombodawg/code_instruct_alpaca_vicuna_wizardlm_56k_backup

--- license: other --- Backup of code_instruct_alpaca_vicuna_wizardlm used in rombodawg/MegaCodeTraining112k Link to the combined dataset bellow https://huggingface.co/datasets/rombodawg/MegaCodeTraining112k

open-llm-leaderboard/details_max-2022__test_mistral2

--- pretty_name: Evaluation run of max-2022/test_mistral2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [max-2022/test_mistral2](https://huggingface.co/max-2022/test_mistral2) 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_max-2022__test_mistral2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-11T22:17:01.815383](https://huggingface.co/datasets/open-llm-leaderboard/details_max-2022__test_mistral2/blob/main/results_2024-02-11T22-17-01.815383.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\": 0.24710575900369156,\n\ \ \"acc_stderr\": 0.03055560450787355,\n \"acc_norm\": 0.24800687316365916,\n\ \ \"acc_norm_stderr\": 0.0313664960522948,\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862666,\n \"mc2\": 0.490951583190258,\n\ \ \"mc2_stderr\": 0.016977888460336696\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.23037542662116042,\n \"acc_stderr\": 0.01230492841874761,\n\ \ \"acc_norm\": 0.2790102389078498,\n \"acc_norm_stderr\": 0.013106784883601338\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.2575184226249751,\n\ \ \"acc_stderr\": 0.004363736410689625,\n \"acc_norm\": 0.25323640709022105,\n\ \ \"acc_norm_stderr\": 0.004339764434219064\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036846,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n\ \ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.2074074074074074,\n\ \ \"acc_stderr\": 0.03502553170678318,\n \"acc_norm\": 0.2074074074074074,\n\ \ \"acc_norm_stderr\": 0.03502553170678318\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.03523807393012047,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.03523807393012047\n \ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.27,\n\ \ \"acc_stderr\": 0.0446196043338474,\n \"acc_norm\": 0.27,\n \ \ \"acc_norm_stderr\": 0.0446196043338474\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.23773584905660378,\n \"acc_stderr\": 0.0261998088075619,\n\ \ \"acc_norm\": 0.23773584905660378,\n \"acc_norm_stderr\": 0.0261998088075619\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2013888888888889,\n\ \ \"acc_stderr\": 0.033536474697138406,\n \"acc_norm\": 0.2013888888888889,\n\ \ \"acc_norm_stderr\": 0.033536474697138406\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\"\ : 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.24,\n\ \ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.24,\n \"acc_stderr\": 0.042923469599092816,\n \ \ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.042923469599092816\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.26011560693641617,\n\ \ \"acc_stderr\": 0.03345036916788991,\n \"acc_norm\": 0.26011560693641617,\n\ \ \"acc_norm_stderr\": 0.03345036916788991\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.04158307533083286,\n\ \ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.04158307533083286\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.3276595744680851,\n \"acc_stderr\": 0.03068302084323101,\n\ \ \"acc_norm\": 0.3276595744680851,\n \"acc_norm_stderr\": 0.03068302084323101\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\ \ \"acc_stderr\": 0.039994238792813344,\n \"acc_norm\": 0.23684210526315788,\n\ \ \"acc_norm_stderr\": 0.039994238792813344\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.2206896551724138,\n \"acc_stderr\": 0.03455930201924812,\n\ \ \"acc_norm\": 0.2206896551724138,\n \"acc_norm_stderr\": 0.03455930201924812\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2566137566137566,\n \"acc_stderr\": 0.022494510767503154,\n \"\ acc_norm\": 0.2566137566137566,\n \"acc_norm_stderr\": 0.022494510767503154\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.03670066451047181,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.03670066451047181\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.23870967741935484,\n \"acc_stderr\": 0.024251071262208837,\n \"\ acc_norm\": 0.23870967741935484,\n \"acc_norm_stderr\": 0.024251071262208837\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.21182266009852216,\n \"acc_stderr\": 0.02874898368994106,\n \"\ acc_norm\": 0.21182266009852216,\n \"acc_norm_stderr\": 0.02874898368994106\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\ : 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.2909090909090909,\n \"acc_stderr\": 0.03546563019624336,\n\ \ \"acc_norm\": 0.2909090909090909,\n \"acc_norm_stderr\": 0.03546563019624336\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.16161616161616163,\n \"acc_stderr\": 0.026225919863629283,\n \"\ acc_norm\": 0.16161616161616163,\n \"acc_norm_stderr\": 0.026225919863629283\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.3005181347150259,\n \"acc_stderr\": 0.0330881859441575,\n\ \ \"acc_norm\": 0.3005181347150259,\n \"acc_norm_stderr\": 0.0330881859441575\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.2153846153846154,\n \"acc_stderr\": 0.020843034557462878,\n\ \ \"acc_norm\": 0.2153846153846154,\n \"acc_norm_stderr\": 0.020843034557462878\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.25925925925925924,\n \"acc_stderr\": 0.02671924078371215,\n \ \ \"acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.02671924078371215\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.2184873949579832,\n \"acc_stderr\": 0.026841514322958934,\n\ \ \"acc_norm\": 0.2184873949579832,\n \"acc_norm_stderr\": 0.026841514322958934\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.2052980132450331,\n \"acc_stderr\": 0.03297986648473834,\n \"\ acc_norm\": 0.2052980132450331,\n \"acc_norm_stderr\": 0.03297986648473834\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.26055045871559634,\n \"acc_stderr\": 0.018819182034850068,\n \"\ acc_norm\": 0.26055045871559634,\n \"acc_norm_stderr\": 0.018819182034850068\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.3055555555555556,\n \"acc_stderr\": 0.03141554629402543,\n \"\ acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.03141554629402543\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3094170403587444,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.3094170403587444,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.29770992366412213,\n \"acc_stderr\": 0.040103589424622034,\n\ \ \"acc_norm\": 0.29770992366412213,\n \"acc_norm_stderr\": 0.040103589424622034\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.21487603305785125,\n \"acc_stderr\": 0.037494924487096966,\n \"\ acc_norm\": 0.21487603305785125,\n \"acc_norm_stderr\": 0.037494924487096966\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.04330043749650743,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.04330043749650743\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.20535714285714285,\n\ \ \"acc_stderr\": 0.03834241021419073,\n \"acc_norm\": 0.20535714285714285,\n\ \ \"acc_norm_stderr\": 0.03834241021419073\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.1650485436893204,\n \"acc_stderr\": 0.036756688322331886,\n\ \ \"acc_norm\": 0.1650485436893204,\n \"acc_norm_stderr\": 0.036756688322331886\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2692307692307692,\n\ \ \"acc_stderr\": 0.029058588303748842,\n \"acc_norm\": 0.2692307692307692,\n\ \ \"acc_norm_stderr\": 0.029058588303748842\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.2515964240102171,\n\ \ \"acc_stderr\": 0.015517322365529627,\n \"acc_norm\": 0.2515964240102171,\n\ \ \"acc_norm_stderr\": 0.015517322365529627\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.23410404624277456,\n \"acc_stderr\": 0.02279711027807113,\n\ \ \"acc_norm\": 0.23410404624277456,\n \"acc_norm_stderr\": 0.02279711027807113\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2346368715083799,\n\ \ \"acc_stderr\": 0.014173044098303665,\n \"acc_norm\": 0.2346368715083799,\n\ \ \"acc_norm_stderr\": 0.014173044098303665\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.02380518652488815,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02380518652488815\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.22508038585209003,\n\ \ \"acc_stderr\": 0.023720088516179027,\n \"acc_norm\": 0.22508038585209003,\n\ \ \"acc_norm_stderr\": 0.023720088516179027\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.2777777777777778,\n \"acc_stderr\": 0.024922001168886324,\n\ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.024922001168886324\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.2730496453900709,\n \"acc_stderr\": 0.026577860943307847,\n \ \ \"acc_norm\": 0.2730496453900709,\n \"acc_norm_stderr\": 0.026577860943307847\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.24771838331160365,\n\ \ \"acc_stderr\": 0.011025499291443737,\n \"acc_norm\": 0.24771838331160365,\n\ \ \"acc_norm_stderr\": 0.011025499291443737\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.2536764705882353,\n \"acc_stderr\": 0.026431329870789527,\n\ \ \"acc_norm\": 0.2536764705882353,\n \"acc_norm_stderr\": 0.026431329870789527\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.2630718954248366,\n \"acc_stderr\": 0.017812676542320657,\n \ \ \"acc_norm\": 0.2630718954248366,\n \"acc_norm_stderr\": 0.017812676542320657\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.2909090909090909,\n\ \ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.2909090909090909,\n\ \ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.2163265306122449,\n \"acc_stderr\": 0.026358916334904052,\n\ \ \"acc_norm\": 0.2163265306122449,\n \"acc_norm_stderr\": 0.026358916334904052\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.22388059701492538,\n\ \ \"acc_stderr\": 0.029475250236017176,\n \"acc_norm\": 0.22388059701492538,\n\ \ \"acc_norm_stderr\": 0.029475250236017176\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.30120481927710846,\n\ \ \"acc_stderr\": 0.0357160923005348,\n \"acc_norm\": 0.30120481927710846,\n\ \ \"acc_norm_stderr\": 0.0357160923005348\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.2982456140350877,\n \"acc_stderr\": 0.03508771929824563,\n\ \ \"acc_norm\": 0.2982456140350877,\n \"acc_norm_stderr\": 0.03508771929824563\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.23133414932680538,\n\ \ \"mc1_stderr\": 0.014761945174862666,\n \"mc2\": 0.490951583190258,\n\ \ \"mc2_stderr\": 0.016977888460336696\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.48539857932123126,\n \"acc_stderr\": 0.014046492383275834\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/max-2022/test_mistral2 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_11T22_17_01.815383 path: - '**/details_harness|arc:challenge|25_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-11T22-17-01.815383.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|gsm8k|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hellaswag|10_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-11T22-17-01.815383.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-management|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T22-17-01.815383.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|truthfulqa:mc|0_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-11T22-17-01.815383.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_11T22_17_01.815383 path: - '**/details_harness|winogrande|5_2024-02-11T22-17-01.815383.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-11T22-17-01.815383.parquet' - config_name: results data_files: - split: 2024_02_11T22_17_01.815383 path: - results_2024-02-11T22-17-01.815383.parquet - split: latest path: - results_2024-02-11T22-17-01.815383.parquet --- # Dataset Card for Evaluation run of max-2022/test_mistral2  Dataset automatically created during the evaluation run of model [max-2022/test_mistral2](https://huggingface.co/max-2022/test_mistral2) 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_max-2022__test_mistral2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-11T22:17:01.815383](https://huggingface.co/datasets/open-llm-leaderboard/details_max-2022__test_mistral2/blob/main/results_2024-02-11T22-17-01.815383.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": 0.24710575900369156, "acc_stderr": 0.03055560450787355, "acc_norm": 0.24800687316365916, "acc_norm_stderr": 0.0313664960522948, "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862666, "mc2": 0.490951583190258, "mc2_stderr": 0.016977888460336696 }, "harness|arc:challenge|25": { "acc": 0.23037542662116042, "acc_stderr": 0.01230492841874761, "acc_norm": 0.2790102389078498, "acc_norm_stderr": 0.013106784883601338 }, "harness|hellaswag|10": { "acc": 0.2575184226249751, "acc_stderr": 0.004363736410689625, "acc_norm": 0.25323640709022105, "acc_norm_stderr": 0.004339764434219064 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.2, "acc_stderr": 0.04020151261036846, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2074074074074074, "acc_stderr": 0.03502553170678318, "acc_norm": 0.2074074074074074, "acc_norm_stderr": 0.03502553170678318 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.25, "acc_stderr": 0.03523807393012047, "acc_norm": 0.25, "acc_norm_stderr": 0.03523807393012047 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.23773584905660378, "acc_stderr": 0.0261998088075619, "acc_norm": 0.23773584905660378, "acc_norm_stderr": 0.0261998088075619 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2013888888888889, "acc_stderr": 0.033536474697138406, "acc_norm": 0.2013888888888889, "acc_norm_stderr": 0.033536474697138406 }, "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": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.24, "acc_stderr": 0.042923469599092816, "acc_norm": 0.24, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.26011560693641617, "acc_stderr": 0.03345036916788991, "acc_norm": 0.26011560693641617, "acc_norm_stderr": 0.03345036916788991 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.04158307533083286, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.04158307533083286 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3276595744680851, "acc_stderr": 0.03068302084323101, "acc_norm": 0.3276595744680851, "acc_norm_stderr": 0.03068302084323101 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813344, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813344 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2206896551724138, "acc_stderr": 0.03455930201924812, "acc_norm": 0.2206896551724138, "acc_norm_stderr": 0.03455930201924812 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2566137566137566, "acc_stderr": 0.022494510767503154, "acc_norm": 0.2566137566137566, "acc_norm_stderr": 0.022494510767503154 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.21428571428571427, "acc_stderr": 0.03670066451047181, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.03670066451047181 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.23870967741935484, "acc_stderr": 0.024251071262208837, "acc_norm": 0.23870967741935484, "acc_norm_stderr": 0.024251071262208837 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.21182266009852216, "acc_stderr": 0.02874898368994106, "acc_norm": 0.21182266009852216, "acc_norm_stderr": 0.02874898368994106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.2909090909090909, "acc_stderr": 0.03546563019624336, "acc_norm": 0.2909090909090909, "acc_norm_stderr": 0.03546563019624336 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.16161616161616163, "acc_stderr": 0.026225919863629283, "acc_norm": 0.16161616161616163, "acc_norm_stderr": 0.026225919863629283 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.3005181347150259, "acc_stderr": 0.0330881859441575, "acc_norm": 0.3005181347150259, "acc_norm_stderr": 0.0330881859441575 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2153846153846154, "acc_stderr": 0.020843034557462878, "acc_norm": 0.2153846153846154, "acc_norm_stderr": 0.020843034557462878 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.02671924078371215, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.02671924078371215 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.2184873949579832, "acc_stderr": 0.026841514322958934, "acc_norm": 0.2184873949579832, "acc_norm_stderr": 0.026841514322958934 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.2052980132450331, "acc_stderr": 0.03297986648473834, "acc_norm": 0.2052980132450331, "acc_norm_stderr": 0.03297986648473834 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.26055045871559634, "acc_stderr": 0.018819182034850068, "acc_norm": 0.26055045871559634, "acc_norm_stderr": 0.018819182034850068 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.3055555555555556, "acc_stderr": 0.03141554629402543, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.03141554629402543 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.3094170403587444, "acc_stderr": 0.03102441174057221, "acc_norm": 0.3094170403587444, "acc_norm_stderr": 0.03102441174057221 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.29770992366412213, "acc_stderr": 0.040103589424622034, "acc_norm": 0.29770992366412213, "acc_norm_stderr": 0.040103589424622034 }, "harness|hendrycksTest-international_law|5": { "acc": 0.21487603305785125, "acc_stderr": 0.037494924487096966, "acc_norm": 0.21487603305785125, "acc_norm_stderr": 0.037494924487096966 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.2777777777777778, "acc_stderr": 0.04330043749650743, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.04330043749650743 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.22085889570552147, "acc_stderr": 0.03259177392742178, "acc_norm": 0.22085889570552147, "acc_norm_stderr": 0.03259177392742178 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.20535714285714285, "acc_stderr": 0.03834241021419073, "acc_norm": 0.20535714285714285, "acc_norm_stderr": 0.03834241021419073 }, "harness|hendrycksTest-management|5": { "acc": 0.1650485436893204, "acc_stderr": 0.036756688322331886, "acc_norm": 0.1650485436893204, "acc_norm_stderr": 0.036756688322331886 }, "harness|hendrycksTest-marketing|5": { "acc": 0.2692307692307692, "acc_stderr": 0.029058588303748842, "acc_norm": 0.2692307692307692, "acc_norm_stderr": 0.029058588303748842 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.2515964240102171, "acc_stderr": 0.015517322365529627, "acc_norm": 0.2515964240102171, "acc_norm_stderr": 0.015517322365529627 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.23410404624277456, "acc_stderr": 0.02279711027807113, "acc_norm": 0.23410404624277456, "acc_norm_stderr": 0.02279711027807113 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2346368715083799, "acc_stderr": 0.014173044098303665, "acc_norm": 0.2346368715083799, "acc_norm_stderr": 0.014173044098303665 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.2222222222222222, "acc_stderr": 0.02380518652488815, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.02380518652488815 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.22508038585209003, "acc_stderr": 0.023720088516179027, "acc_norm": 0.22508038585209003, "acc_norm_stderr": 0.023720088516179027 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.2777777777777778, "acc_stderr": 0.024922001168886324, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.024922001168886324 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.2730496453900709, "acc_stderr": 0.026577860943307847, "acc_norm": 0.2730496453900709, "acc_norm_stderr": 0.026577860943307847 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.24771838331160365, "acc_stderr": 0.011025499291443737, "acc_norm": 0.24771838331160365, "acc_norm_stderr": 0.011025499291443737 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.2536764705882353, "acc_stderr": 0.026431329870789527, "acc_norm": 0.2536764705882353, "acc_norm_stderr": 0.026431329870789527 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.2630718954248366, "acc_stderr": 0.017812676542320657, "acc_norm": 0.2630718954248366, "acc_norm_stderr": 0.017812676542320657 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.2909090909090909, "acc_stderr": 0.04350271442923243, "acc_norm": 0.2909090909090909, "acc_norm_stderr": 0.04350271442923243 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.2163265306122449, "acc_stderr": 0.026358916334904052, "acc_norm": 0.2163265306122449, "acc_norm_stderr": 0.026358916334904052 }, "harness|hendrycksTest-sociology|5": { "acc": 0.22388059701492538, "acc_stderr": 0.029475250236017176, "acc_norm": 0.22388059701492538, "acc_norm_stderr": 0.029475250236017176 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-virology|5": { "acc": 0.30120481927710846, "acc_stderr": 0.0357160923005348, "acc_norm": 0.30120481927710846, "acc_norm_stderr": 0.0357160923005348 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.2982456140350877, "acc_stderr": 0.03508771929824563, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.03508771929824563 }, "harness|truthfulqa:mc|0": { "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862666, "mc2": 0.490951583190258, "mc2_stderr": 0.016977888460336696 }, "harness|winogrande|5": { "acc": 0.48539857932123126, "acc_stderr": 0.014046492383275834 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

hemanth955/Gold-alpaca-med-small-final

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: Input dtype: string - name: Output dtype: int64 - name: Instruction dtype: string - name: Text dtype: string splits: - name: train num_bytes: 48641940 num_examples: 27360 download_size: 10550533 dataset_size: 48641940 --- # Dataset Card for "Gold-alpaca-med-small-final" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k

--- pretty_name: Evaluation run of CallComply/SOLAR-10.7B-Instruct-v1.0-128k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CallComply/SOLAR-10.7B-Instruct-v1.0-128k](https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k)\ \ 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_CallComply__SOLAR-10.7B-Instruct-v1.0-128k\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-14T22:38:12.148949](https://huggingface.co/datasets/open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k/blob/main/results_2024-01-14T22-38-12.148949.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\": 0.5736345987046274,\n\ \ \"acc_stderr\": 0.033417579618165875,\n \"acc_norm\": 0.5822139213719528,\n\ \ \"acc_norm_stderr\": 0.03421698352385503,\n \"mc1\": 0.48592411260709917,\n\ \ \"mc1_stderr\": 0.017496563717042793,\n \"mc2\": 0.6542262778057006,\n\ \ \"mc2_stderr\": 0.015681013574816827\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6262798634812287,\n \"acc_stderr\": 0.014137708601759091,\n\ \ \"acc_norm\": 0.659556313993174,\n \"acc_norm_stderr\": 0.013847460518892973\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6415056761601274,\n\ \ \"acc_stderr\": 0.004785781979354868,\n \"acc_norm\": 0.8434574785899224,\n\ \ \"acc_norm_stderr\": 0.003626262805442223\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.562962962962963,\n\ \ \"acc_stderr\": 0.04284958639753401,\n \"acc_norm\": 0.562962962962963,\n\ \ \"acc_norm_stderr\": 0.04284958639753401\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.625,\n \"acc_stderr\": 0.039397364351956274,\n \ \ \"acc_norm\": 0.625,\n \"acc_norm_stderr\": 0.039397364351956274\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6188679245283019,\n \"acc_stderr\": 0.02989060968628664,\n\ \ \"acc_norm\": 0.6188679245283019,\n \"acc_norm_stderr\": 0.02989060968628664\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6527777777777778,\n\ \ \"acc_stderr\": 0.039812405437178615,\n \"acc_norm\": 0.6527777777777778,\n\ \ \"acc_norm_stderr\": 0.039812405437178615\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.48,\n\ \ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.48,\n \ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099522,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099522\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5659574468085107,\n \"acc_stderr\": 0.03240038086792747,\n\ \ \"acc_norm\": 0.5659574468085107,\n \"acc_norm_stderr\": 0.03240038086792747\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3508771929824561,\n\ \ \"acc_stderr\": 0.04489539350270699,\n \"acc_norm\": 0.3508771929824561,\n\ \ \"acc_norm_stderr\": 0.04489539350270699\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5655172413793104,\n \"acc_stderr\": 0.04130740879555497,\n\ \ \"acc_norm\": 0.5655172413793104,\n \"acc_norm_stderr\": 0.04130740879555497\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3412698412698413,\n \"acc_stderr\": 0.024419234966819064,\n \"\ acc_norm\": 0.3412698412698413,\n \"acc_norm_stderr\": 0.024419234966819064\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.35714285714285715,\n\ \ \"acc_stderr\": 0.04285714285714281,\n \"acc_norm\": 0.35714285714285715,\n\ \ \"acc_norm_stderr\": 0.04285714285714281\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6387096774193548,\n\ \ \"acc_stderr\": 0.027327548447957543,\n \"acc_norm\": 0.6387096774193548,\n\ \ \"acc_norm_stderr\": 0.027327548447957543\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4088669950738916,\n \"acc_stderr\": 0.034590588158832314,\n\ \ \"acc_norm\": 0.4088669950738916,\n \"acc_norm_stderr\": 0.034590588158832314\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\ : 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6424242424242425,\n \"acc_stderr\": 0.03742597043806585,\n\ \ \"acc_norm\": 0.6424242424242425,\n \"acc_norm_stderr\": 0.03742597043806585\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7676767676767676,\n \"acc_stderr\": 0.03008862949021749,\n \"\ acc_norm\": 0.7676767676767676,\n \"acc_norm_stderr\": 0.03008862949021749\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.844559585492228,\n \"acc_stderr\": 0.02614848346915332,\n\ \ \"acc_norm\": 0.844559585492228,\n \"acc_norm_stderr\": 0.02614848346915332\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5769230769230769,\n \"acc_stderr\": 0.025049197876042338,\n\ \ \"acc_norm\": 0.5769230769230769,\n \"acc_norm_stderr\": 0.025049197876042338\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2814814814814815,\n \"acc_stderr\": 0.027420019350945284,\n \ \ \"acc_norm\": 0.2814814814814815,\n \"acc_norm_stderr\": 0.027420019350945284\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6302521008403361,\n \"acc_stderr\": 0.03135709599613591,\n \ \ \"acc_norm\": 0.6302521008403361,\n \"acc_norm_stderr\": 0.03135709599613591\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.763302752293578,\n \"acc_stderr\": 0.018224078117299106,\n \"\ acc_norm\": 0.763302752293578,\n \"acc_norm_stderr\": 0.018224078117299106\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4212962962962963,\n \"acc_stderr\": 0.03367462138896078,\n \"\ acc_norm\": 0.4212962962962963,\n \"acc_norm_stderr\": 0.03367462138896078\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7352941176470589,\n \"acc_stderr\": 0.030964517926923403,\n \"\ acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.030964517926923403\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7341772151898734,\n \"acc_stderr\": 0.02875679962965834,\n \ \ \"acc_norm\": 0.7341772151898734,\n \"acc_norm_stderr\": 0.02875679962965834\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6367713004484304,\n\ \ \"acc_stderr\": 0.032277904428505,\n \"acc_norm\": 0.6367713004484304,\n\ \ \"acc_norm_stderr\": 0.032277904428505\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6946564885496184,\n \"acc_stderr\": 0.040393149787245605,\n\ \ \"acc_norm\": 0.6946564885496184,\n \"acc_norm_stderr\": 0.040393149787245605\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8016528925619835,\n \"acc_stderr\": 0.03640118271990948,\n \"\ acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.03640118271990948\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7177914110429447,\n \"acc_stderr\": 0.03536117886664742,\n\ \ \"acc_norm\": 0.7177914110429447,\n \"acc_norm_stderr\": 0.03536117886664742\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.41964285714285715,\n\ \ \"acc_stderr\": 0.046840993210771065,\n \"acc_norm\": 0.41964285714285715,\n\ \ \"acc_norm_stderr\": 0.046840993210771065\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7475728155339806,\n \"acc_stderr\": 0.04301250399690878,\n\ \ \"acc_norm\": 0.7475728155339806,\n \"acc_norm_stderr\": 0.04301250399690878\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8205128205128205,\n\ \ \"acc_stderr\": 0.025140935950335445,\n \"acc_norm\": 0.8205128205128205,\n\ \ \"acc_norm_stderr\": 0.025140935950335445\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939098,\n \ \ \"acc_norm\": 0.63,\n \"acc_norm_stderr\": 0.04852365870939098\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7547892720306514,\n\ \ \"acc_stderr\": 0.015384352284543932,\n \"acc_norm\": 0.7547892720306514,\n\ \ \"acc_norm_stderr\": 0.015384352284543932\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6734104046242775,\n \"acc_stderr\": 0.025248264774242836,\n\ \ \"acc_norm\": 0.6734104046242775,\n \"acc_norm_stderr\": 0.025248264774242836\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.31620111731843575,\n\ \ \"acc_stderr\": 0.015551673652172544,\n \"acc_norm\": 0.31620111731843575,\n\ \ \"acc_norm_stderr\": 0.015551673652172544\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.630718954248366,\n \"acc_stderr\": 0.027634176689602653,\n\ \ \"acc_norm\": 0.630718954248366,\n \"acc_norm_stderr\": 0.027634176689602653\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6077170418006431,\n\ \ \"acc_stderr\": 0.027731258647011994,\n \"acc_norm\": 0.6077170418006431,\n\ \ \"acc_norm_stderr\": 0.027731258647011994\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6265432098765432,\n \"acc_stderr\": 0.026915003011380154,\n\ \ \"acc_norm\": 0.6265432098765432,\n \"acc_norm_stderr\": 0.026915003011380154\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4148936170212766,\n \"acc_stderr\": 0.029392236584612503,\n \ \ \"acc_norm\": 0.4148936170212766,\n \"acc_norm_stderr\": 0.029392236584612503\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.423728813559322,\n\ \ \"acc_stderr\": 0.012620785155885992,\n \"acc_norm\": 0.423728813559322,\n\ \ \"acc_norm_stderr\": 0.012620785155885992\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5073529411764706,\n \"acc_stderr\": 0.030369552523902173,\n\ \ \"acc_norm\": 0.5073529411764706,\n \"acc_norm_stderr\": 0.030369552523902173\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6045751633986928,\n \"acc_stderr\": 0.019780465954777518,\n \ \ \"acc_norm\": 0.6045751633986928,\n \"acc_norm_stderr\": 0.019780465954777518\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6181818181818182,\n\ \ \"acc_stderr\": 0.04653429807913508,\n \"acc_norm\": 0.6181818181818182,\n\ \ \"acc_norm_stderr\": 0.04653429807913508\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7142857142857143,\n \"acc_stderr\": 0.0289205832206756,\n\ \ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.0289205832206756\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.4975124378109453,\n\ \ \"acc_stderr\": 0.03535490150137288,\n \"acc_norm\": 0.4975124378109453,\n\ \ \"acc_norm_stderr\": 0.03535490150137288\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5,\n \ \ \"acc_stderr\": 0.03892494720807614,\n \"acc_norm\": 0.5,\n \"\ acc_norm_stderr\": 0.03892494720807614\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7485380116959064,\n \"acc_stderr\": 0.033275044238468436,\n\ \ \"acc_norm\": 0.7485380116959064,\n \"acc_norm_stderr\": 0.033275044238468436\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.48592411260709917,\n\ \ \"mc1_stderr\": 0.017496563717042793,\n \"mc2\": 0.6542262778057006,\n\ \ \"mc2_stderr\": 0.015681013574816827\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8050513022888713,\n \"acc_stderr\": 0.011134099415938256\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0712661106899166,\n \ \ \"acc_stderr\": 0.0070864621279544985\n }\n}\n```" repo_url: https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k 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_14T22_38_12.148949 path: - '**/details_harness|arc:challenge|25_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-14T22-38-12.148949.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|gsm8k|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hellaswag|10_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-14T22-38-12.148949.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-management|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-14T22-38-12.148949.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|truthfulqa:mc|0_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-14T22-38-12.148949.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_14T22_38_12.148949 path: - '**/details_harness|winogrande|5_2024-01-14T22-38-12.148949.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-14T22-38-12.148949.parquet' - config_name: results data_files: - split: 2024_01_14T22_38_12.148949 path: - results_2024-01-14T22-38-12.148949.parquet - split: latest path: - results_2024-01-14T22-38-12.148949.parquet --- # Dataset Card for Evaluation run of CallComply/SOLAR-10.7B-Instruct-v1.0-128k  Dataset automatically created during the evaluation run of model [CallComply/SOLAR-10.7B-Instruct-v1.0-128k](https://huggingface.co/CallComply/SOLAR-10.7B-Instruct-v1.0-128k) 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_CallComply__SOLAR-10.7B-Instruct-v1.0-128k", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-14T22:38:12.148949](https://huggingface.co/datasets/open-llm-leaderboard/details_CallComply__SOLAR-10.7B-Instruct-v1.0-128k/blob/main/results_2024-01-14T22-38-12.148949.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": 0.5736345987046274, "acc_stderr": 0.033417579618165875, "acc_norm": 0.5822139213719528, "acc_norm_stderr": 0.03421698352385503, "mc1": 0.48592411260709917, "mc1_stderr": 0.017496563717042793, "mc2": 0.6542262778057006, "mc2_stderr": 0.015681013574816827 }, "harness|arc:challenge|25": { "acc": 0.6262798634812287, "acc_stderr": 0.014137708601759091, "acc_norm": 0.659556313993174, "acc_norm_stderr": 0.013847460518892973 }, "harness|hellaswag|10": { "acc": 0.6415056761601274, "acc_stderr": 0.004785781979354868, "acc_norm": 0.8434574785899224, "acc_norm_stderr": 0.003626262805442223 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.625, "acc_stderr": 0.039397364351956274, "acc_norm": 0.625, "acc_norm_stderr": 0.039397364351956274 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6188679245283019, "acc_stderr": 0.02989060968628664, "acc_norm": 0.6188679245283019, "acc_norm_stderr": 0.02989060968628664 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6527777777777778, "acc_stderr": 0.039812405437178615, "acc_norm": 0.6527777777777778, "acc_norm_stderr": 0.039812405437178615 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099522, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099522 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5659574468085107, "acc_stderr": 0.03240038086792747, "acc_norm": 0.5659574468085107, "acc_norm_stderr": 0.03240038086792747 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3508771929824561, "acc_stderr": 0.04489539350270699, "acc_norm": 0.3508771929824561, "acc_norm_stderr": 0.04489539350270699 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555497, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3412698412698413, "acc_stderr": 0.024419234966819064, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.024419234966819064 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.35714285714285715, "acc_stderr": 0.04285714285714281, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.04285714285714281 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6387096774193548, "acc_stderr": 0.027327548447957543, "acc_norm": 0.6387096774193548, "acc_norm_stderr": 0.027327548447957543 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4088669950738916, "acc_stderr": 0.034590588158832314, "acc_norm": 0.4088669950738916, "acc_norm_stderr": 0.034590588158832314 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6424242424242425, "acc_stderr": 0.03742597043806585, "acc_norm": 0.6424242424242425, "acc_norm_stderr": 0.03742597043806585 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.03008862949021749, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.03008862949021749 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.844559585492228, "acc_stderr": 0.02614848346915332, "acc_norm": 0.844559585492228, "acc_norm_stderr": 0.02614848346915332 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5769230769230769, "acc_stderr": 0.025049197876042338, "acc_norm": 0.5769230769230769, "acc_norm_stderr": 0.025049197876042338 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2814814814814815, "acc_stderr": 0.027420019350945284, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.027420019350945284 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6302521008403361, "acc_stderr": 0.03135709599613591, "acc_norm": 0.6302521008403361, "acc_norm_stderr": 0.03135709599613591 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.763302752293578, "acc_stderr": 0.018224078117299106, "acc_norm": 0.763302752293578, "acc_norm_stderr": 0.018224078117299106 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4212962962962963, "acc_stderr": 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"acc": 0.6265432098765432, "acc_stderr": 0.026915003011380154, "acc_norm": 0.6265432098765432, "acc_norm_stderr": 0.026915003011380154 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4148936170212766, "acc_stderr": 0.029392236584612503, "acc_norm": 0.4148936170212766, "acc_norm_stderr": 0.029392236584612503 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.423728813559322, "acc_stderr": 0.012620785155885992, "acc_norm": 0.423728813559322, "acc_norm_stderr": 0.012620785155885992 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5073529411764706, "acc_stderr": 0.030369552523902173, "acc_norm": 0.5073529411764706, "acc_norm_stderr": 0.030369552523902173 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6045751633986928, "acc_stderr": 0.019780465954777518, "acc_norm": 0.6045751633986928, "acc_norm_stderr": 0.019780465954777518 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6181818181818182, "acc_stderr": 0.04653429807913508, "acc_norm": 0.6181818181818182, "acc_norm_stderr": 0.04653429807913508 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7142857142857143, "acc_stderr": 0.0289205832206756, "acc_norm": 0.7142857142857143, "acc_norm_stderr": 0.0289205832206756 }, "harness|hendrycksTest-sociology|5": { "acc": 0.4975124378109453, "acc_stderr": 0.03535490150137288, "acc_norm": 0.4975124378109453, "acc_norm_stderr": 0.03535490150137288 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness|hendrycksTest-virology|5": { "acc": 0.5, "acc_stderr": 0.03892494720807614, "acc_norm": 0.5, "acc_norm_stderr": 0.03892494720807614 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7485380116959064, "acc_stderr": 0.033275044238468436, "acc_norm": 0.7485380116959064, "acc_norm_stderr": 0.033275044238468436 }, "harness|truthfulqa:mc|0": { "mc1": 0.48592411260709917, "mc1_stderr": 0.017496563717042793, "mc2": 0.6542262778057006, "mc2_stderr": 0.015681013574816827 }, "harness|winogrande|5": { "acc": 0.8050513022888713, "acc_stderr": 0.011134099415938256 }, "harness|gsm8k|5": { "acc": 0.0712661106899166, "acc_stderr": 0.0070864621279544985 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

CyberHarem/ikebukuro_akiha_idolmastercinderellagirls

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of ikebukuro_akiha/池袋晶葉 (THE iDOLM@STER: Cinderella Girls) This is the dataset of ikebukuro_akiha/池袋晶葉 (THE iDOLM@STER: Cinderella Girls), containing 190 images and their tags. The core tags of this character are `brown_hair, glasses, brown_eyes, twintails, long_hair, semi-rimless_eyewear, bangs, pink-framed_eyewear, under-rim_eyewear, blunt_bangs, bow, ribbon`, 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 | 190 | 180.09 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 190 | 125.54 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 443 | 258.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 190 | 165.75 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 443 | 327.91 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ikebukuro_akiha_idolmastercinderellagirls/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/ikebukuro_akiha_idolmastercinderellagirls', 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 | 6 | ![](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, ponytail, ribbed_sweater, solo, turtleneck_sweater, labcoat, looking_at_viewer, simple_background, smile, white_background, large_breasts, red_sweater, blush, hair_bow, long_sleeves, sidelocks, skirt | | 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, solo, serafuku, skirt, labcoat, smile, blush, white_background | | 2 | 5 | ![](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, blue_sailor_collar, blue_skirt, labcoat, long_sleeves, looking_at_viewer, pleated_skirt, red_bow, simple_background, solo, hair_bow, serafuku, shirt, white_background, closed_mouth, grin, sitting | | 3 | 11 | ![](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, blue_skirt, blush, labcoat, long_sleeves, looking_at_viewer, open_clothes, pleated_skirt, solo, white_background, hair_ribbon, serafuku, simple_background, blue_sailor_collar, red_bow, red_ribbon, sidelocks, blue_shirt, smile, collarbone, v-shaped_eyebrows, closed_mouth, hand_up, red-framed_eyewear, signature, white_shirt | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, solo, black_thighhighs, grin, belt, labcoat, rabbit_ears | | 5 | 5 | ![](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, blush, looking_at_viewer, navel, nipples, solo, collarbone, pussy, red-framed_eyewear, small_breasts, completely_nude, depth_of_field, open_mouth, sidelocks, standing, sweat, :o, bar_censor, blurry_background, convenient_censoring, cowboy_shot, dutch_angle, groin, hair_bow, medium_breasts, onsen, rectangular_eyewear, red_bow, sitting, steam, v-shaped_eyebrows, very_long_hair | | 6 | 7 | ![](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, solo, collarbone, double_bun, midriff, necklace, sidelocks, blush, bracelet, looking_at_viewer, short_sleeves, blue_shorts, clothes_around_waist, clothes_writing, navel, off_shoulder, short_shorts, breasts, crop_top, denim_shorts, grin, hair_bow, hair_ribbon, star_(symbol), white_shirt, x_hair_ornament | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | ponytail | ribbed_sweater | solo | turtleneck_sweater | labcoat | looking_at_viewer | simple_background | smile | white_background | large_breasts | red_sweater | blush | hair_bow | long_sleeves | sidelocks | skirt | serafuku | blue_sailor_collar | blue_skirt | pleated_skirt | red_bow | shirt | closed_mouth | grin | sitting | open_clothes | hair_ribbon | red_ribbon | blue_shirt | collarbone | v-shaped_eyebrows | hand_up | red-framed_eyewear | signature | white_shirt | black_thighhighs | belt | rabbit_ears | navel | nipples | pussy | small_breasts | completely_nude | depth_of_field | open_mouth | standing | sweat | :o | bar_censor | blurry_background | convenient_censoring | cowboy_shot | dutch_angle | groin | medium_breasts | onsen | rectangular_eyewear | steam | very_long_hair | double_bun | midriff | necklace | bracelet | short_sleeves | blue_shorts | clothes_around_waist | clothes_writing | off_shoulder | short_shorts | breasts | crop_top | denim_shorts | star_(symbol) | x_hair_ornament | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------|:-----------------|:-------|:---------------------|:----------|:--------------------|:--------------------|:--------|:-------------------|:----------------|:--------------|:--------|:-----------|:---------------|:------------|:--------|:-----------|:---------------------|:-------------|:----------------|:----------|:--------|:---------------|:-------|:----------|:---------------|:--------------|:-------------|:-------------|:-------------|:--------------------|:----------|:---------------------|:------------|:--------------|:-------------------|:-------|:--------------|:--------|:----------|:--------|:----------------|:------------------|:-----------------|:-------------|:-----------|:--------|:-----|:-------------|:--------------------|:-----------------------|:--------------|:--------------|:--------|:-----------------|:--------|:----------------------|:--------|:-----------------|:-------------|:----------|:-----------|:-----------|:----------------|:--------------|:-----------------------|:------------------|:---------------|:---------------|:----------|:-----------|:---------------|:----------------|:------------------| | 0 | 6 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 5 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 11 | ![](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 | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | | | X | | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 5 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | X | | | X | | | X | | | | | | X | X | | X | | | | | | X | | | | X | | | | | X | X | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | 6 | 7 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | X | | | X | | | X | | | | | | X | X | | X | | | | | | | | | X | | | X | | | X | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

one-sec-cv12/chunk_57

--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 25320557952.0 num_examples: 263624 download_size: 23104462381 dataset_size: 25320557952.0 --- # Dataset Card for "chunk_57" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

yzhuang/metatree_fri_c3_1000_50

--- dataset_info: features: - name: id dtype: int64 - name: X sequence: float64 - name: y dtype: int64 splits: - name: train num_bytes: 304920 num_examples: 726 - name: validation num_bytes: 115080 num_examples: 274 download_size: 504483 dataset_size: 420000 --- # Dataset Card for "metatree_fri_c3_1000_50" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

lamini/lamini_docs

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 1846734.3 num_examples: 1260 - name: test num_bytes: 205192.7 num_examples: 140 download_size: 698607 dataset_size: 2051927.0 --- # Dataset Card for "lamini_docs" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

sgjwong/ltedi23-models

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

Tuana/presidents

--- dataset_info: features: - name: id dtype: string - name: content dtype: string - name: content_type dtype: string - name: meta struct: - name: url dtype: string - name: _split_id dtype: int64 - name: id_hash_keys sequence: string - name: score dtype: 'null' - name: embedding dtype: 'null' splits: - name: train num_bytes: 9366886 num_examples: 5529 download_size: 4997888 dataset_size: 9366886 --- # Dataset Card for "presidents" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

hongboyang/LCSTS_instruction1

--- dataset_info: features: - name: INPUT dtype: string - name: TARGET dtype: string splits: - name: train num_bytes: 1128722053 num_examples: 2400591 download_size: 693529602 dataset_size: 1128722053 --- # Dataset Card for "LCSTS_instruction1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

autoevaluate/autoeval-staging-eval-Tristan__zero-shot-classification-large-test-Tristan__z-d81307-16956302

--- type: predictions tags: - autotrain - evaluation datasets: - Tristan/zero-shot-classification-large-test eval_info: task: text_zero_shot_classification model: Tristan/opt-66b-copy metrics: [] dataset_name: Tristan/zero-shot-classification-large-test dataset_config: Tristan--zero-shot-classification-large-test 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: Tristan/opt-66b-copy * Dataset: Tristan/zero-shot-classification-large-test * Config: Tristan--zero-shot-classification-large-test * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model.

furry-br/krystal

--- license: openrail ---

liyongsea/empty_function_jupyter

--- dataset_info: features: - name: path dtype: string - name: content_id dtype: string - name: detected_licenses sequence: string - name: license_type dtype: string - name: repo_name dtype: string - name: repo_url dtype: string - name: star_events_count dtype: int64 - name: fork_events_count dtype: int64 - name: gha_license_id dtype: string - name: gha_event_created_at dtype: timestamp[us] - name: gha_updated_at dtype: timestamp[us] - name: gha_language dtype: string - name: language dtype: string - name: is_generated dtype: bool - name: is_vendor dtype: bool - name: conversion_extension dtype: string - name: size dtype: int64 - name: script dtype: string - name: script_size dtype: int64 splits: - name: train num_bytes: 654648.6506 num_examples: 28 download_size: 292451 dataset_size: 654648.6506 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "empty_function_jupyter" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/lawine_sousounofrieren

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Lawine/ラヴィーネ (Sousou no Frieren) This is the dataset of Lawine/ラヴィーネ (Sousou no Frieren), containing 192 images and their tags. The core tags of this character are `long_hair, braid, blue_eyes, blunt_bangs, grey_hair, french_braid, brown_hair`, 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 | 192 | 124.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 192 | 124.17 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 313 | 191.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lawine_sousounofrieren/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/lawine_sousounofrieren', 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 | 13 | ![](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, blue_capelet, blue_dress, long_sleeves, solo, holding_staff, closed_mouth, upper_body, blurry_background, frilled_capelet, outdoors | | 1 | 14 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, holding_staff, long_sleeves, solo, blue_capelet, blue_dress, frilled_capelet, standing, outdoors, closed_mouth, white_thighhighs, cross-laced_footwear, cloudy_sky, very_long_hair, full_body, thigh_boots, tree | | 2 | 9 | ![](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, closed_mouth, expressionless, blue_capelet, solo, upper_body, blue_dress, outdoors, tree, looking_at_viewer, forest, frills | | 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, blue_capelet, blue_dress, frilled_capelet, long_sleeves, outdoors, solo, looking_at_viewer, open_mouth, closed_mouth, cloudy_sky | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, blue_capelet, closed_mouth, solo, blue_dress, frilled_dress, lace-up_boots, long_sleeves, standing, white_footwear, white_thighhighs, full_body, thigh_boots, frilled_capelet, outdoors, blurry, forest, looking_at_viewer | | 5 | 8 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | 1girl, blue_dress, closed_mouth, long_sleeves, solo, low-tied_long_hair, very_long_hair, expressionless, frilled_capelet, frilled_dress, from_side, profile | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | blue_capelet, blue_dress, frilled_dress, long_sleeves, sitting_on_person, very_long_hair, 2girls, checkered_floor, frilled_capelet, solo_focus, white_thighhighs, green_shorts, thigh_boots, closed_mouth, low-tied_long_hair | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_capelet | blue_dress | long_sleeves | solo | holding_staff | closed_mouth | upper_body | blurry_background | frilled_capelet | outdoors | standing | white_thighhighs | cross-laced_footwear | cloudy_sky | very_long_hair | full_body | thigh_boots | tree | expressionless | looking_at_viewer | forest | frills | open_mouth | frilled_dress | lace-up_boots | white_footwear | blurry | low-tied_long_hair | from_side | profile | sitting_on_person | 2girls | checkered_floor | solo_focus | green_shorts | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:-------------|:---------------|:-------|:----------------|:---------------|:-------------|:--------------------|:------------------|:-----------|:-----------|:-------------------|:-----------------------|:-------------|:-----------------|:------------|:--------------|:-------|:-----------------|:--------------------|:---------|:---------|:-------------|:----------------|:----------------|:-----------------|:---------|:---------------------|:------------|:----------|:--------------------|:---------|:------------------|:-------------|:---------------| | 0 | 13 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 14 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | X | X | X | X | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | 2 | 9 | ![](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 | 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 | | | | | | | | | | | | | | 4 | 7 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | X | X | X | X | | X | | | X | X | X | X | | | | X | X | | | X | X | | | X | X | X | X | | | | | | | | | | 5 | 8 | ![](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 | | | | | | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | | X | X | X | | | X | | | X | | | X | | | X | | X | | | | | | | X | | | | X | | | X | X | X | X | X |

mar-yam1497/HotPotQA_Mistral_dataset_Top3k

--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 7691946 num_examples: 3000 download_size: 3547124 dataset_size: 7691946 configs: - config_name: default data_files: - split: train path: data/train-* ---

jxie/bbbp

--- dataset_info: features: - name: index dtype: int64 - name: text dtype: string - name: label dtype: int64 splits: - name: train_0 num_bytes: 112140 num_examples: 1631 - name: val_0 num_bytes: 18772 num_examples: 204 - name: test_0 num_bytes: 15004 num_examples: 204 - name: train_1 num_bytes: 112140 num_examples: 1631 - name: val_1 num_bytes: 18772 num_examples: 204 - name: test_1 num_bytes: 15004 num_examples: 204 - name: train_2 num_bytes: 112140 num_examples: 1631 - name: val_2 num_bytes: 18772 num_examples: 204 - name: test_2 num_bytes: 15004 num_examples: 204 download_size: 218838 dataset_size: 437748 --- # Dataset Card for "bbbp" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ

--- pretty_name: Evaluation run of TheBloke/Genz-70b-GPTQ dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TheBloke/Genz-70b-GPTQ](https://huggingface.co/TheBloke/Genz-70b-GPTQ) 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_TheBloke__Genz-70b-GPTQ\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-31T00:30:34.342002](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ/blob/main/results_2023-08-31T00%3A30%3A34.342002.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\": 0.7017249416277331,\n\ \ \"acc_stderr\": 0.030832772804323012,\n \"acc_norm\": 0.70569345061239,\n\ \ \"acc_norm_stderr\": 0.03080075128019408,\n \"mc1\": 0.4320685434516524,\n\ \ \"mc1_stderr\": 0.01734120239498826,\n \"mc2\": 0.6228267270427654,\n\ \ \"mc2_stderr\": 0.014836432877772263\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6638225255972696,\n \"acc_stderr\": 0.013804855026205763,\n\ \ \"acc_norm\": 0.7107508532423208,\n \"acc_norm_stderr\": 0.013250012579393443\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.689205337582155,\n\ \ \"acc_stderr\": 0.004618730353217047,\n \"acc_norm\": 0.8764190400318662,\n\ \ \"acc_norm_stderr\": 0.0032843028764223\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.8223684210526315,\n \"acc_stderr\": 0.03110318238312338,\n\ \ \"acc_norm\": 0.8223684210526315,\n \"acc_norm_stderr\": 0.03110318238312338\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.76,\n\ \ \"acc_stderr\": 0.04292346959909284,\n \"acc_norm\": 0.76,\n \ \ \"acc_norm_stderr\": 0.04292346959909284\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.720754716981132,\n \"acc_stderr\": 0.027611163402399715,\n\ \ \"acc_norm\": 0.720754716981132,\n \"acc_norm_stderr\": 0.027611163402399715\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.032166008088022675,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.032166008088022675\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956911,\n \ \ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956911\n \ \ },\n \"harness|hendrycksTest-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\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6473988439306358,\n\ \ \"acc_stderr\": 0.036430371689585475,\n \"acc_norm\": 0.6473988439306358,\n\ \ \"acc_norm_stderr\": 0.036430371689585475\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.676595744680851,\n \"acc_stderr\": 0.030579442773610337,\n\ \ \"acc_norm\": 0.676595744680851,\n \"acc_norm_stderr\": 0.030579442773610337\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.45614035087719296,\n\ \ \"acc_stderr\": 0.04685473041907789,\n \"acc_norm\": 0.45614035087719296,\n\ \ \"acc_norm_stderr\": 0.04685473041907789\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.04013124195424386,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.04013124195424386\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4417989417989418,\n \"acc_stderr\": 0.02557625706125384,\n \"\ acc_norm\": 0.4417989417989418,\n \"acc_norm_stderr\": 0.02557625706125384\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677172,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677172\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8290322580645161,\n\ \ \"acc_stderr\": 0.02141724293632159,\n \"acc_norm\": 0.8290322580645161,\n\ \ \"acc_norm_stderr\": 0.02141724293632159\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5270935960591133,\n \"acc_stderr\": 0.03512819077876106,\n\ \ \"acc_norm\": 0.5270935960591133,\n \"acc_norm_stderr\": 0.03512819077876106\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.8,\n \"acc_stderr\": 0.04020151261036846,\n \"acc_norm\"\ : 0.8,\n \"acc_norm_stderr\": 0.04020151261036846\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8545454545454545,\n \"acc_stderr\": 0.027530196355066573,\n\ \ \"acc_norm\": 0.8545454545454545,\n \"acc_norm_stderr\": 0.027530196355066573\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8686868686868687,\n \"acc_stderr\": 0.024063156416822523,\n \"\ acc_norm\": 0.8686868686868687,\n \"acc_norm_stderr\": 0.024063156416822523\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9378238341968912,\n \"acc_stderr\": 0.017426974154240528,\n\ \ \"acc_norm\": 0.9378238341968912,\n \"acc_norm_stderr\": 0.017426974154240528\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.7051282051282052,\n \"acc_stderr\": 0.023119362758232294,\n\ \ \"acc_norm\": 0.7051282051282052,\n \"acc_norm_stderr\": 0.023119362758232294\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.31851851851851853,\n \"acc_stderr\": 0.028406533090608463,\n \ \ \"acc_norm\": 0.31851851851851853,\n \"acc_norm_stderr\": 0.028406533090608463\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.773109243697479,\n \"acc_stderr\": 0.027205371538279472,\n \ \ \"acc_norm\": 0.773109243697479,\n \"acc_norm_stderr\": 0.027205371538279472\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.5099337748344371,\n \"acc_stderr\": 0.04081677107248437,\n \"\ acc_norm\": 0.5099337748344371,\n \"acc_norm_stderr\": 0.04081677107248437\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8917431192660551,\n \"acc_stderr\": 0.013321348447611769,\n \"\ acc_norm\": 0.8917431192660551,\n \"acc_norm_stderr\": 0.013321348447611769\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.6018518518518519,\n \"acc_stderr\": 0.033384734032074016,\n \"\ acc_norm\": 0.6018518518518519,\n \"acc_norm_stderr\": 0.033384734032074016\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073312,\n \"\ acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073312\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640262,\n \ \ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640262\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.8116591928251121,\n\ \ \"acc_stderr\": 0.026241132996407252,\n \"acc_norm\": 0.8116591928251121,\n\ \ \"acc_norm_stderr\": 0.026241132996407252\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8396946564885496,\n \"acc_stderr\": 0.03217829420744633,\n\ \ \"acc_norm\": 0.8396946564885496,\n \"acc_norm_stderr\": 0.03217829420744633\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.859504132231405,\n \"acc_stderr\": 0.03172233426002157,\n \"acc_norm\"\ : 0.859504132231405,\n \"acc_norm_stderr\": 0.03172233426002157\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8240740740740741,\n\ \ \"acc_stderr\": 0.036809181416738807,\n \"acc_norm\": 0.8240740740740741,\n\ \ \"acc_norm_stderr\": 0.036809181416738807\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8159509202453987,\n \"acc_stderr\": 0.030446777687971726,\n\ \ \"acc_norm\": 0.8159509202453987,\n \"acc_norm_stderr\": 0.030446777687971726\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04745789978762494,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04745789978762494\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8446601941747572,\n \"acc_stderr\": 0.03586594738573974,\n\ \ \"acc_norm\": 0.8446601941747572,\n \"acc_norm_stderr\": 0.03586594738573974\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9102564102564102,\n\ \ \"acc_stderr\": 0.018724301741941642,\n \"acc_norm\": 0.9102564102564102,\n\ \ \"acc_norm_stderr\": 0.018724301741941642\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\": 0.8722860791826309,\n\ \ \"acc_stderr\": 0.011935626313999876,\n \"acc_norm\": 0.8722860791826309,\n\ \ \"acc_norm_stderr\": 0.011935626313999876\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.8005780346820809,\n \"acc_stderr\": 0.021511900654252562,\n\ \ \"acc_norm\": 0.8005780346820809,\n \"acc_norm_stderr\": 0.021511900654252562\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.5754189944134078,\n\ \ \"acc_stderr\": 0.01653117099327888,\n \"acc_norm\": 0.5754189944134078,\n\ \ \"acc_norm_stderr\": 0.01653117099327888\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7745098039215687,\n \"acc_stderr\": 0.02392915551735129,\n\ \ \"acc_norm\": 0.7745098039215687,\n \"acc_norm_stderr\": 0.02392915551735129\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7717041800643086,\n\ \ \"acc_stderr\": 0.023839303311398205,\n \"acc_norm\": 0.7717041800643086,\n\ \ \"acc_norm_stderr\": 0.023839303311398205\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8487654320987654,\n \"acc_stderr\": 0.019935086092149897,\n\ \ \"acc_norm\": 0.8487654320987654,\n \"acc_norm_stderr\": 0.019935086092149897\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5638297872340425,\n \"acc_stderr\": 0.029583452036284076,\n \ \ \"acc_norm\": 0.5638297872340425,\n \"acc_norm_stderr\": 0.029583452036284076\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5534550195567145,\n\ \ \"acc_stderr\": 0.012697046024399654,\n \"acc_norm\": 0.5534550195567145,\n\ \ \"acc_norm_stderr\": 0.012697046024399654\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7389705882352942,\n \"acc_stderr\": 0.026679252270103135,\n\ \ \"acc_norm\": 0.7389705882352942,\n \"acc_norm_stderr\": 0.026679252270103135\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7630718954248366,\n \"acc_stderr\": 0.017201662169789772,\n \ \ \"acc_norm\": 0.7630718954248366,\n \"acc_norm_stderr\": 0.017201662169789772\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7363636363636363,\n\ \ \"acc_stderr\": 0.04220224692971987,\n \"acc_norm\": 0.7363636363636363,\n\ \ \"acc_norm_stderr\": 0.04220224692971987\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.8,\n \"acc_stderr\": 0.02560737598657916,\n \ \ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.02560737598657916\n },\n\ \ \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8606965174129353,\n\ \ \"acc_stderr\": 0.024484487162913973,\n \"acc_norm\": 0.8606965174129353,\n\ \ \"acc_norm_stderr\": 0.024484487162913973\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.9,\n \"acc_stderr\": 0.030151134457776334,\n \ \ \"acc_norm\": 0.9,\n \"acc_norm_stderr\": 0.030151134457776334\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5180722891566265,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.5180722891566265,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.025172984350155754,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.025172984350155754\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4320685434516524,\n\ \ \"mc1_stderr\": 0.01734120239498826,\n \"mc2\": 0.6228267270427654,\n\ \ \"mc2_stderr\": 0.014836432877772263\n }\n}\n```" repo_url: https://huggingface.co/TheBloke/Genz-70b-GPTQ 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_31T00_30_34.342002 path: - '**/details_harness|arc:challenge|25_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hellaswag|10_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T00:30:34.342002.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T00:30:34.342002.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_31T00_30_34.342002 path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T00:30:34.342002.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T00:30:34.342002.parquet' - config_name: results data_files: - split: 2023_08_31T00_30_34.342002 path: - results_2023-08-31T00:30:34.342002.parquet - split: latest path: - results_2023-08-31T00:30:34.342002.parquet --- # Dataset Card for Evaluation run of TheBloke/Genz-70b-GPTQ ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/TheBloke/Genz-70b-GPTQ - **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 [TheBloke/Genz-70b-GPTQ](https://huggingface.co/TheBloke/Genz-70b-GPTQ) 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_TheBloke__Genz-70b-GPTQ", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-31T00:30:34.342002](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Genz-70b-GPTQ/blob/main/results_2023-08-31T00%3A30%3A34.342002.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": 0.7017249416277331, "acc_stderr": 0.030832772804323012, "acc_norm": 0.70569345061239, "acc_norm_stderr": 0.03080075128019408, "mc1": 0.4320685434516524, "mc1_stderr": 0.01734120239498826, "mc2": 0.6228267270427654, "mc2_stderr": 0.014836432877772263 }, "harness|arc:challenge|25": { "acc": 0.6638225255972696, "acc_stderr": 0.013804855026205763, "acc_norm": 0.7107508532423208, "acc_norm_stderr": 0.013250012579393443 }, "harness|hellaswag|10": { "acc": 0.689205337582155, "acc_stderr": 0.004618730353217047, "acc_norm": 0.8764190400318662, "acc_norm_stderr": 0.0032843028764223 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8223684210526315, "acc_stderr": 0.03110318238312338, "acc_norm": 0.8223684210526315, "acc_norm_stderr": 0.03110318238312338 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.76, "acc_stderr": 0.04292346959909284, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.720754716981132, "acc_stderr": 0.027611163402399715, "acc_norm": 0.720754716981132, "acc_norm_stderr": 0.027611163402399715 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8194444444444444, "acc_stderr": 0.032166008088022675, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.032166008088022675 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "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": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6473988439306358, "acc_stderr": 0.036430371689585475, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.036430371689585475 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.676595744680851, "acc_stderr": 0.030579442773610337, "acc_norm": 0.676595744680851, "acc_norm_stderr": 0.030579442773610337 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.45614035087719296, "acc_stderr": 0.04685473041907789, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.04685473041907789 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6344827586206897, "acc_stderr": 0.04013124195424386, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.04013124195424386 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4417989417989418, "acc_stderr": 0.02557625706125384, "acc_norm": 0.4417989417989418, "acc_norm_stderr": 0.02557625706125384 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677172, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677172 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8290322580645161, "acc_stderr": 0.02141724293632159, "acc_norm": 0.8290322580645161, "acc_norm_stderr": 0.02141724293632159 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066573, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066573 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8686868686868687, "acc_stderr": 0.024063156416822523, "acc_norm": 0.8686868686868687, "acc_norm_stderr": 0.024063156416822523 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240528, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240528 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7051282051282052, "acc_stderr": 0.023119362758232294, "acc_norm": 0.7051282051282052, "acc_norm_stderr": 0.023119362758232294 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.028406533090608463, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.028406533090608463 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.773109243697479, "acc_stderr": 0.027205371538279472, "acc_norm": 0.773109243697479, "acc_norm_stderr": 0.027205371538279472 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.5099337748344371, "acc_stderr": 0.04081677107248437, "acc_norm": 0.5099337748344371, "acc_norm_stderr": 0.04081677107248437 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8917431192660551, "acc_stderr": 0.013321348447611769, "acc_norm": 0.8917431192660551, "acc_norm_stderr": 0.013321348447611769 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.6018518518518519, "acc_stderr": 0.033384734032074016, "acc_norm": 0.6018518518518519, "acc_norm_stderr": 0.033384734032074016 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9313725490196079, "acc_stderr": 0.017744453647073312, "acc_norm": 0.9313725490196079, "acc_norm_stderr": 0.017744453647073312 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.9029535864978903, "acc_stderr": 0.019269323025640262, "acc_norm": 0.9029535864978903, "acc_norm_stderr": 0.019269323025640262 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.8116591928251121, "acc_stderr": 0.026241132996407252, "acc_norm": 0.8116591928251121, "acc_norm_stderr": 0.026241132996407252 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8396946564885496, "acc_stderr": 0.03217829420744633, "acc_norm": 0.8396946564885496, "acc_norm_stderr": 0.03217829420744633 }, "harness|hendrycksTest-international_law|5": { "acc": 0.859504132231405, "acc_stderr": 0.03172233426002157, "acc_norm": 0.859504132231405, "acc_norm_stderr": 0.03172233426002157 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8240740740740741, "acc_stderr": 0.036809181416738807, "acc_norm": 0.8240740740740741, "acc_norm_stderr": 0.036809181416738807 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8159509202453987, "acc_stderr": 0.030446777687971726, "acc_norm": 0.8159509202453987, "acc_norm_stderr": 0.030446777687971726 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5, "acc_stderr": 0.04745789978762494, "acc_norm": 0.5, "acc_norm_stderr": 0.04745789978762494 }, "harness|hendrycksTest-management|5": { "acc": 0.8446601941747572, "acc_stderr": 0.03586594738573974, "acc_norm": 0.8446601941747572, "acc_norm_stderr": 0.03586594738573974 }, "harness|hendrycksTest-marketing|5": { "acc": 0.9102564102564102, "acc_stderr": 0.018724301741941642, "acc_norm": 0.9102564102564102, "acc_norm_stderr": 0.018724301741941642 }, "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": 0.8722860791826309, "acc_stderr": 0.011935626313999876, "acc_norm": 0.8722860791826309, "acc_norm_stderr": 0.011935626313999876 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.8005780346820809, "acc_stderr": 0.021511900654252562, "acc_norm": 0.8005780346820809, "acc_norm_stderr": 0.021511900654252562 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.5754189944134078, "acc_stderr": 0.01653117099327888, "acc_norm": 0.5754189944134078, "acc_norm_stderr": 0.01653117099327888 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7745098039215687, "acc_stderr": 0.02392915551735129, "acc_norm": 0.7745098039215687, "acc_norm_stderr": 0.02392915551735129 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7717041800643086, "acc_stderr": 0.023839303311398205, "acc_norm": 0.7717041800643086, "acc_norm_stderr": 0.023839303311398205 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8487654320987654, "acc_stderr": 0.019935086092149897, "acc_norm": 0.8487654320987654, "acc_norm_stderr": 0.019935086092149897 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5638297872340425, "acc_stderr": 0.029583452036284076, "acc_norm": 0.5638297872340425, "acc_norm_stderr": 0.029583452036284076 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5534550195567145, "acc_stderr": 0.012697046024399654, "acc_norm": 0.5534550195567145, "acc_norm_stderr": 0.012697046024399654 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7389705882352942, "acc_stderr": 0.026679252270103135, "acc_norm": 0.7389705882352942, "acc_norm_stderr": 0.026679252270103135 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7630718954248366, "acc_stderr": 0.017201662169789772, "acc_norm": 0.7630718954248366, "acc_norm_stderr": 0.017201662169789772 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7363636363636363, "acc_stderr": 0.04220224692971987, "acc_norm": 0.7363636363636363, "acc_norm_stderr": 0.04220224692971987 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.8, "acc_stderr": 0.02560737598657916, "acc_norm": 0.8, "acc_norm_stderr": 0.02560737598657916 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8606965174129353, "acc_stderr": 0.024484487162913973, "acc_norm": 0.8606965174129353, "acc_norm_stderr": 0.024484487162913973 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.9, "acc_stderr": 0.030151134457776334, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776334 }, "harness|hendrycksTest-virology|5": { "acc": 0.5180722891566265, "acc_stderr": 0.038899512528272166, "acc_norm": 0.5180722891566265, "acc_norm_stderr": 0.038899512528272166 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8771929824561403, "acc_stderr": 0.025172984350155754, "acc_norm": 0.8771929824561403, "acc_norm_stderr": 0.025172984350155754 }, "harness|truthfulqa:mc|0": { "mc1": 0.4320685434516524, "mc1_stderr": 0.01734120239498826, "mc2": 0.6228267270427654, "mc2_stderr": 0.014836432877772263 } } ``` ### 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]

joey234/mmlu-college_biology-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: 9147.1875 num_examples: 27 download_size: 7857 dataset_size: 9147.1875 --- # Dataset Card for "mmlu-college_biology-original-neg" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

AdapterOcean/med_alpaca_standardized_cluster_59_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: 12541572 num_examples: 23244 download_size: 6485582 dataset_size: 12541572 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_59_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_jeiku__NarrativeNexus_7B

--- pretty_name: Evaluation run of jeiku/NarrativeNexus_7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [jeiku/NarrativeNexus_7B](https://huggingface.co/jeiku/NarrativeNexus_7B) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_jeiku__NarrativeNexus_7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-16T01:30:29.349287](https://huggingface.co/datasets/open-llm-leaderboard/details_jeiku__NarrativeNexus_7B/blob/main/results_2024-02-16T01-30-29.349287.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\": 0.6331502373053775,\n\ \ \"acc_stderr\": 0.032649477056743835,\n \"acc_norm\": 0.6360612367088411,\n\ \ \"acc_norm_stderr\": 0.03330403787596569,\n \"mc1\": 0.46878824969400246,\n\ \ \"mc1_stderr\": 0.017469364874577537,\n \"mc2\": 0.6394506791157332,\n\ \ \"mc2_stderr\": 0.015272071804569947\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6279863481228669,\n \"acc_stderr\": 0.01412459788184446,\n\ \ \"acc_norm\": 0.6612627986348123,\n \"acc_norm_stderr\": 0.01383056892797433\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6773551085441147,\n\ \ \"acc_stderr\": 0.004665327309399188,\n \"acc_norm\": 0.8573989245170285,\n\ \ \"acc_norm_stderr\": 0.003489509493001621\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n\ \ \"acc_stderr\": 0.041716541613545426,\n \"acc_norm\": 0.6296296296296297,\n\ \ \"acc_norm_stderr\": 0.041716541613545426\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\ \ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\ \ \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n \ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322663,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322663\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\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.55,\n \ \ \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6358381502890174,\n\ \ \"acc_stderr\": 0.03669072477416907,\n \"acc_norm\": 0.6358381502890174,\n\ \ \"acc_norm_stderr\": 0.03669072477416907\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\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\": 0.5787234042553191,\n \"acc_stderr\": 0.03227834510146268,\n\ \ \"acc_norm\": 0.5787234042553191,\n \"acc_norm_stderr\": 0.03227834510146268\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.47368421052631576,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.47368421052631576,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5793103448275863,\n \"acc_stderr\": 0.04113914981189261,\n\ \ \"acc_norm\": 0.5793103448275863,\n \"acc_norm_stderr\": 0.04113914981189261\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3888888888888889,\n \"acc_stderr\": 0.025107425481137285,\n \"\ acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.025107425481137285\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677171,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677171\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.7645161290322581,\n \"acc_stderr\": 0.02413763242933771,\n \"\ acc_norm\": 0.7645161290322581,\n \"acc_norm_stderr\": 0.02413763242933771\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n \"\ acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.033175059300091805,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.033175059300091805\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\": 0.8601036269430051,\n \"acc_stderr\": 0.025033870583015184,\n\ \ \"acc_norm\": 0.8601036269430051,\n \"acc_norm_stderr\": 0.025033870583015184\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\": 0.3888888888888889,\n \"acc_stderr\": 0.029723278961476664,\n \ \ \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.029723278961476664\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6848739495798319,\n \"acc_stderr\": 0.030176808288974337,\n\ \ \"acc_norm\": 0.6848739495798319,\n \"acc_norm_stderr\": 0.030176808288974337\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8036697247706422,\n \"acc_stderr\": 0.01703071933915434,\n \"\ acc_norm\": 0.8036697247706422,\n \"acc_norm_stderr\": 0.01703071933915434\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.49074074074074076,\n \"acc_stderr\": 0.03409386946992699,\n \"\ acc_norm\": 0.49074074074074076,\n \"acc_norm_stderr\": 0.03409386946992699\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.028626547912437406,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.028626547912437406\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7552742616033755,\n \"acc_stderr\": 0.027985699387036423,\n \ \ \"acc_norm\": 0.7552742616033755,\n \"acc_norm_stderr\": 0.027985699387036423\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7099236641221374,\n \"acc_stderr\": 0.03980066246467765,\n\ \ \"acc_norm\": 0.7099236641221374,\n \"acc_norm_stderr\": 0.03980066246467765\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7851239669421488,\n \"acc_stderr\": 0.03749492448709695,\n \"\ acc_norm\": 0.7851239669421488,\n \"acc_norm_stderr\": 0.03749492448709695\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\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\": 0.4732142857142857,\n\ \ \"acc_stderr\": 0.047389751192741546,\n \"acc_norm\": 0.4732142857142857,\n\ \ \"acc_norm_stderr\": 0.047389751192741546\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.04354631077260595,\n\ \ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.04354631077260595\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406964,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406964\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8084291187739464,\n\ \ \"acc_stderr\": 0.014072859310451949,\n \"acc_norm\": 0.8084291187739464,\n\ \ \"acc_norm_stderr\": 0.014072859310451949\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.024946792225272314,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.024946792225272314\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4312849162011173,\n\ \ \"acc_stderr\": 0.016563829399047707,\n \"acc_norm\": 0.4312849162011173,\n\ \ \"acc_norm_stderr\": 0.016563829399047707\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7026143790849673,\n \"acc_stderr\": 0.02617390850671858,\n\ \ \"acc_norm\": 0.7026143790849673,\n \"acc_norm_stderr\": 0.02617390850671858\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6945337620578779,\n\ \ \"acc_stderr\": 0.026160584450140453,\n \"acc_norm\": 0.6945337620578779,\n\ \ \"acc_norm_stderr\": 0.026160584450140453\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6882716049382716,\n \"acc_stderr\": 0.025773111169630457,\n\ \ \"acc_norm\": 0.6882716049382716,\n \"acc_norm_stderr\": 0.025773111169630457\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4397163120567376,\n \"acc_stderr\": 0.02960991207559411,\n \ \ \"acc_norm\": 0.4397163120567376,\n \"acc_norm_stderr\": 0.02960991207559411\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4576271186440678,\n\ \ \"acc_stderr\": 0.012724296550980188,\n \"acc_norm\": 0.4576271186440678,\n\ \ \"acc_norm_stderr\": 0.012724296550980188\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\": 0.6160130718954249,\n \"acc_stderr\": 0.019675808135281508,\n \ \ \"acc_norm\": 0.6160130718954249,\n \"acc_norm_stderr\": 0.019675808135281508\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6909090909090909,\n\ \ \"acc_stderr\": 0.044262946482000985,\n \"acc_norm\": 0.6909090909090909,\n\ \ \"acc_norm_stderr\": 0.044262946482000985\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.029504896454595957,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.029504896454595957\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8507462686567164,\n\ \ \"acc_stderr\": 0.02519692987482707,\n \"acc_norm\": 0.8507462686567164,\n\ \ \"acc_norm_stderr\": 0.02519692987482707\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4879518072289157,\n\ \ \"acc_stderr\": 0.0389136449583582,\n \"acc_norm\": 0.4879518072289157,\n\ \ \"acc_norm_stderr\": 0.0389136449583582\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8421052631578947,\n \"acc_stderr\": 0.027966785859160882,\n\ \ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.027966785859160882\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.46878824969400246,\n\ \ \"mc1_stderr\": 0.017469364874577537,\n \"mc2\": 0.6394506791157332,\n\ \ \"mc2_stderr\": 0.015272071804569947\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7900552486187845,\n \"acc_stderr\": 0.01144628062926263\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.5178165276724791,\n \ \ \"acc_stderr\": 0.013763738379867933\n }\n}\n```" repo_url: https://huggingface.co/jeiku/NarrativeNexus_7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|arc:challenge|25_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-16T01-30-29.349287.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|gsm8k|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hellaswag|10_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-16T01-30-29.349287.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-management|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T01-30-29.349287.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|truthfulqa:mc|0_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-16T01-30-29.349287.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_16T01_30_29.349287 path: - '**/details_harness|winogrande|5_2024-02-16T01-30-29.349287.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-16T01-30-29.349287.parquet' - config_name: results data_files: - split: 2024_02_16T01_30_29.349287 path: - results_2024-02-16T01-30-29.349287.parquet - split: latest path: - results_2024-02-16T01-30-29.349287.parquet --- # Dataset Card for Evaluation run of jeiku/NarrativeNexus_7B  Dataset automatically created during the evaluation run of model [jeiku/NarrativeNexus_7B](https://huggingface.co/jeiku/NarrativeNexus_7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_jeiku__NarrativeNexus_7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-16T01:30:29.349287](https://huggingface.co/datasets/open-llm-leaderboard/details_jeiku__NarrativeNexus_7B/blob/main/results_2024-02-16T01-30-29.349287.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": 0.6331502373053775, "acc_stderr": 0.032649477056743835, "acc_norm": 0.6360612367088411, "acc_norm_stderr": 0.03330403787596569, "mc1": 0.46878824969400246, "mc1_stderr": 0.017469364874577537, "mc2": 0.6394506791157332, "mc2_stderr": 0.015272071804569947 }, "harness|arc:challenge|25": { "acc": 0.6279863481228669, "acc_stderr": 0.01412459788184446, "acc_norm": 0.6612627986348123, "acc_norm_stderr": 0.01383056892797433 }, "harness|hellaswag|10": { "acc": 0.6773551085441147, "acc_stderr": 0.004665327309399188, "acc_norm": 0.8573989245170285, "acc_norm_stderr": 0.003489509493001621 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6296296296296297, "acc_stderr": 0.041716541613545426, "acc_norm": 0.6296296296296297, "acc_norm_stderr": 0.041716541613545426 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6776315789473685, "acc_stderr": 0.03803510248351585, "acc_norm": 0.6776315789473685, "acc_norm_stderr": 0.03803510248351585 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6943396226415094, "acc_stderr": 0.028353298073322663, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322663 }, "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": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6358381502890174, "acc_stderr": 0.03669072477416907, "acc_norm": 0.6358381502890174, "acc_norm_stderr": 0.03669072477416907 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "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": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.47368421052631576, "acc_stderr": 0.046970851366478626, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.046970851366478626 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5793103448275863, "acc_stderr": 0.04113914981189261, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.04113914981189261 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.025107425481137285, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.025107425481137285 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677171, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677171 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7645161290322581, "acc_stderr": 0.02413763242933771, "acc_norm": 0.7645161290322581, "acc_norm_stderr": 0.02413763242933771 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7636363636363637, "acc_stderr": 0.033175059300091805, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.033175059300091805 }, "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": 0.8601036269430051, "acc_stderr": 0.025033870583015184, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015184 }, "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": 0.3888888888888889, "acc_stderr": 0.029723278961476664, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.029723278961476664 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6848739495798319, "acc_stderr": 0.030176808288974337, "acc_norm": 0.6848739495798319, "acc_norm_stderr": 0.030176808288974337 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8036697247706422, "acc_stderr": 0.01703071933915434, "acc_norm": 0.8036697247706422, "acc_norm_stderr": 0.01703071933915434 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.49074074074074076, "acc_stderr": 0.03409386946992699, "acc_norm": 0.49074074074074076, "acc_norm_stderr": 0.03409386946992699 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7892156862745098, "acc_stderr": 0.028626547912437406, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.028626547912437406 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7552742616033755, "acc_stderr": 0.027985699387036423, "acc_norm": 0.7552742616033755, "acc_norm_stderr": 0.027985699387036423 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7099236641221374, "acc_stderr": 0.03980066246467765, "acc_norm": 0.7099236641221374, "acc_norm_stderr": 0.03980066246467765 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7851239669421488, "acc_stderr": 0.03749492448709695, "acc_norm": 0.7851239669421488, "acc_norm_stderr": 0.03749492448709695 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "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": 0.4732142857142857, "acc_stderr": 0.047389751192741546, "acc_norm": 0.4732142857142857, "acc_norm_stderr": 0.047389751192741546 }, "harness|hendrycksTest-management|5": { "acc": 0.7378640776699029, "acc_stderr": 0.04354631077260595, "acc_norm": 0.7378640776699029, "acc_norm_stderr": 0.04354631077260595 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406964, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406964 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8084291187739464, "acc_stderr": 0.014072859310451949, "acc_norm": 0.8084291187739464, "acc_norm_stderr": 0.014072859310451949 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6878612716763006, "acc_stderr": 0.024946792225272314, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.024946792225272314 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4312849162011173, "acc_stderr": 0.016563829399047707, "acc_norm": 0.4312849162011173, "acc_norm_stderr": 0.016563829399047707 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7026143790849673, "acc_stderr": 0.02617390850671858, "acc_norm": 0.7026143790849673, "acc_norm_stderr": 0.02617390850671858 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6945337620578779, "acc_stderr": 0.026160584450140453, "acc_norm": 0.6945337620578779, "acc_norm_stderr": 0.026160584450140453 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6882716049382716, "acc_stderr": 0.025773111169630457, "acc_norm": 0.6882716049382716, "acc_norm_stderr": 0.025773111169630457 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4397163120567376, "acc_stderr": 0.02960991207559411, "acc_norm": 0.4397163120567376, "acc_norm_stderr": 0.02960991207559411 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4576271186440678, "acc_stderr": 0.012724296550980188, "acc_norm": 0.4576271186440678, "acc_norm_stderr": 0.012724296550980188 }, "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": 0.6160130718954249, "acc_stderr": 0.019675808135281508, "acc_norm": 0.6160130718954249, "acc_norm_stderr": 0.019675808135281508 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6909090909090909, "acc_stderr": 0.044262946482000985, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.044262946482000985 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6938775510204082, "acc_stderr": 0.029504896454595957, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.029504896454595957 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8507462686567164, "acc_stderr": 0.02519692987482707, "acc_norm": 0.8507462686567164, "acc_norm_stderr": 0.02519692987482707 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.87, "acc_stderr": 0.03379976689896309, "acc_norm": 0.87, "acc_norm_stderr": 0.03379976689896309 }, "harness|hendrycksTest-virology|5": { "acc": 0.4879518072289157, "acc_stderr": 0.0389136449583582, "acc_norm": 0.4879518072289157, "acc_norm_stderr": 0.0389136449583582 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8421052631578947, "acc_stderr": 0.027966785859160882, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.027966785859160882 }, "harness|truthfulqa:mc|0": { "mc1": 0.46878824969400246, "mc1_stderr": 0.017469364874577537, "mc2": 0.6394506791157332, "mc2_stderr": 0.015272071804569947 }, "harness|winogrande|5": { "acc": 0.7900552486187845, "acc_stderr": 0.01144628062926263 }, "harness|gsm8k|5": { "acc": 0.5178165276724791, "acc_stderr": 0.013763738379867933 } } ``` ## Dataset Details ### Dataset Description  - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

CyberHarem/spitfire_girlsfrontline

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of spitfire/Spitfire/喷火 (Girls' Frontline) This is the dataset of spitfire/Spitfire/喷火 (Girls' Frontline), containing 15 images and their tags. The core tags of this character are `long_hair, hat, green_eyes, top_hat, grey_hair, breasts, bangs, 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 | 15 | 20.18 MiB | [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 15 | 11.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 34 | 22.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 15 | 18.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 34 | 30.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/spitfire_girlsfrontline/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/spitfire_girlsfrontline', 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 | 12 | ![](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, looking_at_viewer, solo, black_gloves, dress, belt, handgun, necktie, bare_shoulders, boots, brown_hair, holding_gun, official_alternate_costume, pantyhose, small_breasts, thighhighs | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | solo | black_gloves | dress | belt | handgun | necktie | bare_shoulders | boots | brown_hair | holding_gun | official_alternate_costume | pantyhose | small_breasts | thighhighs | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:---------------|:--------|:-------|:----------|:----------|:-----------------|:--------|:-------------|:--------------|:-----------------------------|:------------|:----------------|:-------------| | 0 | 12 | ![](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 |

CyberHarem/moriyama_shiemi

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Moriyama Shiemi (青の祓魔師) This is the dataset of Moriyama Shiemi (青の祓魔師), containing 258 images and their tags. The core tags of this character are `blonde_hair, short_hair, green_eyes, hair_ornament, hair_flower, hairband`, 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 | 258 | 198.76 MiB | [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 258 | 160.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 434 | 266.06 MiB | [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 258 | 190.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 434 | 309.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/moriyama_shiemi/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/moriyama_shiemi', 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 | 13 | ![](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, school_uniform, skirt, solo, smile, flower, open_mouth, blush, bow, white_thighhighs, zettai_ryouiki | | 1 | 5 | ![](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, bow, open_mouth, smile, solo, school_uniform, hair_ribbon, ahoge, aqua_eyes, necktie | | 2 | 18 | ![](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, flower, kimono, smile, solo, open_mouth, blush | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | school_uniform | skirt | solo | smile | flower | open_mouth | blush | bow | white_thighhighs | zettai_ryouiki | hair_ribbon | ahoge | aqua_eyes | necktie | kimono | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------------|:--------|:-------|:--------|:---------|:-------------|:--------|:------|:-------------------|:-----------------|:--------------|:--------|:------------|:----------|:---------| | 0 | 13 | ![](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 | | | | | | | 1 | 5 | ![](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 | | | 2 | 18 | ![](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 |

irds/neumarco_fa_dev_judged

--- pretty_name: '`neumarco/fa/dev/judged`' viewer: false source_datasets: ['irds/neumarco_fa', 'irds/neumarco_fa_dev'] task_categories: - text-retrieval --- # Dataset Card for `neumarco/fa/dev/judged` The `neumarco/fa/dev/judged` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/neumarco#neumarco/fa/dev/judged). # Data This dataset provides: - `queries` (i.e., topics); count=55,578 - For `docs`, use [`irds/neumarco_fa`](https://huggingface.co/datasets/irds/neumarco_fa) - For `qrels`, use [`irds/neumarco_fa_dev`](https://huggingface.co/datasets/irds/neumarco_fa_dev) ## Usage ```python from datasets import load_dataset queries = load_dataset('irds/neumarco_fa_dev_judged', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} ``` 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.

jp1924/JeollaSpeech

--- dataset_info: features: - name: id dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: standard_form dtype: string - name: dialect_form dtype: string - name: start dtype: float32 - name: end dtype: float32 - name: note dtype: string - name: eojeolList list: - name: id dtype: int8 - name: eojeol dtype: string - name: standard dtype: string - name: isDialect dtype: bool - name: speaker struct: - name: id dtype: string - name: name dtype: string - name: age dtype: string - name: occupation dtype: string - name: sex dtype: string - name: birthplace dtype: string - name: principal_residence dtype: string - name: current_residence dtype: string - name: education dtype: string - name: metadata struct: - name: title dtype: string - name: creator dtype: string - name: distributor dtype: string - name: year dtype: string - name: category dtype: string - name: annotation_level list: string - name: sampling dtype: string - name: author dtype: string - name: publisher dtype: string - name: date dtype: string - name: topic dtype: string splits: - name: train num_bytes: 520213137698.024 num_examples: 1988867 - name: validation num_bytes: 61448267920.464 num_examples: 275137 download_size: 557887316021 dataset_size: 581661405618.488 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

yzhuang/autotree_pmlb_10000_Hill_Valley_without_noise_sgosdt_l256_dim10_d3_sd0

--- dataset_info: features: - name: id dtype: int64 - name: input_x sequence: sequence: float32 - name: input_y sequence: sequence: float32 - name: input_y_clean sequence: sequence: float32 - name: rtg sequence: float64 - name: status sequence: sequence: float32 - name: split_threshold sequence: sequence: float32 - name: split_dimension sequence: int64 splits: - name: train num_bytes: 236440000 num_examples: 10000 - name: validation num_bytes: 236440000 num_examples: 10000 download_size: 179483399 dataset_size: 472880000 --- # Dataset Card for "autotree_pmlb_10000_Hill_Valley_without_noise_sgosdt_l256_dim10_d3_sd0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/yoroizuka_mizore_soundeuphonium

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Yoroizuka Mizore/鎧塚みぞれ/铠冢霙/のぞみぞ (Sound! Euphonium) This is the dataset of Yoroizuka Mizore/鎧塚みぞれ/铠冢霙/のぞみぞ (Sound! Euphonium), containing 228 images and their tags. The core tags of this character are `long_hair, blue_hair, red_eyes, black_hair`, 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 | 228 | 159.21 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 228 | 159.12 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 400 | 267.41 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yoroizuka_mizore_soundeuphonium/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/yoroizuka_mizore_soundeuphonium', 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 | 6 | ![](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, blue_sailor_collar, blurry_background, blush, kitauji_high_school_uniform, outdoors, serafuku, solo, white_shirt, blue_neckerchief, blue_skirt, closed_mouth, pleated_skirt, school_bag, short_sleeves, standing, tree, black_bag, looking_to_the_side | | 1 | 15 | ![](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) | blush, kitauji_high_school_uniform, serafuku, 1girl, blue_sailor_collar, white_shirt, solo, indoors, parted_lips, open_mouth, blurry_background, closed_mouth, window | | 2 | 12 | ![](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) | blue_sailor_collar, blush, kitauji_high_school_uniform, serafuku, white_shirt, 2girls, neckerchief, closed_mouth, looking_at_viewer, solo_focus, blurry | | 3 | 11 | ![](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) | blue_neckerchief, blue_sailor_collar, kitauji_high_school_uniform, serafuku, short_sleeves, white_shirt, 2girls, blue_skirt, blush, indoors, pleated_skirt, brown_hair, chair, closed_mouth, sitting, solo_focus, classroom, instrument | | 4 | 5 | ![](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, blue_neckerchief, blue_sailor_collar, blush, chair, classroom, from_side, indoors, kitauji_high_school_uniform, serafuku, solo, white_shirt, window, closed_mouth, short_sleeves, sitting, blurry, flute, holding_instrument | | 5 | 30 | ![](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) | kitauji_high_school_uniform, serafuku, 1girl, solo, white_sailor_collar, holding_instrument, brown_shirt, long_sleeves, playing_instrument, closed_mouth, blurry_background, blue_neckerchief | | 6 | 5 | ![](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, brown_shirt, brown_skirt, holding_instrument, kitauji_high_school_uniform, long_sleeves, pleated_skirt, serafuku, standing, white_sailor_collar, solo, blue_neckerchief, blush, from_side | | 7 | 10 | ![](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) | blush, brown_shirt, closed_mouth, kitauji_high_school_uniform, serafuku, solo_focus, white_sailor_collar, blue_neckerchief, 2girls, long_sleeves, brown_skirt, blurry_background, pleated_skirt, sitting, socks | | 8 | 12 | ![](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) | blush, school_uniform, 1girl, collared_shirt, green_jacket, red_bowtie, solo, white_shirt, closed_mouth, blazer, long_sleeves, looking_at_viewer | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_sailor_collar | blurry_background | blush | kitauji_high_school_uniform | outdoors | serafuku | solo | white_shirt | blue_neckerchief | blue_skirt | closed_mouth | pleated_skirt | school_bag | short_sleeves | standing | tree | black_bag | looking_to_the_side | indoors | parted_lips | open_mouth | window | 2girls | neckerchief | looking_at_viewer | solo_focus | blurry | brown_hair | chair | sitting | classroom | instrument | from_side | flute | holding_instrument | white_sailor_collar | brown_shirt | long_sleeves | playing_instrument | brown_skirt | socks | school_uniform | collared_shirt | green_jacket | red_bowtie | blazer | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------------|:--------------------|:--------|:------------------------------|:-----------|:-----------|:-------|:--------------|:-------------------|:-------------|:---------------|:----------------|:-------------|:----------------|:-----------|:-------|:------------|:----------------------|:----------|:--------------|:-------------|:---------|:---------|:--------------|:--------------------|:-------------|:---------|:-------------|:--------|:----------|:------------|:-------------|:------------|:--------|:---------------------|:----------------------|:--------------|:---------------|:---------------------|:--------------|:--------|:-----------------|:-----------------|:---------------|:-------------|:---------| | 0 | 6 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 15 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 12 | ![](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 | | | | | | | | | | | | | | | | | | | | | 3 | 11 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | | X | | X | X | | X | | X | X | X | X | X | | X | | | | | X | | | | X | | | X | | X | X | X | X | X | | | | | | | | | | | | | | | | 4 | 5 | ![](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 | | | | | | | | | | | | | 5 | 30 | ![](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 | | | | | | | | | 6 | 5 | ![](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 | | | | | | | | 7 | 10 | ![](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 | | | | | | | 8 | 12 | ![](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 |

chrisjay/crowd-speech-africa

--- extra_gated_prompt: "You agree to not attempt to determine the identity of individuals in this dataset" extra_gated_fields: Name: text Affiliation: text Email: text I agree to not attempt to determine the identity of speakers in this dataset: checkbox ---

ai-aerospace/ams_data_train_mistral_v0.1_100

--- license: apache-2.0 base-model: TheBloke/Llama-2-7B-Chat-GGUF --- Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF Format representative of mistral's instruct llms: * https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 * Example dataset: https://huggingface.co/datasets/centroIA/MistralInstructScenarios `<s>[INST] {prompt} [/INST]`

NicholasSynovic/Free-AutoTrain-VEAA

--- license: agpl-3.0 task_categories: - text-classification language: - en pretty_name: Victorian Era Authorship Attribution Data Set (For Free AutoTrain Account) size_categories: - 1K<n<10K source_datasets: - NicholasSynovic/Victorian-Era-Authorship-Attribution --- # Free AutoTrain VEAA > Victorian Era Authorship Attribution Data Set (For Free AutoTrain Account) ## About See the [original HF-hosted dataset](https://huggingface.co/datasets/NicholasSynovic/Victorian-Era-Authorship-Attribution) for more information. The code to generate this dataset came from this [GitHub Repo](https://github.com/NicholasSynovic/nlp-victorianAuthor).

gmongaras/BERT_Base_Cased_512_Dataset_Mapped

--- dataset_info: features: - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 52875464012.02522 num_examples: 136226984 download_size: 17583618282 dataset_size: 52875464012.02522 configs: - config_name: default data_files: - split: train path: data/train-* --- Dataset using the bert-cased tokenizer, cutoff sentences to 512 length (not sentence pairs), all sentence pairs extracted. Original datasets: https://huggingface.co/datasets/bookcorpus https://huggingface.co/datasets/wikipedia Variant: 20220301.en Mapped from: https://huggingface.co/datasets/gmongaras/BERT_Base_Cased_512_Dataset

results-sd-v1-5-sd-v2-1-if-v1-0-karlo/245282ee

--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 182 num_examples: 10 download_size: 1331 dataset_size: 182 --- # Dataset Card for "245282ee" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/linde_fireemblem

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of linde (Fire Emblem) This is the dataset of linde (Fire Emblem), containing 168 images and their tags. The core tags of this character are `brown_hair, long_hair, ponytail, brown_eyes, breasts, very_long_hair, large_breasts`, 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 | 168 | 187.80 MiB | [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 168 | 116.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 378 | 232.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 168 | 170.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 378 | 310.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/linde_fireemblem/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/linde_fireemblem', 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 | 26 | ![](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, solo, circlet, looking_at_viewer, cleavage, navel, smile, blush, hair_ornament, pink_bikini, open_mouth, simple_background | | 1 | 5 | ![](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, circlet, earrings, solo, blush, open_mouth, smile, looking_at_viewer, nipples, one_eye_closed | | 2 | 9 | ![](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, circlet, solo, smile, looking_at_viewer, bare_shoulders, blush, armlet, cleavage, open_mouth, pink_dress, medium_breasts | | 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, bare_shoulders, belt, full_body, hair_ornament, knee_boots, medium_breasts, side_slit, solo, white_dress, white_footwear, absurdly_long_hair, bangs, blush, collarbone, jewelry, long_dress, open_mouth, simple_background, sleeveless_dress, thighs, white_background, circlet, holding_book, leg_up, :d, armpits, hand_up, looking_at_viewer, open_book, pelvic_curtain | | 4 | 25 | ![](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, hetero, nipples, solo_focus, penis, blush, 1boy, sex, open_mouth, vaginal, circlet, mosaic_censoring, cum_in_pussy, spread_legs, nude, cum_on_body, facial, navel, tears | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | circlet | looking_at_viewer | cleavage | navel | smile | blush | hair_ornament | pink_bikini | open_mouth | simple_background | earrings | nipples | one_eye_closed | bare_shoulders | armlet | pink_dress | medium_breasts | belt | full_body | knee_boots | side_slit | white_dress | white_footwear | absurdly_long_hair | bangs | collarbone | jewelry | long_dress | sleeveless_dress | thighs | white_background | holding_book | leg_up | :d | armpits | hand_up | open_book | pelvic_curtain | hetero | solo_focus | penis | 1boy | sex | vaginal | mosaic_censoring | cum_in_pussy | spread_legs | nude | cum_on_body | facial | tears | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:----------|:--------------------|:-----------|:--------|:--------|:--------|:----------------|:--------------|:-------------|:--------------------|:-----------|:----------|:-----------------|:-----------------|:---------|:-------------|:-----------------|:-------|:------------|:-------------|:------------|:--------------|:-----------------|:---------------------|:--------|:-------------|:----------|:-------------|:-------------------|:---------|:-------------------|:---------------|:---------|:-----|:----------|:----------|:------------|:-----------------|:---------|:-------------|:--------|:-------|:------|:----------|:-------------------|:---------------|:--------------|:-------|:--------------|:---------|:--------| | 0 | 26 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 5 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 9 | ![](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 | 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 | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | 4 | 25 | ![](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 |

zirui3/cuad-instructions

--- license: cc-by-4.0 dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: text sequence: string - name: answer_start sequence: int64 - name: instruction dtype: string splits: - name: train num_bytes: 2933858226 num_examples: 44900 - name: test num_bytes: 397434014 num_examples: 8364 download_size: 6827533 dataset_size: 3331292240 ---

ChristophSchuhmann/OpenClip-B32-KNN-Captioner

--- license: apache-2.0 ---

KoziCreative/Testing

--- license: afl-3.0 ---

colkassad/map_navigation_v1

--- license: mit ---

open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1

--- pretty_name: Evaluation run of logicker/SkkuDS-DPO-72B-v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [logicker/SkkuDS-DPO-72B-v1](https://huggingface.co/logicker/SkkuDS-DPO-72B-v1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-16T10:55:52.095277](https://huggingface.co/datasets/open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1/blob/main/results_2024-02-16T10-55-52.095277.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\": 0.7681185312998495,\n\ \ \"acc_stderr\": 0.02797672385731024,\n \"acc_norm\": 0.7728008468755523,\n\ \ \"acc_norm_stderr\": 0.02849748439769033,\n \"mc1\": 0.41370869033047736,\n\ \ \"mc1_stderr\": 0.0172408618120998,\n \"mc2\": 0.595432675425976,\n\ \ \"mc2_stderr\": 0.014511387340720846\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6271331058020477,\n \"acc_stderr\": 0.014131176760131172,\n\ \ \"acc_norm\": 0.659556313993174,\n \"acc_norm_stderr\": 0.013847460518892978\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6671977693686517,\n\ \ \"acc_stderr\": 0.004702533775930293,\n \"acc_norm\": 0.8599880501892053,\n\ \ \"acc_norm_stderr\": 0.0034629026011361893\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.7333333333333333,\n\ \ \"acc_stderr\": 0.038201699145179055,\n \"acc_norm\": 0.7333333333333333,\n\ \ \"acc_norm_stderr\": 0.038201699145179055\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.881578947368421,\n \"acc_stderr\": 0.026293995855474928,\n\ \ \"acc_norm\": 0.881578947368421,\n \"acc_norm_stderr\": 0.026293995855474928\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.8,\n\ \ \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.8,\n \ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.8226415094339623,\n \"acc_stderr\": 0.023508739218846934,\n\ \ \"acc_norm\": 0.8226415094339623,\n \"acc_norm_stderr\": 0.023508739218846934\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.9166666666666666,\n\ \ \"acc_stderr\": 0.023112508176051236,\n \"acc_norm\": 0.9166666666666666,\n\ \ \"acc_norm_stderr\": 0.023112508176051236\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.65,\n \"acc_stderr\": 0.04793724854411019,\n \"acc_norm\": 0.65,\n\ \ \"acc_norm_stderr\": 0.04793724854411019\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.7514450867052023,\n\ \ \"acc_stderr\": 0.03295304696818317,\n \"acc_norm\": 0.7514450867052023,\n\ \ \"acc_norm_stderr\": 0.03295304696818317\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.5490196078431373,\n \"acc_stderr\": 0.049512182523962604,\n\ \ \"acc_norm\": 0.5490196078431373,\n \"acc_norm_stderr\": 0.049512182523962604\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\ \ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.8042553191489362,\n \"acc_stderr\": 0.025937853139977148,\n\ \ \"acc_norm\": 0.8042553191489362,\n \"acc_norm_stderr\": 0.025937853139977148\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5877192982456141,\n\ \ \"acc_stderr\": 0.046306532033665956,\n \"acc_norm\": 0.5877192982456141,\n\ \ \"acc_norm_stderr\": 0.046306532033665956\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.7862068965517242,\n \"acc_stderr\": 0.03416520447747549,\n\ \ \"acc_norm\": 0.7862068965517242,\n \"acc_norm_stderr\": 0.03416520447747549\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.7116402116402116,\n \"acc_stderr\": 0.02333065405453588,\n \"\ acc_norm\": 0.7116402116402116,\n \"acc_norm_stderr\": 0.02333065405453588\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5952380952380952,\n\ \ \"acc_stderr\": 0.04390259265377563,\n \"acc_norm\": 0.5952380952380952,\n\ \ \"acc_norm_stderr\": 0.04390259265377563\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.8838709677419355,\n \"acc_stderr\": 0.018225757949432306,\n \"\ acc_norm\": 0.8838709677419355,\n \"acc_norm_stderr\": 0.018225757949432306\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.6551724137931034,\n \"acc_stderr\": 0.03344283744280459,\n \"\ acc_norm\": 0.6551724137931034,\n \"acc_norm_stderr\": 0.03344283744280459\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.83,\n \"acc_stderr\": 0.03775251680686371,\n \"acc_norm\"\ : 0.83,\n \"acc_norm_stderr\": 0.03775251680686371\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8545454545454545,\n \"acc_stderr\": 0.027530196355066573,\n\ \ \"acc_norm\": 0.8545454545454545,\n \"acc_norm_stderr\": 0.027530196355066573\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.9343434343434344,\n \"acc_stderr\": 0.01764652667723333,\n \"\ acc_norm\": 0.9343434343434344,\n \"acc_norm_stderr\": 0.01764652667723333\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9896373056994818,\n \"acc_stderr\": 0.007308424386792194,\n\ \ \"acc_norm\": 0.9896373056994818,\n \"acc_norm_stderr\": 0.007308424386792194\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.8153846153846154,\n \"acc_stderr\": 0.01967163241310029,\n \ \ \"acc_norm\": 0.8153846153846154,\n \"acc_norm_stderr\": 0.01967163241310029\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.030485538042484616,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.030485538042484616\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\ : {\n \"acc\": 0.8445378151260504,\n \"acc_stderr\": 0.023536818625398904,\n\ \ \"acc_norm\": 0.8445378151260504,\n \"acc_norm_stderr\": 0.023536818625398904\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.5562913907284768,\n \"acc_stderr\": 0.04056527902281732,\n \"\ acc_norm\": 0.5562913907284768,\n \"acc_norm_stderr\": 0.04056527902281732\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.926605504587156,\n \"acc_stderr\": 0.011180976446357573,\n \"\ acc_norm\": 0.926605504587156,\n \"acc_norm_stderr\": 0.011180976446357573\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.6990740740740741,\n \"acc_stderr\": 0.03128039084329883,\n \"\ acc_norm\": 0.6990740740740741,\n \"acc_norm_stderr\": 0.03128039084329883\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073322,\n \"\ acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073322\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640273,\n \ \ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640273\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7982062780269058,\n\ \ \"acc_stderr\": 0.026936111912802273,\n \"acc_norm\": 0.7982062780269058,\n\ \ \"acc_norm_stderr\": 0.026936111912802273\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8702290076335878,\n \"acc_stderr\": 0.029473649496907065,\n\ \ \"acc_norm\": 0.8702290076335878,\n \"acc_norm_stderr\": 0.029473649496907065\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.9090909090909091,\n \"acc_stderr\": 0.026243194054073892,\n \"\ acc_norm\": 0.9090909090909091,\n \"acc_norm_stderr\": 0.026243194054073892\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8518518518518519,\n\ \ \"acc_stderr\": 0.03434300243630999,\n \"acc_norm\": 0.8518518518518519,\n\ \ \"acc_norm_stderr\": 0.03434300243630999\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8711656441717791,\n \"acc_stderr\": 0.02632138319878367,\n\ \ \"acc_norm\": 0.8711656441717791,\n \"acc_norm_stderr\": 0.02632138319878367\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.6607142857142857,\n\ \ \"acc_stderr\": 0.044939490686135404,\n \"acc_norm\": 0.6607142857142857,\n\ \ \"acc_norm_stderr\": 0.044939490686135404\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8640776699029126,\n \"acc_stderr\": 0.03393295729761011,\n\ \ \"acc_norm\": 0.8640776699029126,\n \"acc_norm_stderr\": 0.03393295729761011\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9401709401709402,\n\ \ \"acc_stderr\": 0.015537514263253874,\n \"acc_norm\": 0.9401709401709402,\n\ \ \"acc_norm_stderr\": 0.015537514263253874\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.86,\n \"acc_stderr\": 0.034873508801977725,\n \ \ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.034873508801977725\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.9144316730523627,\n\ \ \"acc_stderr\": 0.010002965568647285,\n \"acc_norm\": 0.9144316730523627,\n\ \ \"acc_norm_stderr\": 0.010002965568647285\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.8352601156069365,\n \"acc_stderr\": 0.019971040982442262,\n\ \ \"acc_norm\": 0.8352601156069365,\n \"acc_norm_stderr\": 0.019971040982442262\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.6424581005586593,\n\ \ \"acc_stderr\": 0.01602939447489489,\n \"acc_norm\": 0.6424581005586593,\n\ \ \"acc_norm_stderr\": 0.01602939447489489\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.8562091503267973,\n \"acc_stderr\": 0.020091188936043728,\n\ \ \"acc_norm\": 0.8562091503267973,\n \"acc_norm_stderr\": 0.020091188936043728\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.8295819935691319,\n\ \ \"acc_stderr\": 0.02135534302826405,\n \"acc_norm\": 0.8295819935691319,\n\ \ \"acc_norm_stderr\": 0.02135534302826405\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8611111111111112,\n \"acc_stderr\": 0.01924252622654454,\n\ \ \"acc_norm\": 0.8611111111111112,\n \"acc_norm_stderr\": 0.01924252622654454\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.624113475177305,\n \"acc_stderr\": 0.028893955412115882,\n \ \ \"acc_norm\": 0.624113475177305,\n \"acc_norm_stderr\": 0.028893955412115882\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.6140808344198174,\n\ \ \"acc_stderr\": 0.012433398911476134,\n \"acc_norm\": 0.6140808344198174,\n\ \ \"acc_norm_stderr\": 0.012433398911476134\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.8198529411764706,\n \"acc_stderr\": 0.023345163616544838,\n\ \ \"acc_norm\": 0.8198529411764706,\n \"acc_norm_stderr\": 0.023345163616544838\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.8088235294117647,\n \"acc_stderr\": 0.015908290136278067,\n \ \ \"acc_norm\": 0.8088235294117647,\n \"acc_norm_stderr\": 0.015908290136278067\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7363636363636363,\n\ \ \"acc_stderr\": 0.04220224692971987,\n \"acc_norm\": 0.7363636363636363,\n\ \ \"acc_norm_stderr\": 0.04220224692971987\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.8326530612244898,\n \"acc_stderr\": 0.02389714476891452,\n\ \ \"acc_norm\": 0.8326530612244898,\n \"acc_norm_stderr\": 0.02389714476891452\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.022076326101824667,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.022076326101824667\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.94,\n \"acc_stderr\": 0.023868325657594194,\n \ \ \"acc_norm\": 0.94,\n \"acc_norm_stderr\": 0.023868325657594194\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.572289156626506,\n\ \ \"acc_stderr\": 0.03851597683718533,\n \"acc_norm\": 0.572289156626506,\n\ \ \"acc_norm_stderr\": 0.03851597683718533\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8888888888888888,\n \"acc_stderr\": 0.024103384202072864,\n\ \ \"acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.024103384202072864\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.41370869033047736,\n\ \ \"mc1_stderr\": 0.0172408618120998,\n \"mc2\": 0.595432675425976,\n\ \ \"mc2_stderr\": 0.014511387340720846\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8263614838200474,\n \"acc_stderr\": 0.010646116480330996\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6588324488248674,\n \ \ \"acc_stderr\": 0.013059111935831497\n }\n}\n```" repo_url: https://huggingface.co/logicker/SkkuDS-DPO-72B-v1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|arc:challenge|25_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-16T10-55-52.095277.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|gsm8k|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hellaswag|10_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-16T10-55-52.095277.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-management|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-16T10-55-52.095277.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|truthfulqa:mc|0_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-16T10-55-52.095277.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_16T10_55_52.095277 path: - '**/details_harness|winogrande|5_2024-02-16T10-55-52.095277.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-16T10-55-52.095277.parquet' - config_name: results data_files: - split: 2024_02_16T10_55_52.095277 path: - results_2024-02-16T10-55-52.095277.parquet - split: latest path: - results_2024-02-16T10-55-52.095277.parquet --- # Dataset Card for Evaluation run of logicker/SkkuDS-DPO-72B-v1  Dataset automatically created during the evaluation run of model [logicker/SkkuDS-DPO-72B-v1](https://huggingface.co/logicker/SkkuDS-DPO-72B-v1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-16T10:55:52.095277](https://huggingface.co/datasets/open-llm-leaderboard/details_logicker__SkkuDS-DPO-72B-v1/blob/main/results_2024-02-16T10-55-52.095277.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": 0.7681185312998495, "acc_stderr": 0.02797672385731024, "acc_norm": 0.7728008468755523, "acc_norm_stderr": 0.02849748439769033, "mc1": 0.41370869033047736, "mc1_stderr": 0.0172408618120998, "mc2": 0.595432675425976, "mc2_stderr": 0.014511387340720846 }, "harness|arc:challenge|25": { "acc": 0.6271331058020477, "acc_stderr": 0.014131176760131172, "acc_norm": 0.659556313993174, "acc_norm_stderr": 0.013847460518892978 }, "harness|hellaswag|10": { "acc": 0.6671977693686517, "acc_stderr": 0.004702533775930293, "acc_norm": 0.8599880501892053, "acc_norm_stderr": 0.0034629026011361893 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7333333333333333, "acc_stderr": 0.038201699145179055, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.038201699145179055 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.881578947368421, "acc_stderr": 0.026293995855474928, "acc_norm": 0.881578947368421, "acc_norm_stderr": 0.026293995855474928 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8226415094339623, "acc_stderr": 0.023508739218846934, "acc_norm": 0.8226415094339623, "acc_norm_stderr": 0.023508739218846934 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9166666666666666, "acc_stderr": 0.023112508176051236, "acc_norm": 0.9166666666666666, "acc_norm_stderr": 0.023112508176051236 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.65, "acc_stderr": 0.04793724854411019, "acc_norm": 0.65, "acc_norm_stderr": 0.04793724854411019 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818317, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818317 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5490196078431373, "acc_stderr": 0.049512182523962604, "acc_norm": 0.5490196078431373, "acc_norm_stderr": 0.049512182523962604 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8042553191489362, "acc_stderr": 0.025937853139977148, "acc_norm": 0.8042553191489362, "acc_norm_stderr": 0.025937853139977148 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5877192982456141, "acc_stderr": 0.046306532033665956, "acc_norm": 0.5877192982456141, "acc_norm_stderr": 0.046306532033665956 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7862068965517242, "acc_stderr": 0.03416520447747549, "acc_norm": 0.7862068965517242, "acc_norm_stderr": 0.03416520447747549 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.7116402116402116, "acc_stderr": 0.02333065405453588, "acc_norm": 0.7116402116402116, "acc_norm_stderr": 0.02333065405453588 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5952380952380952, "acc_stderr": 0.04390259265377563, "acc_norm": 0.5952380952380952, "acc_norm_stderr": 0.04390259265377563 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8838709677419355, "acc_stderr": 0.018225757949432306, "acc_norm": 0.8838709677419355, "acc_norm_stderr": 0.018225757949432306 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6551724137931034, "acc_stderr": 0.03344283744280459, "acc_norm": 0.6551724137931034, "acc_norm_stderr": 0.03344283744280459 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066573, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066573 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9343434343434344, "acc_stderr": 0.01764652667723333, "acc_norm": 0.9343434343434344, "acc_norm_stderr": 0.01764652667723333 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9896373056994818, "acc_stderr": 0.007308424386792194, "acc_norm": 0.9896373056994818, "acc_norm_stderr": 0.007308424386792194 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8153846153846154, "acc_stderr": 0.01967163241310029, "acc_norm": 0.8153846153846154, "acc_norm_stderr": 0.01967163241310029 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.5, "acc_stderr": 0.030485538042484616, "acc_norm": 0.5, "acc_norm_stderr": 0.030485538042484616 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.8445378151260504, "acc_stderr": 0.023536818625398904, "acc_norm": 0.8445378151260504, "acc_norm_stderr": 0.023536818625398904 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.5562913907284768, "acc_stderr": 0.04056527902281732, "acc_norm": 0.5562913907284768, "acc_norm_stderr": 0.04056527902281732 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.926605504587156, "acc_stderr": 0.011180976446357573, "acc_norm": 0.926605504587156, "acc_norm_stderr": 0.011180976446357573 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.6990740740740741, "acc_stderr": 0.03128039084329883, "acc_norm": 0.6990740740740741, "acc_norm_stderr": 0.03128039084329883 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9313725490196079, "acc_stderr": 0.017744453647073322, "acc_norm": 0.9313725490196079, "acc_norm_stderr": 0.017744453647073322 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.9029535864978903, "acc_stderr": 0.019269323025640273, "acc_norm": 0.9029535864978903, "acc_norm_stderr": 0.019269323025640273 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7982062780269058, "acc_stderr": 0.026936111912802273, "acc_norm": 0.7982062780269058, "acc_norm_stderr": 0.026936111912802273 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8702290076335878, "acc_stderr": 0.029473649496907065, "acc_norm": 0.8702290076335878, "acc_norm_stderr": 0.029473649496907065 }, "harness|hendrycksTest-international_law|5": { "acc": 0.9090909090909091, "acc_stderr": 0.026243194054073892, "acc_norm": 0.9090909090909091, "acc_norm_stderr": 0.026243194054073892 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8518518518518519, "acc_stderr": 0.03434300243630999, "acc_norm": 0.8518518518518519, "acc_norm_stderr": 0.03434300243630999 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8711656441717791, "acc_stderr": 0.02632138319878367, "acc_norm": 0.8711656441717791, "acc_norm_stderr": 0.02632138319878367 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.6607142857142857, "acc_stderr": 0.044939490686135404, "acc_norm": 0.6607142857142857, "acc_norm_stderr": 0.044939490686135404 }, "harness|hendrycksTest-management|5": { "acc": 0.8640776699029126, "acc_stderr": 0.03393295729761011, "acc_norm": 0.8640776699029126, "acc_norm_stderr": 0.03393295729761011 }, "harness|hendrycksTest-marketing|5": { "acc": 0.9401709401709402, "acc_stderr": 0.015537514263253874, "acc_norm": 0.9401709401709402, "acc_norm_stderr": 0.015537514263253874 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.86, "acc_stderr": 0.034873508801977725, 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