davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
passionMan/usda_tokenized_source	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string - name: label dtype: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 1314644 num_examples: 5628 - name: test num_bytes: 437798 num_examples: 1876 download_size: 434891 dataset_size: 1752442 --- # Dataset Card for "usda_tokenized_source" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
bigfish87/test	--- license: openrail ---
anan-2024/twitter_dataset_1712976471	--- 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: 276649 num_examples: 759 download_size: 151493 dataset_size: 276649 configs: - config_name: default data_files: - split: train path: data/train-* ---
liuyanchen1015/MULTI_VALUE_stsb_invariant_tag_amnt	--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: score dtype: float64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: dev num_bytes: 162 num_examples: 1 - name: test num_bytes: 192 num_examples: 1 download_size: 5842 dataset_size: 354 --- # Dataset Card for "MULTI_VALUE_stsb_invariant_tag_amnt" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
RevEng-23-24/Dataset48K	--- dataset_info: features: - name: assembly dtype: string - name: c_source_code dtype: string splits: - name: train num_bytes: 54615105 num_examples: 30657 - name: val num_bytes: 14102616 num_examples: 7665 - name: test num_bytes: 17112427 num_examples: 9581 download_size: 24803662 dataset_size: 85830148 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* - split: test path: data/test-* ---
ronniewy/chinese_nli	--- license: cc-by-4.0 ---
kanxue/muep_cot_checkpoint	--- license: apache-2.0 ---
Circularmachines/batch_indexing_machine_224x224_images	--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 1200580554.73 num_examples: 72510 download_size: 1200450555 dataset_size: 1200580554.73 --- # Dataset Card for "batch_indexing_machine_224x224_images" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
sethapun/imdb_misspelled_30	--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': neg '1': pos - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 33632801 num_examples: 25000 - name: validation num_bytes: 32851081 num_examples: 25000 download_size: 47443707 dataset_size: 66483882 --- # Dataset Card for "imdb_misspelled_30" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Cynaptics/Test2Sql	--- license: apache-2.0 dataset_info: features: - name: schema dtype: string - name: query dtype: string - name: question dtype: string splits: - name: small_validation num_bytes: 1171681 num_examples: 1000 - name: train num_bytes: 572158109 num_examples: 489956 - name: small_train num_bytes: 11702337 num_examples: 10000 - name: spider_test num_bytes: 759534287 num_examples: 4840 - name: sql_eval_test num_bytes: 18048597 num_examples: 3509 download_size: 150973260 dataset_size: 1362615011 configs: - config_name: default data_files: - split: small_validation path: data/small_validation-* - split: train path: data/train-* - split: small_train path: data/small_train-* - split: spider_test path: data/spider_test-* - split: sql_eval_test path: data/sql_eval_test-* ---
Rounak28/bengaliAI-preprocessed-whisper-medium-0-50000	--- dataset_info: features: - name: id dtype: string - name: sentence dtype: string - name: split dtype: string - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 48065858980 num_examples: 50000 download_size: 6861840289 dataset_size: 48065858980 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "bengaliAI-preprocessed-whisper-medium-0-50000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Falcon96/cidmoreira	--- license: openrail ---
open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B	--- pretty_name: Evaluation run of feeltheAGI/Maverick-Math-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [feeltheAGI/Maverick-Math-7B](https://huggingface.co/feeltheAGI/Maverick-Math-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_feeltheAGI__Maverick-Math-7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-14T10:55:45.107983](https://huggingface.co/datasets/open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B/blob/main/results_2024-03-14T10-55-45.107983.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\": 0.6296804564180761,\n\ \ \"acc_stderr\": 0.03245152465151836,\n \"acc_norm\": 0.6301031619229365,\n\ \ \"acc_norm_stderr\": 0.033115363797357654,\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769625,\n \"mc2\": 0.5596682871042189,\n\ \ \"mc2_stderr\": 0.015333014253402569\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6220136518771331,\n \"acc_stderr\": 0.0141696645203031,\n\ \ \"acc_norm\": 0.6527303754266212,\n \"acc_norm_stderr\": 0.013913034529620455\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6515634335789683,\n\ \ \"acc_stderr\": 0.004755013243022125,\n \"acc_norm\": 0.8454491137223661,\n\ \ \"acc_norm_stderr\": 0.0036073726062950976\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.562962962962963,\n\ \ \"acc_stderr\": 0.04284958639753401,\n \"acc_norm\": 0.562962962962963,\n\ \ \"acc_norm_stderr\": 0.04284958639753401\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.690566037735849,\n \"acc_stderr\": 0.028450154794118637,\n\ \ \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118637\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.03745554791462456,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.03745554791462456\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\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.35294117647058826,\n \"acc_stderr\": 0.04755129616062946,\n\ \ \"acc_norm\": 0.35294117647058826,\n \"acc_norm_stderr\": 0.04755129616062946\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.42105263157894735,\n\ \ \"acc_stderr\": 0.046446020912223177,\n \"acc_norm\": 0.42105263157894735,\n\ \ \"acc_norm_stderr\": 0.046446020912223177\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.42857142857142855,\n \"acc_stderr\": 0.025487187147859375,\n \"\ acc_norm\": 0.42857142857142855,\n \"acc_norm_stderr\": 0.025487187147859375\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.42063492063492064,\n\ \ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\ \ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7483870967741936,\n\ \ \"acc_stderr\": 0.024685979286239963,\n \"acc_norm\": 0.7483870967741936,\n\ \ \"acc_norm_stderr\": 0.024685979286239963\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\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\ : 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7878787878787878,\n \"acc_stderr\": 0.031922715695483016,\n\ \ \"acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.031922715695483016\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7828282828282829,\n \"acc_stderr\": 0.02937661648494563,\n \"\ acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.02937661648494563\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9067357512953368,\n \"acc_stderr\": 0.02098685459328972,\n\ \ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.02098685459328972\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6410256410256411,\n \"acc_stderr\": 0.024321738484602357,\n\ \ \"acc_norm\": 0.6410256410256411,\n \"acc_norm_stderr\": 0.024321738484602357\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3,\n \"acc_stderr\": 0.02794045713622841,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.02794045713622841\n },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\"\ : {\n \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.03077805742293167,\n\ \ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.03077805742293167\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8293577981651377,\n \"acc_stderr\": 0.016129271025099864,\n \"\ acc_norm\": 0.8293577981651377,\n \"acc_norm_stderr\": 0.016129271025099864\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\": 0.8088235294117647,\n\ \ \"acc_stderr\": 0.027599174300640763,\n \"acc_norm\": 0.8088235294117647,\n\ \ \"acc_norm_stderr\": 0.027599174300640763\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.7932489451476793,\n \"acc_stderr\": 0.0263616516683891,\n\ \ \"acc_norm\": 0.7932489451476793,\n \"acc_norm_stderr\": 0.0263616516683891\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7557251908396947,\n \"acc_stderr\": 0.03768335959728744,\n\ \ \"acc_norm\": 0.7557251908396947,\n \"acc_norm_stderr\": 0.03768335959728744\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228733,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228733\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615624,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615624\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.5178571428571429,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.5178571428571429,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.043546310772605956,\n\ \ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.043546310772605956\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.021586494001281382,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.021586494001281382\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8212005108556832,\n\ \ \"acc_stderr\": 0.013702643715368985,\n \"acc_norm\": 0.8212005108556832,\n\ \ \"acc_norm_stderr\": 0.013702643715368985\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.02494679222527231,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.02494679222527231\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.35083798882681566,\n\ \ \"acc_stderr\": 0.01596103667523096,\n \"acc_norm\": 0.35083798882681566,\n\ \ \"acc_norm_stderr\": 0.01596103667523096\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6895424836601307,\n \"acc_stderr\": 0.026493033225145898,\n\ \ \"acc_norm\": 0.6895424836601307,\n \"acc_norm_stderr\": 0.026493033225145898\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7202572347266881,\n\ \ \"acc_stderr\": 0.025494259350694912,\n \"acc_norm\": 0.7202572347266881,\n\ \ \"acc_norm_stderr\": 0.025494259350694912\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7037037037037037,\n \"acc_stderr\": 0.02540719779889016,\n\ \ \"acc_norm\": 0.7037037037037037,\n \"acc_norm_stderr\": 0.02540719779889016\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303062,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303062\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4602346805736636,\n\ \ \"acc_stderr\": 0.012729785386598559,\n \"acc_norm\": 0.4602346805736636,\n\ \ \"acc_norm_stderr\": 0.012729785386598559\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6433823529411765,\n \"acc_stderr\": 0.029097209568411952,\n\ \ \"acc_norm\": 0.6433823529411765,\n \"acc_norm_stderr\": 0.029097209568411952\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6552287581699346,\n \"acc_stderr\": 0.019228322018696644,\n \ \ \"acc_norm\": 0.6552287581699346,\n \"acc_norm_stderr\": 0.019228322018696644\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\": 0.6979591836734694,\n \"acc_stderr\": 0.0293936093198798,\n\ \ \"acc_norm\": 0.6979591836734694,\n \"acc_norm_stderr\": 0.0293936093198798\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.835820895522388,\n\ \ \"acc_stderr\": 0.02619392354445412,\n \"acc_norm\": 0.835820895522388,\n\ \ \"acc_norm_stderr\": 0.02619392354445412\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5301204819277109,\n\ \ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\ \ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7894736842105263,\n \"acc_stderr\": 0.03126781714663179,\n\ \ \"acc_norm\": 0.7894736842105263,\n \"acc_norm_stderr\": 0.03126781714663179\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769625,\n \"mc2\": 0.5596682871042189,\n\ \ \"mc2_stderr\": 0.015333014253402569\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7971586424625099,\n \"acc_stderr\": 0.011301439925936645\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6618650492797574,\n \ \ \"acc_stderr\": 0.013030829145172208\n }\n}\n```" repo_url: https://huggingface.co/feeltheAGI/Maverick-Math-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_03_14T10_55_45.107983 path: - '/details_harness\|arc:challenge\|25_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-14T10-55-45.107983.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|gsm8k\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hellaswag\|10_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-14T10-55-45.107983.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-14T10-55-45.107983.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '/details_harness\|winogrande\|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-14T10-55-45.107983.parquet' - config_name: results data_files: - split: 2024_03_14T10_55_45.107983 path: - results_2024-03-14T10-55-45.107983.parquet - split: latest path: - results_2024-03-14T10-55-45.107983.parquet --- # Dataset Card for Evaluation run of feeltheAGI/Maverick-Math-7B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [feeltheAGI/Maverick-Math-7B](https://huggingface.co/feeltheAGI/Maverick-Math-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_feeltheAGI__Maverick-Math-7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-14T10:55:45.107983](https://huggingface.co/datasets/open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B/blob/main/results_2024-03-14T10-55-45.107983.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": 0.6296804564180761, "acc_stderr": 0.03245152465151836, "acc_norm": 0.6301031619229365, "acc_norm_stderr": 0.033115363797357654, "mc1": 0.39167686658506734, "mc1_stderr": 0.017087795881769625, "mc2": 0.5596682871042189, "mc2_stderr": 0.015333014253402569 }, "harness\|arc:challenge\|25": { "acc": 0.6220136518771331, "acc_stderr": 0.0141696645203031, "acc_norm": 0.6527303754266212, "acc_norm_stderr": 0.013913034529620455 }, "harness\|hellaswag\|10": { "acc": 0.6515634335789683, "acc_stderr": 0.004755013243022125, "acc_norm": 0.8454491137223661, "acc_norm_stderr": 0.0036073726062950976 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.690566037735849, "acc_stderr": 0.028450154794118637, "acc_norm": 0.690566037735849, "acc_norm_stderr": 0.028450154794118637 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03745554791462456, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03745554791462456 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.35294117647058826, "acc_stderr": 0.04755129616062946, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.04755129616062946 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5531914893617021, "acc_stderr": 0.0325005368436584, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.0325005368436584 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.42105263157894735, "acc_stderr": 0.046446020912223177, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.046446020912223177 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.42857142857142855, "acc_stderr": 0.025487187147859375, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.025487187147859375 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7483870967741936, "acc_stderr": 0.024685979286239963, "acc_norm": 0.7483870967741936, "acc_norm_stderr": 0.024685979286239963 }, "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": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7878787878787878, "acc_stderr": 0.031922715695483016, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.031922715695483016 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7828282828282829, "acc_stderr": 0.02937661648494563, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.02937661648494563 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9067357512953368, "acc_stderr": 0.02098685459328972, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.02098685459328972 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6410256410256411, "acc_stderr": 0.024321738484602357, "acc_norm": 0.6410256410256411, "acc_norm_stderr": 0.024321738484602357 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3, "acc_stderr": 0.02794045713622841, "acc_norm": 0.3, "acc_norm_stderr": 0.02794045713622841 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6596638655462185, "acc_stderr": 0.03077805742293167, "acc_norm": 0.6596638655462185, "acc_norm_stderr": 0.03077805742293167 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8293577981651377, "acc_stderr": 0.016129271025099864, "acc_norm": 0.8293577981651377, "acc_norm_stderr": 0.016129271025099864 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.0340470532865388, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.0340470532865388 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8088235294117647, "acc_stderr": 0.027599174300640763, "acc_norm": 0.8088235294117647, "acc_norm_stderr": 0.027599174300640763 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7932489451476793, "acc_stderr": 0.0263616516683891, "acc_norm": 0.7932489451476793, "acc_norm_stderr": 0.0263616516683891 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6905829596412556, "acc_stderr": 0.03102441174057221, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.03102441174057221 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7557251908396947, "acc_stderr": 0.03768335959728744, "acc_norm": 0.7557251908396947, "acc_norm_stderr": 0.03768335959728744 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228733, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228733 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615624, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615624 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.5178571428571429, "acc_stderr": 0.047427623612430116, "acc_norm": 0.5178571428571429, "acc_norm_stderr": 0.047427623612430116 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7378640776699029, "acc_stderr": 0.043546310772605956, "acc_norm": 0.7378640776699029, "acc_norm_stderr": 0.043546310772605956 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8760683760683761, "acc_stderr": 0.021586494001281382, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.021586494001281382 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8212005108556832, "acc_stderr": 0.013702643715368985, "acc_norm": 0.8212005108556832, "acc_norm_stderr": 0.013702643715368985 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6878612716763006, "acc_stderr": 0.02494679222527231, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.02494679222527231 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.35083798882681566, "acc_stderr": 0.01596103667523096, "acc_norm": 0.35083798882681566, "acc_norm_stderr": 0.01596103667523096 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6895424836601307, "acc_stderr": 0.026493033225145898, "acc_norm": 0.6895424836601307, "acc_norm_stderr": 0.026493033225145898 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7202572347266881, "acc_stderr": 0.025494259350694912, "acc_norm": 0.7202572347266881, "acc_norm_stderr": 0.025494259350694912 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7037037037037037, "acc_stderr": 0.02540719779889016, "acc_norm": 0.7037037037037037, "acc_norm_stderr": 0.02540719779889016 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303062, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303062 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4602346805736636, "acc_stderr": 0.012729785386598559, "acc_norm": 0.4602346805736636, "acc_norm_stderr": 0.012729785386598559 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6433823529411765, "acc_stderr": 0.029097209568411952, "acc_norm": 0.6433823529411765, "acc_norm_stderr": 0.029097209568411952 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6552287581699346, "acc_stderr": 0.019228322018696644, "acc_norm": 0.6552287581699346, "acc_norm_stderr": 0.019228322018696644 }, "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": 0.6979591836734694, "acc_stderr": 0.0293936093198798, "acc_norm": 0.6979591836734694, "acc_norm_stderr": 0.0293936093198798 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.835820895522388, "acc_stderr": 0.02619392354445412, "acc_norm": 0.835820895522388, "acc_norm_stderr": 0.02619392354445412 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5301204819277109, "acc_stderr": 0.03885425420866767, "acc_norm": 0.5301204819277109, "acc_norm_stderr": 0.03885425420866767 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7894736842105263, "acc_stderr": 0.03126781714663179, "acc_norm": 0.7894736842105263, "acc_norm_stderr": 0.03126781714663179 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.39167686658506734, "mc1_stderr": 0.017087795881769625, "mc2": 0.5596682871042189, "mc2_stderr": 0.015333014253402569 }, "harness\|winogrande\|5": { "acc": 0.7971586424625099, "acc_stderr": 0.011301439925936645 }, "harness\|gsm8k\|5": { "acc": 0.6618650492797574, "acc_stderr": 0.013030829145172208 } } ``` ## 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]
SkyWR/Pespi	--- license: openrail ---
open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged	--- pretty_name: Evaluation run of Korabbit/Llama-2-7b-chat-hf-afr-200step-merged dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Korabbit/Llama-2-7b-chat-hf-afr-200step-merged](https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 1 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged\"\ ,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\ \ are the [latest results from run 2023-12-02T13:52:27.757521](https://huggingface.co/datasets/open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged/blob/main/results_2023-12-02T13-52-27.757521.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\": 0.18953752843062927,\n\ \ \"acc_stderr\": 0.010795837931896377\n },\n \"harness\|gsm8k\|5\":\ \ {\n \"acc\": 0.18953752843062927,\n \"acc_stderr\": 0.010795837931896377\n\ \ }\n}\n```" repo_url: https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_gsm8k_5 data_files: - split: 2023_12_02T13_52_27.757521 path: - '/details_harness\|gsm8k\|5_2023-12-02T13-52-27.757521.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-02T13-52-27.757521.parquet' - config_name: results data_files: - split: 2023_12_02T13_52_27.757521 path: - results_2023-12-02T13-52-27.757521.parquet - split: latest path: - results_2023-12-02T13-52-27.757521.parquet --- # Dataset Card for Evaluation run of Korabbit/Llama-2-7b-chat-hf-afr-200step-merged ## Dataset Description - Homepage: - Repository: https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged - 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 [Korabbit/Llama-2-7b-chat-hf-afr-200step-merged](https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 1 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged", "harness_gsm8k_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-02T13:52:27.757521](https://huggingface.co/datasets/open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged/blob/main/results_2023-12-02T13-52-27.757521.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": 0.18953752843062927, "acc_stderr": 0.010795837931896377 }, "harness\|gsm8k\|5": { "acc": 0.18953752843062927, "acc_stderr": 0.010795837931896377 } } ``` ### 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]
BangumiBase/myheroacademia	--- license: mit tags: - art size_categories: - 10K<n<100K --- # Bangumi Image Base of My Hero Academia This is the image base of bangumi My Hero Academia, we detected 146 characters, 15676 images in total. The full dataset is [here](all.zip). Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: \| # \| Images \| Download \| Preview 1 \| Preview 2 \| Preview 3 \| Preview 4 \| Preview 5 \| Preview 6 \| Preview 7 \| Preview 8 \| \|:------\|---------:\|:----------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\| \| 0 \| 186 \| [Download](0/dataset.zip) \| ![preview 1](0/preview_1.png) \| ![preview 2](0/preview_2.png) \| ![preview 3](0/preview_3.png) \| ![preview 4](0/preview_4.png) \| ![preview 5](0/preview_5.png) \| ![preview 6](0/preview_6.png) \| ![preview 7](0/preview_7.png) \| ![preview 8](0/preview_8.png) \| \| 1 \| 254 \| [Download](1/dataset.zip) \| ![preview 1](1/preview_1.png) \| ![preview 2](1/preview_2.png) \| ![preview 3](1/preview_3.png) \| ![preview 4](1/preview_4.png) \| ![preview 5](1/preview_5.png) \| ![preview 6](1/preview_6.png) \| ![preview 7](1/preview_7.png) \| ![preview 8](1/preview_8.png) \| \| 2 \| 105 \| [Download](2/dataset.zip) \| ![preview 1](2/preview_1.png) \| ![preview 2](2/preview_2.png) \| ![preview 3](2/preview_3.png) \| ![preview 4](2/preview_4.png) \| ![preview 5](2/preview_5.png) \| ![preview 6](2/preview_6.png) \| ![preview 7](2/preview_7.png) \| ![preview 8](2/preview_8.png) \| \| 3 \| 546 \| [Download](3/dataset.zip) \| ![preview 1](3/preview_1.png) \| ![preview 2](3/preview_2.png) \| ![preview 3](3/preview_3.png) \| ![preview 4](3/preview_4.png) \| ![preview 5](3/preview_5.png) \| ![preview 6](3/preview_6.png) \| ![preview 7](3/preview_7.png) \| ![preview 8](3/preview_8.png) \| \| 4 \| 69 \| [Download](4/dataset.zip) \| ![preview 1](4/preview_1.png) \| ![preview 2](4/preview_2.png) \| ![preview 3](4/preview_3.png) \| ![preview 4](4/preview_4.png) \| ![preview 5](4/preview_5.png) \| ![preview 6](4/preview_6.png) \| ![preview 7](4/preview_7.png) \| ![preview 8](4/preview_8.png) \| \| 5 \| 739 \| [Download](5/dataset.zip) \| ![preview 1](5/preview_1.png) \| ![preview 2](5/preview_2.png) \| ![preview 3](5/preview_3.png) \| ![preview 4](5/preview_4.png) \| ![preview 5](5/preview_5.png) \| ![preview 6](5/preview_6.png) \| ![preview 7](5/preview_7.png) \| ![preview 8](5/preview_8.png) \| \| 6 \| 201 \| [Download](6/dataset.zip) \| ![preview 1](6/preview_1.png) \| ![preview 2](6/preview_2.png) \| ![preview 3](6/preview_3.png) \| ![preview 4](6/preview_4.png) \| ![preview 5](6/preview_5.png) \| ![preview 6](6/preview_6.png) \| ![preview 7](6/preview_7.png) \| ![preview 8](6/preview_8.png) \| \| 7 \| 34 \| [Download](7/dataset.zip) \| ![preview 1](7/preview_1.png) \| ![preview 2](7/preview_2.png) \| ![preview 3](7/preview_3.png) \| ![preview 4](7/preview_4.png) \| ![preview 5](7/preview_5.png) \| ![preview 6](7/preview_6.png) \| ![preview 7](7/preview_7.png) \| ![preview 8](7/preview_8.png) \| \| 8 \| 129 \| [Download](8/dataset.zip) \| ![preview 1](8/preview_1.png) \| ![preview 2](8/preview_2.png) \| ![preview 3](8/preview_3.png) \| ![preview 4](8/preview_4.png) \| ![preview 5](8/preview_5.png) \| ![preview 6](8/preview_6.png) \| ![preview 7](8/preview_7.png) \| ![preview 8](8/preview_8.png) \| \| 9 \| 31 \| [Download](9/dataset.zip) \| ![preview 1](9/preview_1.png) \| ![preview 2](9/preview_2.png) \| ![preview 3](9/preview_3.png) \| ![preview 4](9/preview_4.png) \| ![preview 5](9/preview_5.png) \| ![preview 6](9/preview_6.png) \| ![preview 7](9/preview_7.png) \| ![preview 8](9/preview_8.png) \| \| 10 \| 3091 \| [Download](10/dataset.zip) \| ![preview 1](10/preview_1.png) \| ![preview 2](10/preview_2.png) \| ![preview 3](10/preview_3.png) \| ![preview 4](10/preview_4.png) \| ![preview 5](10/preview_5.png) \| ![preview 6](10/preview_6.png) \| ![preview 7](10/preview_7.png) \| ![preview 8](10/preview_8.png) \| \| 11 \| 71 \| [Download](11/dataset.zip) \| ![preview 1](11/preview_1.png) \| ![preview 2](11/preview_2.png) \| ![preview 3](11/preview_3.png) \| ![preview 4](11/preview_4.png) \| ![preview 5](11/preview_5.png) \| ![preview 6](11/preview_6.png) \| ![preview 7](11/preview_7.png) \| ![preview 8](11/preview_8.png) \| \| 12 \| 174 \| [Download](12/dataset.zip) \| ![preview 1](12/preview_1.png) \| ![preview 2](12/preview_2.png) \| ![preview 3](12/preview_3.png) \| ![preview 4](12/preview_4.png) \| ![preview 5](12/preview_5.png) \| ![preview 6](12/preview_6.png) \| ![preview 7](12/preview_7.png) \| ![preview 8](12/preview_8.png) \| \| 13 \| 211 \| [Download](13/dataset.zip) \| ![preview 1](13/preview_1.png) \| ![preview 2](13/preview_2.png) \| ![preview 3](13/preview_3.png) \| ![preview 4](13/preview_4.png) \| ![preview 5](13/preview_5.png) \| ![preview 6](13/preview_6.png) \| ![preview 7](13/preview_7.png) \| ![preview 8](13/preview_8.png) \| \| 14 \| 878 \| [Download](14/dataset.zip) \| ![preview 1](14/preview_1.png) \| ![preview 2](14/preview_2.png) \| ![preview 3](14/preview_3.png) \| ![preview 4](14/preview_4.png) \| ![preview 5](14/preview_5.png) \| ![preview 6](14/preview_6.png) \| ![preview 7](14/preview_7.png) \| ![preview 8](14/preview_8.png) \| \| 15 \| 130 \| [Download](15/dataset.zip) \| ![preview 1](15/preview_1.png) \| ![preview 2](15/preview_2.png) \| ![preview 3](15/preview_3.png) \| ![preview 4](15/preview_4.png) \| ![preview 5](15/preview_5.png) \| ![preview 6](15/preview_6.png) \| ![preview 7](15/preview_7.png) \| ![preview 8](15/preview_8.png) \| \| 16 \| 75 \| [Download](16/dataset.zip) \| ![preview 1](16/preview_1.png) \| ![preview 2](16/preview_2.png) \| ![preview 3](16/preview_3.png) \| ![preview 4](16/preview_4.png) \| ![preview 5](16/preview_5.png) \| ![preview 6](16/preview_6.png) \| ![preview 7](16/preview_7.png) \| ![preview 8](16/preview_8.png) \| \| 17 \| 63 \| [Download](17/dataset.zip) \| ![preview 1](17/preview_1.png) \| ![preview 2](17/preview_2.png) \| ![preview 3](17/preview_3.png) \| ![preview 4](17/preview_4.png) \| ![preview 5](17/preview_5.png) \| ![preview 6](17/preview_6.png) \| ![preview 7](17/preview_7.png) \| ![preview 8](17/preview_8.png) \| \| 18 \| 69 \| [Download](18/dataset.zip) \| ![preview 1](18/preview_1.png) \| ![preview 2](18/preview_2.png) \| ![preview 3](18/preview_3.png) \| ![preview 4](18/preview_4.png) \| ![preview 5](18/preview_5.png) \| ![preview 6](18/preview_6.png) \| ![preview 7](18/preview_7.png) \| ![preview 8](18/preview_8.png) \| \| 19 \| 540 \| [Download](19/dataset.zip) \| ![preview 1](19/preview_1.png) \| ![preview 2](19/preview_2.png) \| ![preview 3](19/preview_3.png) \| ![preview 4](19/preview_4.png) \| ![preview 5](19/preview_5.png) \| ![preview 6](19/preview_6.png) \| ![preview 7](19/preview_7.png) \| ![preview 8](19/preview_8.png) \| \| 20 \| 274 \| [Download](20/dataset.zip) \| ![preview 1](20/preview_1.png) \| ![preview 2](20/preview_2.png) \| ![preview 3](20/preview_3.png) \| ![preview 4](20/preview_4.png) \| ![preview 5](20/preview_5.png) \| ![preview 6](20/preview_6.png) \| ![preview 7](20/preview_7.png) \| ![preview 8](20/preview_8.png) \| \| 21 \| 286 \| [Download](21/dataset.zip) \| ![preview 1](21/preview_1.png) \| ![preview 2](21/preview_2.png) \| ![preview 3](21/preview_3.png) \| ![preview 4](21/preview_4.png) \| ![preview 5](21/preview_5.png) \| ![preview 6](21/preview_6.png) \| ![preview 7](21/preview_7.png) \| ![preview 8](21/preview_8.png) \| \| 22 \| 140 \| [Download](22/dataset.zip) \| ![preview 1](22/preview_1.png) \| ![preview 2](22/preview_2.png) \| ![preview 3](22/preview_3.png) \| ![preview 4](22/preview_4.png) \| ![preview 5](22/preview_5.png) \| ![preview 6](22/preview_6.png) \| ![preview 7](22/preview_7.png) \| ![preview 8](22/preview_8.png) \| \| 23 \| 25 \| [Download](23/dataset.zip) \| ![preview 1](23/preview_1.png) \| ![preview 2](23/preview_2.png) \| ![preview 3](23/preview_3.png) \| ![preview 4](23/preview_4.png) \| ![preview 5](23/preview_5.png) \| ![preview 6](23/preview_6.png) \| ![preview 7](23/preview_7.png) \| ![preview 8](23/preview_8.png) \| \| 24 \| 81 \| [Download](24/dataset.zip) \| ![preview 1](24/preview_1.png) \| ![preview 2](24/preview_2.png) \| ![preview 3](24/preview_3.png) \| ![preview 4](24/preview_4.png) \| ![preview 5](24/preview_5.png) \| ![preview 6](24/preview_6.png) \| ![preview 7](24/preview_7.png) \| ![preview 8](24/preview_8.png) \| \| 25 \| 30 \| [Download](25/dataset.zip) \| ![preview 1](25/preview_1.png) \| ![preview 2](25/preview_2.png) \| ![preview 3](25/preview_3.png) \| ![preview 4](25/preview_4.png) \| ![preview 5](25/preview_5.png) \| ![preview 6](25/preview_6.png) \| ![preview 7](25/preview_7.png) \| ![preview 8](25/preview_8.png) \| \| 26 \| 60 \| [Download](26/dataset.zip) \| ![preview 1](26/preview_1.png) \| ![preview 2](26/preview_2.png) \| ![preview 3](26/preview_3.png) \| ![preview 4](26/preview_4.png) \| ![preview 5](26/preview_5.png) \| ![preview 6](26/preview_6.png) \| ![preview 7](26/preview_7.png) \| ![preview 8](26/preview_8.png) \| \| 27 \| 26 \| [Download](27/dataset.zip) \| ![preview 1](27/preview_1.png) \| ![preview 2](27/preview_2.png) \| ![preview 3](27/preview_3.png) \| ![preview 4](27/preview_4.png) \| ![preview 5](27/preview_5.png) \| ![preview 6](27/preview_6.png) \| ![preview 7](27/preview_7.png) \| ![preview 8](27/preview_8.png) \| \| 28 \| 41 \| [Download](28/dataset.zip) \| ![preview 1](28/preview_1.png) \| ![preview 2](28/preview_2.png) \| ![preview 3](28/preview_3.png) \| ![preview 4](28/preview_4.png) \| ![preview 5](28/preview_5.png) \| ![preview 6](28/preview_6.png) \| ![preview 7](28/preview_7.png) \| ![preview 8](28/preview_8.png) \| \| 29 \| 52 \| [Download](29/dataset.zip) \| ![preview 1](29/preview_1.png) \| ![preview 2](29/preview_2.png) \| ![preview 3](29/preview_3.png) \| ![preview 4](29/preview_4.png) \| ![preview 5](29/preview_5.png) \| ![preview 6](29/preview_6.png) \| ![preview 7](29/preview_7.png) \| ![preview 8](29/preview_8.png) \| \| 30 \| 81 \| [Download](30/dataset.zip) \| ![preview 1](30/preview_1.png) \| ![preview 2](30/preview_2.png) \| ![preview 3](30/preview_3.png) \| ![preview 4](30/preview_4.png) \| ![preview 5](30/preview_5.png) \| ![preview 6](30/preview_6.png) \| ![preview 7](30/preview_7.png) \| ![preview 8](30/preview_8.png) \| \| 31 \| 26 \| [Download](31/dataset.zip) \| ![preview 1](31/preview_1.png) \| ![preview 2](31/preview_2.png) \| ![preview 3](31/preview_3.png) \| ![preview 4](31/preview_4.png) \| ![preview 5](31/preview_5.png) \| ![preview 6](31/preview_6.png) \| ![preview 7](31/preview_7.png) \| ![preview 8](31/preview_8.png) \| \| 32 \| 86 \| [Download](32/dataset.zip) \| ![preview 1](32/preview_1.png) \| ![preview 2](32/preview_2.png) \| ![preview 3](32/preview_3.png) \| ![preview 4](32/preview_4.png) \| ![preview 5](32/preview_5.png) \| ![preview 6](32/preview_6.png) \| ![preview 7](32/preview_7.png) \| ![preview 8](32/preview_8.png) \| \| 33 \| 65 \| [Download](33/dataset.zip) \| ![preview 1](33/preview_1.png) \| ![preview 2](33/preview_2.png) \| ![preview 3](33/preview_3.png) \| ![preview 4](33/preview_4.png) \| ![preview 5](33/preview_5.png) \| ![preview 6](33/preview_6.png) \| ![preview 7](33/preview_7.png) \| ![preview 8](33/preview_8.png) \| \| 34 \| 32 \| [Download](34/dataset.zip) \| ![preview 1](34/preview_1.png) \| ![preview 2](34/preview_2.png) \| ![preview 3](34/preview_3.png) \| ![preview 4](34/preview_4.png) \| ![preview 5](34/preview_5.png) \| ![preview 6](34/preview_6.png) \| ![preview 7](34/preview_7.png) \| ![preview 8](34/preview_8.png) \| \| 35 \| 41 \| [Download](35/dataset.zip) \| ![preview 1](35/preview_1.png) \| ![preview 2](35/preview_2.png) \| ![preview 3](35/preview_3.png) \| ![preview 4](35/preview_4.png) \| ![preview 5](35/preview_5.png) \| ![preview 6](35/preview_6.png) \| ![preview 7](35/preview_7.png) \| ![preview 8](35/preview_8.png) \| \| 36 \| 74 \| [Download](36/dataset.zip) \| ![preview 1](36/preview_1.png) \| ![preview 2](36/preview_2.png) \| ![preview 3](36/preview_3.png) \| ![preview 4](36/preview_4.png) \| ![preview 5](36/preview_5.png) \| ![preview 6](36/preview_6.png) \| ![preview 7](36/preview_7.png) \| ![preview 8](36/preview_8.png) \| \| 37 \| 259 \| [Download](37/dataset.zip) \| ![preview 1](37/preview_1.png) \| ![preview 2](37/preview_2.png) \| ![preview 3](37/preview_3.png) \| ![preview 4](37/preview_4.png) \| ![preview 5](37/preview_5.png) \| ![preview 6](37/preview_6.png) \| ![preview 7](37/preview_7.png) \| ![preview 8](37/preview_8.png) \| \| 38 \| 26 \| [Download](38/dataset.zip) \| ![preview 1](38/preview_1.png) \| ![preview 2](38/preview_2.png) \| ![preview 3](38/preview_3.png) \| ![preview 4](38/preview_4.png) \| ![preview 5](38/preview_5.png) \| ![preview 6](38/preview_6.png) \| ![preview 7](38/preview_7.png) \| ![preview 8](38/preview_8.png) \| \| 39 \| 11 \| [Download](39/dataset.zip) \| ![preview 1](39/preview_1.png) \| ![preview 2](39/preview_2.png) \| ![preview 3](39/preview_3.png) \| ![preview 4](39/preview_4.png) \| ![preview 5](39/preview_5.png) \| ![preview 6](39/preview_6.png) \| ![preview 7](39/preview_7.png) \| ![preview 8](39/preview_8.png) \| \| 40 \| 26 \| [Download](40/dataset.zip) \| ![preview 1](40/preview_1.png) \| ![preview 2](40/preview_2.png) \| ![preview 3](40/preview_3.png) \| ![preview 4](40/preview_4.png) \| ![preview 5](40/preview_5.png) \| ![preview 6](40/preview_6.png) \| ![preview 7](40/preview_7.png) \| ![preview 8](40/preview_8.png) \| \| 41 \| 78 \| [Download](41/dataset.zip) \| ![preview 1](41/preview_1.png) \| ![preview 2](41/preview_2.png) \| ![preview 3](41/preview_3.png) \| ![preview 4](41/preview_4.png) \| ![preview 5](41/preview_5.png) \| ![preview 6](41/preview_6.png) \| ![preview 7](41/preview_7.png) \| ![preview 8](41/preview_8.png) \| \| 42 \| 29 \| [Download](42/dataset.zip) \| ![preview 1](42/preview_1.png) \| ![preview 2](42/preview_2.png) \| ![preview 3](42/preview_3.png) \| ![preview 4](42/preview_4.png) \| ![preview 5](42/preview_5.png) \| ![preview 6](42/preview_6.png) \| ![preview 7](42/preview_7.png) \| ![preview 8](42/preview_8.png) \| \| 43 \| 24 \| [Download](43/dataset.zip) \| ![preview 1](43/preview_1.png) \| ![preview 2](43/preview_2.png) \| ![preview 3](43/preview_3.png) \| ![preview 4](43/preview_4.png) \| ![preview 5](43/preview_5.png) \| ![preview 6](43/preview_6.png) \| ![preview 7](43/preview_7.png) \| ![preview 8](43/preview_8.png) \| \| 44 \| 41 \| [Download](44/dataset.zip) \| ![preview 1](44/preview_1.png) \| ![preview 2](44/preview_2.png) \| ![preview 3](44/preview_3.png) \| ![preview 4](44/preview_4.png) \| ![preview 5](44/preview_5.png) \| ![preview 6](44/preview_6.png) \| ![preview 7](44/preview_7.png) \| ![preview 8](44/preview_8.png) \| \| 45 \| 24 \| [Download](45/dataset.zip) \| ![preview 1](45/preview_1.png) \| ![preview 2](45/preview_2.png) \| ![preview 3](45/preview_3.png) \| ![preview 4](45/preview_4.png) \| ![preview 5](45/preview_5.png) \| ![preview 6](45/preview_6.png) \| ![preview 7](45/preview_7.png) \| ![preview 8](45/preview_8.png) \| \| 46 \| 450 \| [Download](46/dataset.zip) \| ![preview 1](46/preview_1.png) \| ![preview 2](46/preview_2.png) \| ![preview 3](46/preview_3.png) \| ![preview 4](46/preview_4.png) \| ![preview 5](46/preview_5.png) \| ![preview 6](46/preview_6.png) \| ![preview 7](46/preview_7.png) \| ![preview 8](46/preview_8.png) \| \| 47 \| 21 \| [Download](47/dataset.zip) \| ![preview 1](47/preview_1.png) \| ![preview 2](47/preview_2.png) \| ![preview 3](47/preview_3.png) \| ![preview 4](47/preview_4.png) \| ![preview 5](47/preview_5.png) \| ![preview 6](47/preview_6.png) \| ![preview 7](47/preview_7.png) \| ![preview 8](47/preview_8.png) \| \| 48 \| 43 \| [Download](48/dataset.zip) \| ![preview 1](48/preview_1.png) \| ![preview 2](48/preview_2.png) \| ![preview 3](48/preview_3.png) \| ![preview 4](48/preview_4.png) \| ![preview 5](48/preview_5.png) \| ![preview 6](48/preview_6.png) \| ![preview 7](48/preview_7.png) \| ![preview 8](48/preview_8.png) \| \| 49 \| 75 \| [Download](49/dataset.zip) \| ![preview 1](49/preview_1.png) \| ![preview 2](49/preview_2.png) \| ![preview 3](49/preview_3.png) \| ![preview 4](49/preview_4.png) \| ![preview 5](49/preview_5.png) \| ![preview 6](49/preview_6.png) \| ![preview 7](49/preview_7.png) \| ![preview 8](49/preview_8.png) \| \| 50 \| 85 \| [Download](50/dataset.zip) \| ![preview 1](50/preview_1.png) \| ![preview 2](50/preview_2.png) \| ![preview 3](50/preview_3.png) \| ![preview 4](50/preview_4.png) \| ![preview 5](50/preview_5.png) \| ![preview 6](50/preview_6.png) \| ![preview 7](50/preview_7.png) \| ![preview 8](50/preview_8.png) \| \| 51 \| 85 \| [Download](51/dataset.zip) \| ![preview 1](51/preview_1.png) \| ![preview 2](51/preview_2.png) \| ![preview 3](51/preview_3.png) \| ![preview 4](51/preview_4.png) \| ![preview 5](51/preview_5.png) \| ![preview 6](51/preview_6.png) \| ![preview 7](51/preview_7.png) \| ![preview 8](51/preview_8.png) \| \| 52 \| 41 \| [Download](52/dataset.zip) \| ![preview 1](52/preview_1.png) \| ![preview 2](52/preview_2.png) \| ![preview 3](52/preview_3.png) \| ![preview 4](52/preview_4.png) \| ![preview 5](52/preview_5.png) \| ![preview 6](52/preview_6.png) \| ![preview 7](52/preview_7.png) \| ![preview 8](52/preview_8.png) \| \| 53 \| 20 \| [Download](53/dataset.zip) \| ![preview 1](53/preview_1.png) \| ![preview 2](53/preview_2.png) \| ![preview 3](53/preview_3.png) \| ![preview 4](53/preview_4.png) \| ![preview 5](53/preview_5.png) \| ![preview 6](53/preview_6.png) \| ![preview 7](53/preview_7.png) \| ![preview 8](53/preview_8.png) \| \| 54 \| 79 \| [Download](54/dataset.zip) \| ![preview 1](54/preview_1.png) \| ![preview 2](54/preview_2.png) \| ![preview 3](54/preview_3.png) \| ![preview 4](54/preview_4.png) \| ![preview 5](54/preview_5.png) \| ![preview 6](54/preview_6.png) \| ![preview 7](54/preview_7.png) \| ![preview 8](54/preview_8.png) \| \| 55 \| 20 \| [Download](55/dataset.zip) \| ![preview 1](55/preview_1.png) \| ![preview 2](55/preview_2.png) \| ![preview 3](55/preview_3.png) \| ![preview 4](55/preview_4.png) \| ![preview 5](55/preview_5.png) \| ![preview 6](55/preview_6.png) \| ![preview 7](55/preview_7.png) \| ![preview 8](55/preview_8.png) \| \| 56 \| 117 \| [Download](56/dataset.zip) \| ![preview 1](56/preview_1.png) \| ![preview 2](56/preview_2.png) \| ![preview 3](56/preview_3.png) \| ![preview 4](56/preview_4.png) \| ![preview 5](56/preview_5.png) \| ![preview 6](56/preview_6.png) \| ![preview 7](56/preview_7.png) \| ![preview 8](56/preview_8.png) \| \| 57 \| 21 \| [Download](57/dataset.zip) \| ![preview 1](57/preview_1.png) \| ![preview 2](57/preview_2.png) \| ![preview 3](57/preview_3.png) \| ![preview 4](57/preview_4.png) \| ![preview 5](57/preview_5.png) \| ![preview 6](57/preview_6.png) \| ![preview 7](57/preview_7.png) \| ![preview 8](57/preview_8.png) \| \| 58 \| 159 \| [Download](58/dataset.zip) \| ![preview 1](58/preview_1.png) \| ![preview 2](58/preview_2.png) \| ![preview 3](58/preview_3.png) \| ![preview 4](58/preview_4.png) \| ![preview 5](58/preview_5.png) \| ![preview 6](58/preview_6.png) \| ![preview 7](58/preview_7.png) \| ![preview 8](58/preview_8.png) \| \| 59 \| 41 \| [Download](59/dataset.zip) \| ![preview 1](59/preview_1.png) \| ![preview 2](59/preview_2.png) \| ![preview 3](59/preview_3.png) \| ![preview 4](59/preview_4.png) \| ![preview 5](59/preview_5.png) \| ![preview 6](59/preview_6.png) \| ![preview 7](59/preview_7.png) \| ![preview 8](59/preview_8.png) \| \| 60 \| 14 \| [Download](60/dataset.zip) \| ![preview 1](60/preview_1.png) \| ![preview 2](60/preview_2.png) \| ![preview 3](60/preview_3.png) \| ![preview 4](60/preview_4.png) \| ![preview 5](60/preview_5.png) \| ![preview 6](60/preview_6.png) \| ![preview 7](60/preview_7.png) \| ![preview 8](60/preview_8.png) \| \| 61 \| 32 \| [Download](61/dataset.zip) \| ![preview 1](61/preview_1.png) \| ![preview 2](61/preview_2.png) \| ![preview 3](61/preview_3.png) \| ![preview 4](61/preview_4.png) \| ![preview 5](61/preview_5.png) \| ![preview 6](61/preview_6.png) \| ![preview 7](61/preview_7.png) \| ![preview 8](61/preview_8.png) \| \| 62 \| 29 \| [Download](62/dataset.zip) \| ![preview 1](62/preview_1.png) \| ![preview 2](62/preview_2.png) \| ![preview 3](62/preview_3.png) \| ![preview 4](62/preview_4.png) \| ![preview 5](62/preview_5.png) \| ![preview 6](62/preview_6.png) \| ![preview 7](62/preview_7.png) \| ![preview 8](62/preview_8.png) \| \| 63 \| 388 \| [Download](63/dataset.zip) \| ![preview 1](63/preview_1.png) \| ![preview 2](63/preview_2.png) \| ![preview 3](63/preview_3.png) \| ![preview 4](63/preview_4.png) \| ![preview 5](63/preview_5.png) \| ![preview 6](63/preview_6.png) \| ![preview 7](63/preview_7.png) \| ![preview 8](63/preview_8.png) \| \| 64 \| 42 \| [Download](64/dataset.zip) \| ![preview 1](64/preview_1.png) \| ![preview 2](64/preview_2.png) \| ![preview 3](64/preview_3.png) \| ![preview 4](64/preview_4.png) \| ![preview 5](64/preview_5.png) \| ![preview 6](64/preview_6.png) \| ![preview 7](64/preview_7.png) \| ![preview 8](64/preview_8.png) \| \| 65 \| 124 \| [Download](65/dataset.zip) \| ![preview 1](65/preview_1.png) \| ![preview 2](65/preview_2.png) \| ![preview 3](65/preview_3.png) \| ![preview 4](65/preview_4.png) \| ![preview 5](65/preview_5.png) \| ![preview 6](65/preview_6.png) \| ![preview 7](65/preview_7.png) \| ![preview 8](65/preview_8.png) \| \| 66 \| 24 \| [Download](66/dataset.zip) \| ![preview 1](66/preview_1.png) \| ![preview 2](66/preview_2.png) \| ![preview 3](66/preview_3.png) \| ![preview 4](66/preview_4.png) \| ![preview 5](66/preview_5.png) \| ![preview 6](66/preview_6.png) \| ![preview 7](66/preview_7.png) \| ![preview 8](66/preview_8.png) \| \| 67 \| 25 \| [Download](67/dataset.zip) \| ![preview 1](67/preview_1.png) \| ![preview 2](67/preview_2.png) \| ![preview 3](67/preview_3.png) \| ![preview 4](67/preview_4.png) \| ![preview 5](67/preview_5.png) \| ![preview 6](67/preview_6.png) \| ![preview 7](67/preview_7.png) \| ![preview 8](67/preview_8.png) \| \| 68 \| 20 \| [Download](68/dataset.zip) \| ![preview 1](68/preview_1.png) \| ![preview 2](68/preview_2.png) \| ![preview 3](68/preview_3.png) \| ![preview 4](68/preview_4.png) \| ![preview 5](68/preview_5.png) \| ![preview 6](68/preview_6.png) \| ![preview 7](68/preview_7.png) \| ![preview 8](68/preview_8.png) \| \| 69 \| 45 \| [Download](69/dataset.zip) \| ![preview 1](69/preview_1.png) \| ![preview 2](69/preview_2.png) \| ![preview 3](69/preview_3.png) \| ![preview 4](69/preview_4.png) \| ![preview 5](69/preview_5.png) \| ![preview 6](69/preview_6.png) \| ![preview 7](69/preview_7.png) \| ![preview 8](69/preview_8.png) \| \| 70 \| 20 \| [Download](70/dataset.zip) \| ![preview 1](70/preview_1.png) \| ![preview 2](70/preview_2.png) \| ![preview 3](70/preview_3.png) \| ![preview 4](70/preview_4.png) \| ![preview 5](70/preview_5.png) \| ![preview 6](70/preview_6.png) \| ![preview 7](70/preview_7.png) \| ![preview 8](70/preview_8.png) \| \| 71 \| 21 \| [Download](71/dataset.zip) \| ![preview 1](71/preview_1.png) \| ![preview 2](71/preview_2.png) \| ![preview 3](71/preview_3.png) \| ![preview 4](71/preview_4.png) \| ![preview 5](71/preview_5.png) \| ![preview 6](71/preview_6.png) \| ![preview 7](71/preview_7.png) \| ![preview 8](71/preview_8.png) \| \| 72 \| 31 \| [Download](72/dataset.zip) \| ![preview 1](72/preview_1.png) \| ![preview 2](72/preview_2.png) \| ![preview 3](72/preview_3.png) \| ![preview 4](72/preview_4.png) \| ![preview 5](72/preview_5.png) \| ![preview 6](72/preview_6.png) \| ![preview 7](72/preview_7.png) \| ![preview 8](72/preview_8.png) \| \| 73 \| 26 \| [Download](73/dataset.zip) \| ![preview 1](73/preview_1.png) \| ![preview 2](73/preview_2.png) \| ![preview 3](73/preview_3.png) \| ![preview 4](73/preview_4.png) \| ![preview 5](73/preview_5.png) \| ![preview 6](73/preview_6.png) \| ![preview 7](73/preview_7.png) \| ![preview 8](73/preview_8.png) \| \| 74 \| 14 \| [Download](74/dataset.zip) \| ![preview 1](74/preview_1.png) \| ![preview 2](74/preview_2.png) \| ![preview 3](74/preview_3.png) \| ![preview 4](74/preview_4.png) \| ![preview 5](74/preview_5.png) \| ![preview 6](74/preview_6.png) \| ![preview 7](74/preview_7.png) \| ![preview 8](74/preview_8.png) \| \| 75 \| 33 \| [Download](75/dataset.zip) \| ![preview 1](75/preview_1.png) \| ![preview 2](75/preview_2.png) \| ![preview 3](75/preview_3.png) \| ![preview 4](75/preview_4.png) \| ![preview 5](75/preview_5.png) \| ![preview 6](75/preview_6.png) \| ![preview 7](75/preview_7.png) \| ![preview 8](75/preview_8.png) \| \| 76 \| 21 \| [Download](76/dataset.zip) \| ![preview 1](76/preview_1.png) \| ![preview 2](76/preview_2.png) \| ![preview 3](76/preview_3.png) \| ![preview 4](76/preview_4.png) \| ![preview 5](76/preview_5.png) \| ![preview 6](76/preview_6.png) \| ![preview 7](76/preview_7.png) \| ![preview 8](76/preview_8.png) \| \| 77 \| 9 \| [Download](77/dataset.zip) \| ![preview 1](77/preview_1.png) \| ![preview 2](77/preview_2.png) \| ![preview 3](77/preview_3.png) \| ![preview 4](77/preview_4.png) \| ![preview 5](77/preview_5.png) \| ![preview 6](77/preview_6.png) \| ![preview 7](77/preview_7.png) \| ![preview 8](77/preview_8.png) \| \| 78 \| 17 \| [Download](78/dataset.zip) \| ![preview 1](78/preview_1.png) \| ![preview 2](78/preview_2.png) \| ![preview 3](78/preview_3.png) \| ![preview 4](78/preview_4.png) \| ![preview 5](78/preview_5.png) \| ![preview 6](78/preview_6.png) \| ![preview 7](78/preview_7.png) \| ![preview 8](78/preview_8.png) \| \| 79 \| 32 \| [Download](79/dataset.zip) \| ![preview 1](79/preview_1.png) \| ![preview 2](79/preview_2.png) \| ![preview 3](79/preview_3.png) \| ![preview 4](79/preview_4.png) \| ![preview 5](79/preview_5.png) \| ![preview 6](79/preview_6.png) \| ![preview 7](79/preview_7.png) \| ![preview 8](79/preview_8.png) \| \| 80 \| 24 \| [Download](80/dataset.zip) \| ![preview 1](80/preview_1.png) \| ![preview 2](80/preview_2.png) \| ![preview 3](80/preview_3.png) \| ![preview 4](80/preview_4.png) \| ![preview 5](80/preview_5.png) \| ![preview 6](80/preview_6.png) \| ![preview 7](80/preview_7.png) \| ![preview 8](80/preview_8.png) \| \| 81 \| 26 \| [Download](81/dataset.zip) \| ![preview 1](81/preview_1.png) \| ![preview 2](81/preview_2.png) \| ![preview 3](81/preview_3.png) \| ![preview 4](81/preview_4.png) \| ![preview 5](81/preview_5.png) \| ![preview 6](81/preview_6.png) \| ![preview 7](81/preview_7.png) \| ![preview 8](81/preview_8.png) \| \| 82 \| 21 \| [Download](82/dataset.zip) \| ![preview 1](82/preview_1.png) \| ![preview 2](82/preview_2.png) \| ![preview 3](82/preview_3.png) \| ![preview 4](82/preview_4.png) \| ![preview 5](82/preview_5.png) \| ![preview 6](82/preview_6.png) \| ![preview 7](82/preview_7.png) \| ![preview 8](82/preview_8.png) \| \| 83 \| 18 \| [Download](83/dataset.zip) \| ![preview 1](83/preview_1.png) \| ![preview 2](83/preview_2.png) \| ![preview 3](83/preview_3.png) \| ![preview 4](83/preview_4.png) \| ![preview 5](83/preview_5.png) \| ![preview 6](83/preview_6.png) \| ![preview 7](83/preview_7.png) \| ![preview 8](83/preview_8.png) \| \| 84 \| 331 \| [Download](84/dataset.zip) \| ![preview 1](84/preview_1.png) \| ![preview 2](84/preview_2.png) \| ![preview 3](84/preview_3.png) \| ![preview 4](84/preview_4.png) \| ![preview 5](84/preview_5.png) \| ![preview 6](84/preview_6.png) \| ![preview 7](84/preview_7.png) \| ![preview 8](84/preview_8.png) \| \| 85 \| 12 \| [Download](85/dataset.zip) \| ![preview 1](85/preview_1.png) \| ![preview 2](85/preview_2.png) \| ![preview 3](85/preview_3.png) \| ![preview 4](85/preview_4.png) \| ![preview 5](85/preview_5.png) \| ![preview 6](85/preview_6.png) \| ![preview 7](85/preview_7.png) \| ![preview 8](85/preview_8.png) \| \| 86 \| 20 \| [Download](86/dataset.zip) \| ![preview 1](86/preview_1.png) \| ![preview 2](86/preview_2.png) \| ![preview 3](86/preview_3.png) \| ![preview 4](86/preview_4.png) \| ![preview 5](86/preview_5.png) \| ![preview 6](86/preview_6.png) \| ![preview 7](86/preview_7.png) \| ![preview 8](86/preview_8.png) \| \| 87 \| 18 \| [Download](87/dataset.zip) \| ![preview 1](87/preview_1.png) \| ![preview 2](87/preview_2.png) \| ![preview 3](87/preview_3.png) \| ![preview 4](87/preview_4.png) \| ![preview 5](87/preview_5.png) \| ![preview 6](87/preview_6.png) \| ![preview 7](87/preview_7.png) \| ![preview 8](87/preview_8.png) \| \| 88 \| 101 \| [Download](88/dataset.zip) \| ![preview 1](88/preview_1.png) \| ![preview 2](88/preview_2.png) \| ![preview 3](88/preview_3.png) \| ![preview 4](88/preview_4.png) \| ![preview 5](88/preview_5.png) \| ![preview 6](88/preview_6.png) \| ![preview 7](88/preview_7.png) \| ![preview 8](88/preview_8.png) \| \| 89 \| 813 \| [Download](89/dataset.zip) \| ![preview 1](89/preview_1.png) \| ![preview 2](89/preview_2.png) \| ![preview 3](89/preview_3.png) \| ![preview 4](89/preview_4.png) \| ![preview 5](89/preview_5.png) \| ![preview 6](89/preview_6.png) \| ![preview 7](89/preview_7.png) \| ![preview 8](89/preview_8.png) \| \| 90 \| 19 \| [Download](90/dataset.zip) \| ![preview 1](90/preview_1.png) \| ![preview 2](90/preview_2.png) \| ![preview 3](90/preview_3.png) \| ![preview 4](90/preview_4.png) \| ![preview 5](90/preview_5.png) \| ![preview 6](90/preview_6.png) \| ![preview 7](90/preview_7.png) \| ![preview 8](90/preview_8.png) \| \| 91 \| 34 \| [Download](91/dataset.zip) \| ![preview 1](91/preview_1.png) \| ![preview 2](91/preview_2.png) \| ![preview 3](91/preview_3.png) \| ![preview 4](91/preview_4.png) \| ![preview 5](91/preview_5.png) \| ![preview 6](91/preview_6.png) \| ![preview 7](91/preview_7.png) \| ![preview 8](91/preview_8.png) \| \| 92 \| 13 \| [Download](92/dataset.zip) \| ![preview 1](92/preview_1.png) \| ![preview 2](92/preview_2.png) \| ![preview 3](92/preview_3.png) \| ![preview 4](92/preview_4.png) \| ![preview 5](92/preview_5.png) \| ![preview 6](92/preview_6.png) \| ![preview 7](92/preview_7.png) \| ![preview 8](92/preview_8.png) \| \| 93 \| 11 \| [Download](93/dataset.zip) \| ![preview 1](93/preview_1.png) \| ![preview 2](93/preview_2.png) \| ![preview 3](93/preview_3.png) \| ![preview 4](93/preview_4.png) \| ![preview 5](93/preview_5.png) \| ![preview 6](93/preview_6.png) \| ![preview 7](93/preview_7.png) \| ![preview 8](93/preview_8.png) \| \| 94 \| 13 \| [Download](94/dataset.zip) \| ![preview 1](94/preview_1.png) \| ![preview 2](94/preview_2.png) \| ![preview 3](94/preview_3.png) \| ![preview 4](94/preview_4.png) \| ![preview 5](94/preview_5.png) \| ![preview 6](94/preview_6.png) \| ![preview 7](94/preview_7.png) \| ![preview 8](94/preview_8.png) \| \| 95 \| 11 \| [Download](95/dataset.zip) \| ![preview 1](95/preview_1.png) \| ![preview 2](95/preview_2.png) \| ![preview 3](95/preview_3.png) \| ![preview 4](95/preview_4.png) \| ![preview 5](95/preview_5.png) \| ![preview 6](95/preview_6.png) \| ![preview 7](95/preview_7.png) \| ![preview 8](95/preview_8.png) \| \| 96 \| 33 \| [Download](96/dataset.zip) \| ![preview 1](96/preview_1.png) \| ![preview 2](96/preview_2.png) \| ![preview 3](96/preview_3.png) \| ![preview 4](96/preview_4.png) \| ![preview 5](96/preview_5.png) \| ![preview 6](96/preview_6.png) \| ![preview 7](96/preview_7.png) \| ![preview 8](96/preview_8.png) \| \| 97 \| 17 \| [Download](97/dataset.zip) \| ![preview 1](97/preview_1.png) \| ![preview 2](97/preview_2.png) \| ![preview 3](97/preview_3.png) \| ![preview 4](97/preview_4.png) \| ![preview 5](97/preview_5.png) \| ![preview 6](97/preview_6.png) \| ![preview 7](97/preview_7.png) \| ![preview 8](97/preview_8.png) \| \| 98 \| 21 \| [Download](98/dataset.zip) \| ![preview 1](98/preview_1.png) \| ![preview 2](98/preview_2.png) \| ![preview 3](98/preview_3.png) \| ![preview 4](98/preview_4.png) \| ![preview 5](98/preview_5.png) \| ![preview 6](98/preview_6.png) \| ![preview 7](98/preview_7.png) \| ![preview 8](98/preview_8.png) \| \| 99 \| 25 \| [Download](99/dataset.zip) \| ![preview 1](99/preview_1.png) \| ![preview 2](99/preview_2.png) \| ![preview 3](99/preview_3.png) \| ![preview 4](99/preview_4.png) \| ![preview 5](99/preview_5.png) \| ![preview 6](99/preview_6.png) \| ![preview 7](99/preview_7.png) \| ![preview 8](99/preview_8.png) \| \| 100 \| 25 \| [Download](100/dataset.zip) \| ![preview 1](100/preview_1.png) \| ![preview 2](100/preview_2.png) \| ![preview 3](100/preview_3.png) \| ![preview 4](100/preview_4.png) \| ![preview 5](100/preview_5.png) \| ![preview 6](100/preview_6.png) \| ![preview 7](100/preview_7.png) \| ![preview 8](100/preview_8.png) \| \| 101 \| 16 \| [Download](101/dataset.zip) \| ![preview 1](101/preview_1.png) \| ![preview 2](101/preview_2.png) \| ![preview 3](101/preview_3.png) \| ![preview 4](101/preview_4.png) \| ![preview 5](101/preview_5.png) \| ![preview 6](101/preview_6.png) \| ![preview 7](101/preview_7.png) \| ![preview 8](101/preview_8.png) \| \| 102 \| 34 \| [Download](102/dataset.zip) \| ![preview 1](102/preview_1.png) \| ![preview 2](102/preview_2.png) \| ![preview 3](102/preview_3.png) \| ![preview 4](102/preview_4.png) \| ![preview 5](102/preview_5.png) \| ![preview 6](102/preview_6.png) \| ![preview 7](102/preview_7.png) \| ![preview 8](102/preview_8.png) \| \| 103 \| 52 \| [Download](103/dataset.zip) \| ![preview 1](103/preview_1.png) \| ![preview 2](103/preview_2.png) \| ![preview 3](103/preview_3.png) \| ![preview 4](103/preview_4.png) \| ![preview 5](103/preview_5.png) \| ![preview 6](103/preview_6.png) \| ![preview 7](103/preview_7.png) \| ![preview 8](103/preview_8.png) \| \| 104 \| 199 \| [Download](104/dataset.zip) \| ![preview 1](104/preview_1.png) \| ![preview 2](104/preview_2.png) \| ![preview 3](104/preview_3.png) \| ![preview 4](104/preview_4.png) \| ![preview 5](104/preview_5.png) \| ![preview 6](104/preview_6.png) \| ![preview 7](104/preview_7.png) \| ![preview 8](104/preview_8.png) \| \| 105 \| 34 \| [Download](105/dataset.zip) \| ![preview 1](105/preview_1.png) \| ![preview 2](105/preview_2.png) \| ![preview 3](105/preview_3.png) \| ![preview 4](105/preview_4.png) \| ![preview 5](105/preview_5.png) \| ![preview 6](105/preview_6.png) \| ![preview 7](105/preview_7.png) \| ![preview 8](105/preview_8.png) \| \| 106 \| 36 \| [Download](106/dataset.zip) \| ![preview 1](106/preview_1.png) \| ![preview 2](106/preview_2.png) \| ![preview 3](106/preview_3.png) \| ![preview 4](106/preview_4.png) \| ![preview 5](106/preview_5.png) \| ![preview 6](106/preview_6.png) \| ![preview 7](106/preview_7.png) \| ![preview 8](106/preview_8.png) \| \| 107 \| 11 \| [Download](107/dataset.zip) \| ![preview 1](107/preview_1.png) \| ![preview 2](107/preview_2.png) \| ![preview 3](107/preview_3.png) \| ![preview 4](107/preview_4.png) \| ![preview 5](107/preview_5.png) \| ![preview 6](107/preview_6.png) \| ![preview 7](107/preview_7.png) \| ![preview 8](107/preview_8.png) \| \| 108 \| 31 \| [Download](108/dataset.zip) \| ![preview 1](108/preview_1.png) \| ![preview 2](108/preview_2.png) \| ![preview 3](108/preview_3.png) \| ![preview 4](108/preview_4.png) \| ![preview 5](108/preview_5.png) \| ![preview 6](108/preview_6.png) \| ![preview 7](108/preview_7.png) \| ![preview 8](108/preview_8.png) \| \| 109 \| 19 \| [Download](109/dataset.zip) \| ![preview 1](109/preview_1.png) \| ![preview 2](109/preview_2.png) \| ![preview 3](109/preview_3.png) \| ![preview 4](109/preview_4.png) \| ![preview 5](109/preview_5.png) \| ![preview 6](109/preview_6.png) \| ![preview 7](109/preview_7.png) \| ![preview 8](109/preview_8.png) \| \| 110 \| 22 \| [Download](110/dataset.zip) \| ![preview 1](110/preview_1.png) \| ![preview 2](110/preview_2.png) \| ![preview 3](110/preview_3.png) \| ![preview 4](110/preview_4.png) \| ![preview 5](110/preview_5.png) \| ![preview 6](110/preview_6.png) \| ![preview 7](110/preview_7.png) \| ![preview 8](110/preview_8.png) \| \| 111 \| 7 \| [Download](111/dataset.zip) \| ![preview 1](111/preview_1.png) \| ![preview 2](111/preview_2.png) \| ![preview 3](111/preview_3.png) \| ![preview 4](111/preview_4.png) \| ![preview 5](111/preview_5.png) \| ![preview 6](111/preview_6.png) \| ![preview 7](111/preview_7.png) \| N/A \| \| 112 \| 67 \| [Download](112/dataset.zip) \| ![preview 1](112/preview_1.png) \| ![preview 2](112/preview_2.png) \| ![preview 3](112/preview_3.png) \| ![preview 4](112/preview_4.png) \| ![preview 5](112/preview_5.png) \| ![preview 6](112/preview_6.png) \| ![preview 7](112/preview_7.png) \| ![preview 8](112/preview_8.png) \| \| 113 \| 23 \| [Download](113/dataset.zip) \| ![preview 1](113/preview_1.png) \| ![preview 2](113/preview_2.png) \| ![preview 3](113/preview_3.png) \| ![preview 4](113/preview_4.png) \| ![preview 5](113/preview_5.png) \| ![preview 6](113/preview_6.png) \| ![preview 7](113/preview_7.png) \| ![preview 8](113/preview_8.png) \| \| 114 \| 390 \| [Download](114/dataset.zip) \| ![preview 1](114/preview_1.png) \| ![preview 2](114/preview_2.png) \| ![preview 3](114/preview_3.png) \| ![preview 4](114/preview_4.png) \| ![preview 5](114/preview_5.png) \| ![preview 6](114/preview_6.png) \| ![preview 7](114/preview_7.png) \| ![preview 8](114/preview_8.png) \| \| 115 \| 18 \| [Download](115/dataset.zip) \| ![preview 1](115/preview_1.png) \| ![preview 2](115/preview_2.png) \| ![preview 3](115/preview_3.png) \| ![preview 4](115/preview_4.png) \| ![preview 5](115/preview_5.png) \| ![preview 6](115/preview_6.png) \| ![preview 7](115/preview_7.png) \| ![preview 8](115/preview_8.png) \| \| 116 \| 10 \| [Download](116/dataset.zip) \| ![preview 1](116/preview_1.png) \| ![preview 2](116/preview_2.png) \| ![preview 3](116/preview_3.png) \| ![preview 4](116/preview_4.png) \| ![preview 5](116/preview_5.png) \| ![preview 6](116/preview_6.png) \| ![preview 7](116/preview_7.png) \| ![preview 8](116/preview_8.png) \| \| 117 \| 31 \| [Download](117/dataset.zip) \| ![preview 1](117/preview_1.png) \| ![preview 2](117/preview_2.png) \| ![preview 3](117/preview_3.png) \| ![preview 4](117/preview_4.png) \| ![preview 5](117/preview_5.png) \| ![preview 6](117/preview_6.png) \| ![preview 7](117/preview_7.png) \| ![preview 8](117/preview_8.png) \| \| 118 \| 46 \| [Download](118/dataset.zip) \| ![preview 1](118/preview_1.png) \| ![preview 2](118/preview_2.png) \| ![preview 3](118/preview_3.png) \| ![preview 4](118/preview_4.png) \| ![preview 5](118/preview_5.png) \| ![preview 6](118/preview_6.png) \| ![preview 7](118/preview_7.png) \| ![preview 8](118/preview_8.png) \| \| 119 \| 16 \| [Download](119/dataset.zip) \| ![preview 1](119/preview_1.png) \| ![preview 2](119/preview_2.png) \| ![preview 3](119/preview_3.png) \| ![preview 4](119/preview_4.png) \| ![preview 5](119/preview_5.png) \| ![preview 6](119/preview_6.png) \| ![preview 7](119/preview_7.png) \| ![preview 8](119/preview_8.png) \| \| 120 \| 32 \| [Download](120/dataset.zip) \| ![preview 1](120/preview_1.png) \| ![preview 2](120/preview_2.png) \| ![preview 3](120/preview_3.png) \| ![preview 4](120/preview_4.png) \| ![preview 5](120/preview_5.png) \| ![preview 6](120/preview_6.png) \| ![preview 7](120/preview_7.png) \| ![preview 8](120/preview_8.png) \| \| 121 \| 10 \| [Download](121/dataset.zip) \| ![preview 1](121/preview_1.png) \| ![preview 2](121/preview_2.png) \| ![preview 3](121/preview_3.png) \| ![preview 4](121/preview_4.png) \| ![preview 5](121/preview_5.png) \| ![preview 6](121/preview_6.png) \| ![preview 7](121/preview_7.png) \| ![preview 8](121/preview_8.png) \| \| 122 \| 126 \| [Download](122/dataset.zip) \| ![preview 1](122/preview_1.png) \| ![preview 2](122/preview_2.png) \| ![preview 3](122/preview_3.png) \| ![preview 4](122/preview_4.png) \| ![preview 5](122/preview_5.png) \| ![preview 6](122/preview_6.png) \| ![preview 7](122/preview_7.png) \| ![preview 8](122/preview_8.png) \| \| 123 \| 48 \| [Download](123/dataset.zip) \| ![preview 1](123/preview_1.png) \| ![preview 2](123/preview_2.png) \| ![preview 3](123/preview_3.png) \| ![preview 4](123/preview_4.png) \| ![preview 5](123/preview_5.png) \| ![preview 6](123/preview_6.png) \| ![preview 7](123/preview_7.png) \| ![preview 8](123/preview_8.png) \| \| 124 \| 21 \| [Download](124/dataset.zip) \| ![preview 1](124/preview_1.png) \| ![preview 2](124/preview_2.png) \| ![preview 3](124/preview_3.png) \| ![preview 4](124/preview_4.png) \| ![preview 5](124/preview_5.png) \| ![preview 6](124/preview_6.png) \| ![preview 7](124/preview_7.png) \| ![preview 8](124/preview_8.png) \| \| 125 \| 10 \| [Download](125/dataset.zip) \| ![preview 1](125/preview_1.png) \| ![preview 2](125/preview_2.png) \| ![preview 3](125/preview_3.png) \| ![preview 4](125/preview_4.png) \| ![preview 5](125/preview_5.png) \| ![preview 6](125/preview_6.png) \| ![preview 7](125/preview_7.png) \| ![preview 8](125/preview_8.png) \| \| 126 \| 52 \| [Download](126/dataset.zip) \| ![preview 1](126/preview_1.png) \| ![preview 2](126/preview_2.png) \| ![preview 3](126/preview_3.png) \| ![preview 4](126/preview_4.png) \| ![preview 5](126/preview_5.png) \| ![preview 6](126/preview_6.png) \| ![preview 7](126/preview_7.png) \| ![preview 8](126/preview_8.png) \| \| 127 \| 42 \| [Download](127/dataset.zip) \| ![preview 1](127/preview_1.png) \| ![preview 2](127/preview_2.png) \| ![preview 3](127/preview_3.png) \| ![preview 4](127/preview_4.png) \| ![preview 5](127/preview_5.png) \| ![preview 6](127/preview_6.png) \| ![preview 7](127/preview_7.png) \| ![preview 8](127/preview_8.png) \| \| 128 \| 32 \| [Download](128/dataset.zip) \| ![preview 1](128/preview_1.png) \| ![preview 2](128/preview_2.png) \| ![preview 3](128/preview_3.png) \| ![preview 4](128/preview_4.png) \| ![preview 5](128/preview_5.png) \| ![preview 6](128/preview_6.png) \| ![preview 7](128/preview_7.png) \| ![preview 8](128/preview_8.png) \| \| 129 \| 28 \| [Download](129/dataset.zip) \| ![preview 1](129/preview_1.png) \| ![preview 2](129/preview_2.png) \| ![preview 3](129/preview_3.png) \| ![preview 4](129/preview_4.png) \| ![preview 5](129/preview_5.png) \| ![preview 6](129/preview_6.png) \| ![preview 7](129/preview_7.png) \| ![preview 8](129/preview_8.png) \| \| 130 \| 13 \| [Download](130/dataset.zip) \| ![preview 1](130/preview_1.png) \| ![preview 2](130/preview_2.png) \| ![preview 3](130/preview_3.png) \| ![preview 4](130/preview_4.png) \| ![preview 5](130/preview_5.png) \| ![preview 6](130/preview_6.png) \| ![preview 7](130/preview_7.png) \| ![preview 8](130/preview_8.png) \| \| 131 \| 9 \| [Download](131/dataset.zip) \| ![preview 1](131/preview_1.png) \| ![preview 2](131/preview_2.png) \| ![preview 3](131/preview_3.png) \| ![preview 4](131/preview_4.png) \| ![preview 5](131/preview_5.png) \| ![preview 6](131/preview_6.png) \| ![preview 7](131/preview_7.png) \| ![preview 8](131/preview_8.png) \| \| 132 \| 57 \| [Download](132/dataset.zip) \| ![preview 1](132/preview_1.png) \| ![preview 2](132/preview_2.png) \| ![preview 3](132/preview_3.png) \| ![preview 4](132/preview_4.png) \| ![preview 5](132/preview_5.png) \| ![preview 6](132/preview_6.png) \| ![preview 7](132/preview_7.png) \| ![preview 8](132/preview_8.png) \| \| 133 \| 32 \| [Download](133/dataset.zip) \| ![preview 1](133/preview_1.png) \| ![preview 2](133/preview_2.png) \| ![preview 3](133/preview_3.png) \| ![preview 4](133/preview_4.png) \| ![preview 5](133/preview_5.png) \| ![preview 6](133/preview_6.png) \| ![preview 7](133/preview_7.png) \| ![preview 8](133/preview_8.png) \| \| 134 \| 14 \| [Download](134/dataset.zip) \| ![preview 1](134/preview_1.png) \| ![preview 2](134/preview_2.png) \| ![preview 3](134/preview_3.png) \| ![preview 4](134/preview_4.png) \| ![preview 5](134/preview_5.png) \| ![preview 6](134/preview_6.png) \| ![preview 7](134/preview_7.png) \| ![preview 8](134/preview_8.png) \| \| 135 \| 138 \| [Download](135/dataset.zip) \| ![preview 1](135/preview_1.png) \| ![preview 2](135/preview_2.png) \| ![preview 3](135/preview_3.png) \| ![preview 4](135/preview_4.png) \| ![preview 5](135/preview_5.png) \| ![preview 6](135/preview_6.png) \| ![preview 7](135/preview_7.png) \| ![preview 8](135/preview_8.png) \| \| 136 \| 14 \| [Download](136/dataset.zip) \| ![preview 1](136/preview_1.png) \| ![preview 2](136/preview_2.png) \| ![preview 3](136/preview_3.png) \| ![preview 4](136/preview_4.png) \| ![preview 5](136/preview_5.png) \| ![preview 6](136/preview_6.png) \| ![preview 7](136/preview_7.png) \| ![preview 8](136/preview_8.png) \| \| 137 \| 11 \| [Download](137/dataset.zip) \| ![preview 1](137/preview_1.png) \| ![preview 2](137/preview_2.png) \| ![preview 3](137/preview_3.png) \| ![preview 4](137/preview_4.png) \| ![preview 5](137/preview_5.png) \| ![preview 6](137/preview_6.png) \| ![preview 7](137/preview_7.png) \| ![preview 8](137/preview_8.png) \| \| 138 \| 6 \| [Download](138/dataset.zip) \| ![preview 1](138/preview_1.png) \| ![preview 2](138/preview_2.png) \| ![preview 3](138/preview_3.png) \| ![preview 4](138/preview_4.png) \| ![preview 5](138/preview_5.png) \| ![preview 6](138/preview_6.png) \| N/A \| N/A \| \| 139 \| 33 \| [Download](139/dataset.zip) \| ![preview 1](139/preview_1.png) \| ![preview 2](139/preview_2.png) \| ![preview 3](139/preview_3.png) \| ![preview 4](139/preview_4.png) \| ![preview 5](139/preview_5.png) \| ![preview 6](139/preview_6.png) \| ![preview 7](139/preview_7.png) \| ![preview 8](139/preview_8.png) \| \| 140 \| 7 \| [Download](140/dataset.zip) \| ![preview 1](140/preview_1.png) \| ![preview 2](140/preview_2.png) \| ![preview 3](140/preview_3.png) \| ![preview 4](140/preview_4.png) \| ![preview 5](140/preview_5.png) \| ![preview 6](140/preview_6.png) \| ![preview 7](140/preview_7.png) \| N/A \| \| 141 \| 8 \| [Download](141/dataset.zip) \| ![preview 1](141/preview_1.png) \| ![preview 2](141/preview_2.png) \| ![preview 3](141/preview_3.png) \| ![preview 4](141/preview_4.png) \| ![preview 5](141/preview_5.png) \| ![preview 6](141/preview_6.png) \| ![preview 7](141/preview_7.png) \| ![preview 8](141/preview_8.png) \| \| 142 \| 8 \| [Download](142/dataset.zip) \| ![preview 1](142/preview_1.png) \| ![preview 2](142/preview_2.png) \| ![preview 3](142/preview_3.png) \| ![preview 4](142/preview_4.png) \| ![preview 5](142/preview_5.png) \| ![preview 6](142/preview_6.png) \| ![preview 7](142/preview_7.png) \| ![preview 8](142/preview_8.png) \| \| 143 \| 15 \| [Download](143/dataset.zip) \| ![preview 1](143/preview_1.png) \| ![preview 2](143/preview_2.png) \| ![preview 3](143/preview_3.png) \| ![preview 4](143/preview_4.png) \| ![preview 5](143/preview_5.png) \| ![preview 6](143/preview_6.png) \| ![preview 7](143/preview_7.png) \| ![preview 8](143/preview_8.png) \| \| 144 \| 17 \| [Download](144/dataset.zip) \| ![preview 1](144/preview_1.png) \| ![preview 2](144/preview_2.png) \| ![preview 3](144/preview_3.png) \| ![preview 4](144/preview_4.png) \| ![preview 5](144/preview_5.png) \| ![preview 6](144/preview_6.png) \| ![preview 7](144/preview_7.png) \| ![preview 8](144/preview_8.png) \| \| noise \| 467 \| [Download](-1/dataset.zip) \| ![preview 1](-1/preview_1.png) \| ![preview 2](-1/preview_2.png) \| ![preview 3](-1/preview_3.png) \| ![preview 4](-1/preview_4.png) \| ![preview 5](-1/preview_5.png) \| ![preview 6](-1/preview_6.png) \| ![preview 7](-1/preview_7.png) \| ![preview 8](-1/preview_8.png) \|
open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview	--- pretty_name: Evaluation run of cognitivecomputations/dolphin-2.8-experiment26-7b-preview dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [cognitivecomputations/dolphin-2.8-experiment26-7b-preview](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview)\ \ 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_cognitivecomputations__dolphin-2.8-experiment26-7b-preview\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-03T20:15:12.993951](https://huggingface.co/datasets/open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview/blob/main/results_2024-03-03T20-15-12.993951.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\": 0.6353244379094956,\n\ \ \"acc_stderr\": 0.032491657533462066,\n \"acc_norm\": 0.6360998788498634,\n\ \ \"acc_norm_stderr\": 0.033161036274808056,\n \"mc1\": 0.3769889840881273,\n\ \ \"mc1_stderr\": 0.016965517578930354,\n \"mc2\": 0.5487265863315941,\n\ \ \"mc2_stderr\": 0.015174281776839011\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6143344709897611,\n \"acc_stderr\": 0.014224250973257186,\n\ \ \"acc_norm\": 0.6450511945392492,\n \"acc_norm_stderr\": 0.013983036904094094\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6413065126468831,\n\ \ \"acc_stderr\": 0.004786368011500458,\n \"acc_norm\": 0.8378809002190799,\n\ \ \"acc_norm_stderr\": 0.00367806799442448\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5703703703703704,\n\ \ \"acc_stderr\": 0.04276349494376599,\n \"acc_norm\": 0.5703703703703704,\n\ \ \"acc_norm_stderr\": 0.04276349494376599\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.61,\n\ \ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.03621034121889507,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.03621034121889507\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \ \ \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.049999999999999996\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.56,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.630057803468208,\n\ \ \"acc_stderr\": 0.0368122963339432,\n \"acc_norm\": 0.630057803468208,\n\ \ \"acc_norm_stderr\": 0.0368122963339432\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.048786087144669955,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.048786087144669955\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108101,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108101\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.046920083813689104,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.046920083813689104\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4126984126984127,\n \"acc_stderr\": 0.025355741263055266,\n \"\ acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.025355741263055266\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\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.7419354838709677,\n \"acc_stderr\": 0.02489246917246283,\n \"\ acc_norm\": 0.7419354838709677,\n \"acc_norm_stderr\": 0.02489246917246283\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.5024630541871922,\n \"acc_stderr\": 0.03517945038691063,\n \"\ acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7676767676767676,\n \"acc_stderr\": 0.030088629490217487,\n \"\ acc_norm\": 0.7676767676767676,\n \"acc_norm_stderr\": 0.030088629490217487\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.022473253332768763,\n\ \ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.022473253332768763\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.676923076923077,\n \"acc_stderr\": 0.02371088850197057,\n \ \ \"acc_norm\": 0.676923076923077,\n \"acc_norm_stderr\": 0.02371088850197057\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131143,\n \ \ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131143\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6512605042016807,\n \"acc_stderr\": 0.030956636328566545,\n\ \ \"acc_norm\": 0.6512605042016807,\n \"acc_norm_stderr\": 0.030956636328566545\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.038615575462551684,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.038615575462551684\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8403669724770643,\n \"acc_stderr\": 0.015703498348461763,\n \"\ acc_norm\": 0.8403669724770643,\n \"acc_norm_stderr\": 0.015703498348461763\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8431372549019608,\n \"acc_stderr\": 0.025524722324553346,\n \"\ acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.025524722324553346\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.02574490253229092,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.02574490253229092\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.031024411740572213,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.031024411740572213\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7480916030534351,\n \"acc_stderr\": 0.03807387116306086,\n\ \ \"acc_norm\": 0.7480916030534351,\n \"acc_norm_stderr\": 0.03807387116306086\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.039418975265163046,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.039418975265163046\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7300613496932515,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.7300613496932515,\n \"acc_norm_stderr\": 0.034878251684978906\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\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.020930193185179333,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.020930193185179333\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\": 0.8122605363984674,\n\ \ \"acc_stderr\": 0.013964393769899133,\n \"acc_norm\": 0.8122605363984674,\n\ \ \"acc_norm_stderr\": 0.013964393769899133\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7167630057803468,\n \"acc_stderr\": 0.024257901705323378,\n\ \ \"acc_norm\": 0.7167630057803468,\n \"acc_norm_stderr\": 0.024257901705323378\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2916201117318436,\n\ \ \"acc_stderr\": 0.015201032512520437,\n \"acc_norm\": 0.2916201117318436,\n\ \ \"acc_norm_stderr\": 0.015201032512520437\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7222222222222222,\n \"acc_stderr\": 0.025646863097137904,\n\ \ \"acc_norm\": 0.7222222222222222,\n \"acc_norm_stderr\": 0.025646863097137904\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6913183279742765,\n\ \ \"acc_stderr\": 0.026236965881153266,\n \"acc_norm\": 0.6913183279742765,\n\ \ \"acc_norm_stderr\": 0.026236965881153266\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.02517104191530968,\n\ \ \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.02517104191530968\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.48226950354609927,\n \"acc_stderr\": 0.02980873964223777,\n \ \ \"acc_norm\": 0.48226950354609927,\n \"acc_norm_stderr\": 0.02980873964223777\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4667535853976532,\n\ \ \"acc_stderr\": 0.012741974333897224,\n \"acc_norm\": 0.4667535853976532,\n\ \ \"acc_norm_stderr\": 0.012741974333897224\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6433823529411765,\n \"acc_stderr\": 0.02909720956841195,\n\ \ \"acc_norm\": 0.6433823529411765,\n \"acc_norm_stderr\": 0.02909720956841195\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6617647058823529,\n \"acc_stderr\": 0.019139943748487036,\n \ \ \"acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.019139943748487036\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\": 0.7306122448979592,\n \"acc_stderr\": 0.02840125202902294,\n\ \ \"acc_norm\": 0.7306122448979592,\n \"acc_norm_stderr\": 0.02840125202902294\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8009950248756219,\n\ \ \"acc_stderr\": 0.028231365092758406,\n \"acc_norm\": 0.8009950248756219,\n\ \ \"acc_norm_stderr\": 0.028231365092758406\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.83,\n \"acc_stderr\": 0.037752516806863715,\n \ \ \"acc_norm\": 0.83,\n \"acc_norm_stderr\": 0.037752516806863715\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3769889840881273,\n\ \ \"mc1_stderr\": 0.016965517578930354,\n \"mc2\": 0.5487265863315941,\n\ \ \"mc2_stderr\": 0.015174281776839011\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8161010260457774,\n \"acc_stderr\": 0.010887916013305892\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6360879454131918,\n \ \ \"acc_stderr\": 0.013252539227966195\n }\n}\n```" repo_url: https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|arc:challenge\|25_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-03T20-15-12.993951.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|gsm8k\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hellaswag\|10_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-03T20-15-12.993951.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-03T20-15-12.993951.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '/details_harness\|winogrande\|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-03T20-15-12.993951.parquet' - config_name: results data_files: - split: 2024_03_03T20_15_12.993951 path: - results_2024-03-03T20-15-12.993951.parquet - split: latest path: - results_2024-03-03T20-15-12.993951.parquet --- # Dataset Card for Evaluation run of cognitivecomputations/dolphin-2.8-experiment26-7b-preview <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [cognitivecomputations/dolphin-2.8-experiment26-7b-preview](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview) 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_cognitivecomputations__dolphin-2.8-experiment26-7b-preview", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-03T20:15:12.993951](https://huggingface.co/datasets/open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview/blob/main/results_2024-03-03T20-15-12.993951.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": 0.6353244379094956, "acc_stderr": 0.032491657533462066, "acc_norm": 0.6360998788498634, "acc_norm_stderr": 0.033161036274808056, "mc1": 0.3769889840881273, "mc1_stderr": 0.016965517578930354, "mc2": 0.5487265863315941, "mc2_stderr": 0.015174281776839011 }, "harness\|arc:challenge\|25": { "acc": 0.6143344709897611, "acc_stderr": 0.014224250973257186, "acc_norm": 0.6450511945392492, "acc_norm_stderr": 0.013983036904094094 }, "harness\|hellaswag\|10": { "acc": 0.6413065126468831, "acc_stderr": 0.004786368011500458, "acc_norm": 0.8378809002190799, "acc_norm_stderr": 0.00367806799442448 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5703703703703704, "acc_stderr": 0.04276349494376599, "acc_norm": 0.5703703703703704, "acc_norm_stderr": 0.04276349494376599 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.75, "acc_stderr": 0.03621034121889507, "acc_norm": 0.75, "acc_norm_stderr": 0.03621034121889507 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.630057803468208, "acc_stderr": 0.0368122963339432, "acc_norm": 0.630057803468208, "acc_norm_stderr": 0.0368122963339432 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108101, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108101 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4649122807017544, "acc_stderr": 0.046920083813689104, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.046920083813689104 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4126984126984127, "acc_stderr": 0.025355741263055266, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.025355741263055266 }, "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": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7419354838709677, "acc_stderr": 0.02489246917246283, "acc_norm": 0.7419354838709677, "acc_norm_stderr": 0.02489246917246283 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5024630541871922, "acc_stderr": 0.03517945038691063, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.03517945038691063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7676767676767676, "acc_stderr": 0.030088629490217487, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.030088629490217487 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8911917098445595, "acc_stderr": 0.022473253332768763, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.022473253332768763 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.676923076923077, "acc_stderr": 0.02371088850197057, "acc_norm": 0.676923076923077, "acc_norm_stderr": 0.02371088850197057 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131143, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.028897748741131143 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6512605042016807, "acc_stderr": 0.030956636328566545, "acc_norm": 0.6512605042016807, "acc_norm_stderr": 0.030956636328566545 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.33774834437086093, "acc_stderr": 0.038615575462551684, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.038615575462551684 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8403669724770643, "acc_stderr": 0.015703498348461763, "acc_norm": 0.8403669724770643, "acc_norm_stderr": 0.015703498348461763 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8431372549019608, "acc_stderr": 0.025524722324553346, "acc_norm": 0.8431372549019608, "acc_norm_stderr": 0.025524722324553346 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8059071729957806, "acc_stderr": 0.02574490253229092, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.02574490253229092 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6905829596412556, "acc_stderr": 0.031024411740572213, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.031024411740572213 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7480916030534351, "acc_stderr": 0.03807387116306086, "acc_norm": 0.7480916030534351, "acc_norm_stderr": 0.03807387116306086 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7520661157024794, "acc_stderr": 0.039418975265163046, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.039418975265163046 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7300613496932515, "acc_stderr": 0.034878251684978906, "acc_norm": 0.7300613496932515, "acc_norm_stderr": 0.034878251684978906 }, "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": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8846153846153846, "acc_stderr": 0.020930193185179333, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.020930193185179333 }, "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": 0.8122605363984674, "acc_stderr": 0.013964393769899133, "acc_norm": 0.8122605363984674, "acc_norm_stderr": 0.013964393769899133 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7167630057803468, "acc_stderr": 0.024257901705323378, "acc_norm": 0.7167630057803468, "acc_norm_stderr": 0.024257901705323378 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2916201117318436, "acc_stderr": 0.015201032512520437, "acc_norm": 0.2916201117318436, "acc_norm_stderr": 0.015201032512520437 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.025646863097137904, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.025646863097137904 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6913183279742765, "acc_stderr": 0.026236965881153266, "acc_norm": 0.6913183279742765, "acc_norm_stderr": 0.026236965881153266 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7129629629629629, "acc_stderr": 0.02517104191530968, "acc_norm": 0.7129629629629629, "acc_norm_stderr": 0.02517104191530968 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.48226950354609927, "acc_stderr": 0.02980873964223777, "acc_norm": 0.48226950354609927, "acc_norm_stderr": 0.02980873964223777 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4667535853976532, "acc_stderr": 0.012741974333897224, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.012741974333897224 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6433823529411765, "acc_stderr": 0.02909720956841195, "acc_norm": 0.6433823529411765, "acc_norm_stderr": 0.02909720956841195 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6617647058823529, "acc_stderr": 0.019139943748487036, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.019139943748487036 }, "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": 0.7306122448979592, "acc_stderr": 0.02840125202902294, "acc_norm": 0.7306122448979592, "acc_norm_stderr": 0.02840125202902294 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8009950248756219, "acc_stderr": 0.028231365092758406, "acc_norm": 0.8009950248756219, "acc_norm_stderr": 0.028231365092758406 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.83, "acc_stderr": 0.037752516806863715, "acc_norm": 0.83, "acc_norm_stderr": 0.037752516806863715 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3769889840881273, "mc1_stderr": 0.016965517578930354, "mc2": 0.5487265863315941, "mc2_stderr": 0.015174281776839011 }, "harness\|winogrande\|5": { "acc": 0.8161010260457774, "acc_stderr": 0.010887916013305892 }, "harness\|gsm8k\|5": { "acc": 0.6360879454131918, "acc_stderr": 0.013252539227966195 } } ``` ## 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]
vic0428/imdb-card-pred-decimal	--- dataset_info: features: - name: text dtype: string - name: prompt dtype: string - name: true_cardinality dtype: int64 splits: - name: train num_bytes: 39101954.4 num_examples: 80000 - name: test num_bytes: 9775488.6 num_examples: 20000 download_size: 8384711 dataset_size: 48877443.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "imdb-card-pred-decimal" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-html-90000	--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 666516 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
runes/3D	--- license: cc ---
SUSTech/mt_bench	--- dataset_info: features: - name: question_id dtype: int64 - name: category dtype: string - name: turns list: - name: content dtype: string - name: role dtype: string - name: reference sequence: string splits: - name: train num_bytes: 46852 num_examples: 80 download_size: 31246 dataset_size: 46852 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "mt_bench" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
sid220/2713-2024-shot-prediction	--- license: mit ---
ovior/twitter_dataset_1713229857	--- 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: 2288515 num_examples: 7210 download_size: 1295624 dataset_size: 2288515 configs: - config_name: default data_files: - split: train path: data/train-* ---
MrOvkill/SVIG-v0.1	--- license: wtfpl ---
open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k	--- pretty_name: Evaluation run of NurtureAI/Orca-2-7B-16k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NurtureAI/Orca-2-7B-16k](https://huggingface.co/NurtureAI/Orca-2-7B-16k) 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 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_NurtureAI__Orca-2-7B-16k_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-25T21:39:02.599324](https://huggingface.co/datasets/open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k_public/blob/main/results_2023-11-25T21-39-02.599324.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\": 0.36746546712957223,\n\ \ \"acc_stderr\": 0.033751277531008754,\n \"acc_norm\": 0.3738175555586316,\n\ \ \"acc_norm_stderr\": 0.03459812342976094,\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.01586634640138431,\n \"mc2\": 0.45373679597767685,\n\ \ \"mc2_stderr\": 0.015753224924844992,\n \"em\": 0.21046560402684564,\n\ \ \"em_stderr\": 0.004174608410380015,\n \"f1\": 0.267364723154363,\n\ \ \"f1_stderr\": 0.004242093940617827\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.4735494880546075,\n \"acc_stderr\": 0.014590931358120174,\n\ \ \"acc_norm\": 0.5059726962457338,\n \"acc_norm_stderr\": 0.014610348300255795\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.47410874327823144,\n\ \ \"acc_stderr\": 0.004983087049281742,\n \"acc_norm\": 0.6389165504879506,\n\ \ \"acc_norm_stderr\": 0.00479333052565621\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952365,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952365\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.4342105263157895,\n \"acc_stderr\": 0.0403356566784832,\n\ \ \"acc_norm\": 0.4342105263157895,\n \"acc_norm_stderr\": 0.0403356566784832\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.41,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.41,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.39622641509433965,\n \"acc_stderr\": 0.030102793781791194,\n\ \ \"acc_norm\": 0.39622641509433965,\n \"acc_norm_stderr\": 0.030102793781791194\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.3819444444444444,\n\ \ \"acc_stderr\": 0.040629907841466674,\n \"acc_norm\": 0.3819444444444444,\n\ \ \"acc_norm_stderr\": 0.040629907841466674\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \"acc_norm\": 0.31,\n\ \ \"acc_norm_stderr\": 0.046482319871173156\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932269,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932269\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3468208092485549,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.3468208092485549,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.30392156862745096,\n \"acc_stderr\": 0.045766654032077636,\n\ \ \"acc_norm\": 0.30392156862745096,\n \"acc_norm_stderr\": 0.045766654032077636\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n\ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.02951319662553935,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.02951319662553935\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2807017543859649,\n\ \ \"acc_stderr\": 0.04227054451232199,\n \"acc_norm\": 0.2807017543859649,\n\ \ \"acc_norm_stderr\": 0.04227054451232199\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.38620689655172413,\n \"acc_stderr\": 0.04057324734419035,\n\ \ \"acc_norm\": 0.38620689655172413,\n \"acc_norm_stderr\": 0.04057324734419035\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948368,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948368\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.23015873015873015,\n\ \ \"acc_stderr\": 0.037649508797906066,\n \"acc_norm\": 0.23015873015873015,\n\ \ \"acc_norm_stderr\": 0.037649508797906066\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.4,\n\ \ \"acc_stderr\": 0.02786932057166463,\n \"acc_norm\": 0.4,\n \ \ \"acc_norm_stderr\": 0.02786932057166463\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.33497536945812806,\n \"acc_stderr\": 0.033208527423483104,\n\ \ \"acc_norm\": 0.33497536945812806,\n \"acc_norm_stderr\": 0.033208527423483104\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.5454545454545454,\n \"acc_stderr\": 0.038881769216741004,\n\ \ \"acc_norm\": 0.5454545454545454,\n \"acc_norm_stderr\": 0.038881769216741004\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.4292929292929293,\n \"acc_stderr\": 0.03526552724601198,\n \"\ acc_norm\": 0.4292929292929293,\n \"acc_norm_stderr\": 0.03526552724601198\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.5284974093264249,\n \"acc_stderr\": 0.03602573571288441,\n\ \ \"acc_norm\": 0.5284974093264249,\n \"acc_norm_stderr\": 0.03602573571288441\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.34102564102564104,\n \"acc_stderr\": 0.024035489676335065,\n\ \ \"acc_norm\": 0.34102564102564104,\n \"acc_norm_stderr\": 0.024035489676335065\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275794,\n \ \ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275794\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.3067226890756303,\n \"acc_stderr\": 0.02995382389188704,\n \ \ \"acc_norm\": 0.3067226890756303,\n \"acc_norm_stderr\": 0.02995382389188704\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.036030385453603826,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.036030385453603826\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5229357798165137,\n \"acc_stderr\": 0.0214147570581755,\n \"acc_norm\"\ : 0.5229357798165137,\n \"acc_norm_stderr\": 0.0214147570581755\n },\n\ \ \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\": 0.2916666666666667,\n\ \ \"acc_stderr\": 0.03099866630456052,\n \"acc_norm\": 0.2916666666666667,\n\ \ \"acc_norm_stderr\": 0.03099866630456052\n },\n \"harness\|hendrycksTest-high_school_us_history\|5\"\ : {\n \"acc\": 0.5490196078431373,\n \"acc_stderr\": 0.03492406104163613,\n\ \ \"acc_norm\": 0.5490196078431373,\n \"acc_norm_stderr\": 0.03492406104163613\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.6033755274261603,\n \"acc_stderr\": 0.03184399873811226,\n \ \ \"acc_norm\": 0.6033755274261603,\n \"acc_norm_stderr\": 0.03184399873811226\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.4304932735426009,\n\ \ \"acc_stderr\": 0.033231973029429394,\n \"acc_norm\": 0.4304932735426009,\n\ \ \"acc_norm_stderr\": 0.033231973029429394\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.45038167938931295,\n \"acc_stderr\": 0.04363643698524779,\n\ \ \"acc_norm\": 0.45038167938931295,\n \"acc_norm_stderr\": 0.04363643698524779\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.4049586776859504,\n \"acc_stderr\": 0.04481137755942469,\n \"\ acc_norm\": 0.4049586776859504,\n \"acc_norm_stderr\": 0.04481137755942469\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.4074074074074074,\n\ \ \"acc_stderr\": 0.04750077341199986,\n \"acc_norm\": 0.4074074074074074,\n\ \ \"acc_norm_stderr\": 0.04750077341199986\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.3803680981595092,\n \"acc_stderr\": 0.03814269893261837,\n\ \ \"acc_norm\": 0.3803680981595092,\n \"acc_norm_stderr\": 0.03814269893261837\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04109974682633932,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04109974682633932\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.36893203883495146,\n \"acc_stderr\": 0.047776151811567386,\n\ \ \"acc_norm\": 0.36893203883495146,\n \"acc_norm_stderr\": 0.047776151811567386\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.43162393162393164,\n\ \ \"acc_stderr\": 0.0324483553531149,\n \"acc_norm\": 0.43162393162393164,\n\ \ \"acc_norm_stderr\": 0.0324483553531149\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768079,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768079\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.40485312899106,\n\ \ \"acc_stderr\": 0.017553246467720256,\n \"acc_norm\": 0.40485312899106,\n\ \ \"acc_norm_stderr\": 0.017553246467720256\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.3959537572254335,\n \"acc_stderr\": 0.026329813341946243,\n\ \ \"acc_norm\": 0.3959537572254335,\n \"acc_norm_stderr\": 0.026329813341946243\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24134078212290502,\n\ \ \"acc_stderr\": 0.014310999547961464,\n \"acc_norm\": 0.24134078212290502,\n\ \ \"acc_norm_stderr\": 0.014310999547961464\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.3954248366013072,\n \"acc_stderr\": 0.027996723180631438,\n\ \ \"acc_norm\": 0.3954248366013072,\n \"acc_norm_stderr\": 0.027996723180631438\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.36012861736334406,\n\ \ \"acc_stderr\": 0.027264297599804015,\n \"acc_norm\": 0.36012861736334406,\n\ \ \"acc_norm_stderr\": 0.027264297599804015\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.42592592592592593,\n \"acc_stderr\": 0.027513747284379424,\n\ \ \"acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.027513747284379424\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.31560283687943264,\n \"acc_stderr\": 0.02772498944950931,\n \ \ \"acc_norm\": 0.31560283687943264,\n \"acc_norm_stderr\": 0.02772498944950931\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.29921773142112124,\n\ \ \"acc_stderr\": 0.01169537463069603,\n \"acc_norm\": 0.29921773142112124,\n\ \ \"acc_norm_stderr\": 0.01169537463069603\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.3897058823529412,\n \"acc_stderr\": 0.029624663581159696,\n\ \ \"acc_norm\": 0.3897058823529412,\n \"acc_norm_stderr\": 0.029624663581159696\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.3349673202614379,\n \"acc_stderr\": 0.019094228167000325,\n \ \ \"acc_norm\": 0.3349673202614379,\n \"acc_norm_stderr\": 0.019094228167000325\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.37272727272727274,\n\ \ \"acc_stderr\": 0.04631381319425463,\n \"acc_norm\": 0.37272727272727274,\n\ \ \"acc_norm_stderr\": 0.04631381319425463\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.4204081632653061,\n \"acc_stderr\": 0.03160106993449604,\n\ \ \"acc_norm\": 0.4204081632653061,\n \"acc_norm_stderr\": 0.03160106993449604\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.472636815920398,\n\ \ \"acc_stderr\": 0.035302355173346824,\n \"acc_norm\": 0.472636815920398,\n\ \ \"acc_norm_stderr\": 0.035302355173346824\n },\n \"harness\|hendrycksTest-us_foreign_policy\|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-virology\|5\": {\n \"acc\": 0.35542168674698793,\n\ \ \"acc_stderr\": 0.03726214354322415,\n \"acc_norm\": 0.35542168674698793,\n\ \ \"acc_norm_stderr\": 0.03726214354322415\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.32748538011695905,\n \"acc_stderr\": 0.035993357714560276,\n\ \ \"acc_norm\": 0.32748538011695905,\n \"acc_norm_stderr\": 0.035993357714560276\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.01586634640138431,\n \"mc2\": 0.45373679597767685,\n\ \ \"mc2_stderr\": 0.015753224924844992\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5422257300710339,\n \"acc_stderr\": 0.014002284504422435\n\ \ },\n \"harness\|drop\|3\": {\n \"em\": 0.21046560402684564,\n \ \ \"em_stderr\": 0.004174608410380015,\n \"f1\": 0.267364723154363,\n \ \ \"f1_stderr\": 0.004242093940617827\n },\n \"harness\|gsm8k\|5\": {\n\ \ \"acc\": 0.015163002274450341,\n \"acc_stderr\": 0.0033660229497263225\n\ \ }\n}\n```" repo_url: https://huggingface.co/NurtureAI/Orca-2-7B-16k 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_11_25T21_39_02.599324 path: - '/details_harness\|arc:challenge\|25_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-11-25T21-39-02.599324.parquet' - config_name: harness_drop_3 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|drop\|3_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-11-25T21-39-02.599324.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|gsm8k\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hellaswag\|10_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-11-25T21-39-02.599324.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-management\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-virology\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|truthfulqa:mc\|0_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-11-25T21-39-02.599324.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '/details_harness\|winogrande\|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-11-25T21-39-02.599324.parquet' - config_name: results data_files: - split: 2023_11_25T21_39_02.599324 path: - results_2023-11-25T21-39-02.599324.parquet - split: latest path: - results_2023-11-25T21-39-02.599324.parquet --- # Dataset Card for Evaluation run of NurtureAI/Orca-2-7B-16k ## Dataset Description - Homepage: - Repository: https://huggingface.co/NurtureAI/Orca-2-7B-16k - 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 [NurtureAI/Orca-2-7B-16k](https://huggingface.co/NurtureAI/Orca-2-7B-16k) 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 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_NurtureAI__Orca-2-7B-16k_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-25T21:39:02.599324](https://huggingface.co/datasets/open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k_public/blob/main/results_2023-11-25T21-39-02.599324.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": 0.36746546712957223, "acc_stderr": 0.033751277531008754, "acc_norm": 0.3738175555586316, "acc_norm_stderr": 0.03459812342976094, "mc1": 0.28886168910648713, "mc1_stderr": 0.01586634640138431, "mc2": 0.45373679597767685, "mc2_stderr": 0.015753224924844992, "em": 0.21046560402684564, "em_stderr": 0.004174608410380015, "f1": 0.267364723154363, "f1_stderr": 0.004242093940617827 }, "harness\|arc:challenge\|25": { "acc": 0.4735494880546075, "acc_stderr": 0.014590931358120174, "acc_norm": 0.5059726962457338, "acc_norm_stderr": 0.014610348300255795 }, "harness\|hellaswag\|10": { "acc": 0.47410874327823144, "acc_stderr": 0.004983087049281742, "acc_norm": 0.6389165504879506, "acc_norm_stderr": 0.00479333052565621 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.4342105263157895, "acc_stderr": 0.0403356566784832, "acc_norm": 0.4342105263157895, "acc_norm_stderr": 0.0403356566784832 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.39622641509433965, "acc_stderr": 0.030102793781791194, "acc_norm": 0.39622641509433965, "acc_norm_stderr": 0.030102793781791194 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.3819444444444444, "acc_stderr": 0.040629907841466674, "acc_norm": 0.3819444444444444, "acc_norm_stderr": 0.040629907841466674 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.22, "acc_stderr": 0.04163331998932269, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932269 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3468208092485549, "acc_stderr": 0.036291466701596636, "acc_norm": 0.3468208092485549, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.30392156862745096, "acc_stderr": 0.045766654032077636, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.045766654032077636 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.2851063829787234, "acc_stderr": 0.02951319662553935, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.02951319662553935 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2807017543859649, "acc_stderr": 0.04227054451232199, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.04227054451232199 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.38620689655172413, "acc_stderr": 0.04057324734419035, "acc_norm": 0.38620689655172413, "acc_norm_stderr": 0.04057324734419035 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948368, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948368 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.23015873015873015, "acc_stderr": 0.037649508797906066, "acc_norm": 0.23015873015873015, "acc_norm_stderr": 0.037649508797906066 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.4, "acc_stderr": 0.02786932057166463, "acc_norm": 0.4, "acc_norm_stderr": 0.02786932057166463 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.33497536945812806, "acc_stderr": 0.033208527423483104, "acc_norm": 0.33497536945812806, "acc_norm_stderr": 0.033208527423483104 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.5454545454545454, "acc_stderr": 0.038881769216741004, "acc_norm": 0.5454545454545454, "acc_norm_stderr": 0.038881769216741004 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.4292929292929293, "acc_stderr": 0.03526552724601198, "acc_norm": 0.4292929292929293, "acc_norm_stderr": 0.03526552724601198 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.5284974093264249, "acc_stderr": 0.03602573571288441, "acc_norm": 0.5284974093264249, "acc_norm_stderr": 0.03602573571288441 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.34102564102564104, "acc_stderr": 0.024035489676335065, "acc_norm": 0.34102564102564104, "acc_norm_stderr": 0.024035489676335065 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.24074074074074073, "acc_stderr": 0.026067159222275794, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.026067159222275794 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.3067226890756303, "acc_stderr": 0.02995382389188704, "acc_norm": 0.3067226890756303, "acc_norm_stderr": 0.02995382389188704 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.26490066225165565, "acc_stderr": 0.036030385453603826, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.036030385453603826 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5229357798165137, "acc_stderr": 0.0214147570581755, "acc_norm": 0.5229357798165137, "acc_norm_stderr": 0.0214147570581755 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.2916666666666667, "acc_stderr": 0.03099866630456052, "acc_norm": 0.2916666666666667, "acc_norm_stderr": 0.03099866630456052 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.5490196078431373, "acc_stderr": 0.03492406104163613, "acc_norm": 0.5490196078431373, "acc_norm_stderr": 0.03492406104163613 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.6033755274261603, "acc_stderr": 0.03184399873811226, "acc_norm": 0.6033755274261603, "acc_norm_stderr": 0.03184399873811226 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.4304932735426009, "acc_stderr": 0.033231973029429394, "acc_norm": 0.4304932735426009, "acc_norm_stderr": 0.033231973029429394 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.45038167938931295, "acc_stderr": 0.04363643698524779, "acc_norm": 0.45038167938931295, "acc_norm_stderr": 0.04363643698524779 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.4049586776859504, "acc_stderr": 0.04481137755942469, "acc_norm": 0.4049586776859504, "acc_norm_stderr": 0.04481137755942469 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.4074074074074074, "acc_stderr": 0.04750077341199986, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.04750077341199986 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.3803680981595092, "acc_stderr": 0.03814269893261837, "acc_norm": 0.3803680981595092, "acc_norm_stderr": 0.03814269893261837 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.25, "acc_stderr": 0.04109974682633932, "acc_norm": 0.25, "acc_norm_stderr": 0.04109974682633932 }, "harness\|hendrycksTest-management\|5": { "acc": 0.36893203883495146, "acc_stderr": 0.047776151811567386, "acc_norm": 0.36893203883495146, "acc_norm_stderr": 0.047776151811567386 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.43162393162393164, "acc_stderr": 0.0324483553531149, "acc_norm": 0.43162393162393164, "acc_norm_stderr": 0.0324483553531149 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.40485312899106, "acc_stderr": 0.017553246467720256, "acc_norm": 0.40485312899106, "acc_norm_stderr": 0.017553246467720256 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.3959537572254335, "acc_stderr": 0.026329813341946243, "acc_norm": 0.3959537572254335, "acc_norm_stderr": 0.026329813341946243 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.24134078212290502, "acc_stderr": 0.014310999547961464, "acc_norm": 0.24134078212290502, "acc_norm_stderr": 0.014310999547961464 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.3954248366013072, "acc_stderr": 0.027996723180631438, "acc_norm": 0.3954248366013072, "acc_norm_stderr": 0.027996723180631438 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.36012861736334406, "acc_stderr": 0.027264297599804015, "acc_norm": 0.36012861736334406, "acc_norm_stderr": 0.027264297599804015 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.42592592592592593, "acc_stderr": 0.027513747284379424, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.027513747284379424 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.31560283687943264, "acc_stderr": 0.02772498944950931, "acc_norm": 0.31560283687943264, "acc_norm_stderr": 0.02772498944950931 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.29921773142112124, "acc_stderr": 0.01169537463069603, "acc_norm": 0.29921773142112124, "acc_norm_stderr": 0.01169537463069603 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.3897058823529412, "acc_stderr": 0.029624663581159696, "acc_norm": 0.3897058823529412, "acc_norm_stderr": 0.029624663581159696 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.3349673202614379, "acc_stderr": 0.019094228167000325, "acc_norm": 0.3349673202614379, "acc_norm_stderr": 0.019094228167000325 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.37272727272727274, "acc_stderr": 0.04631381319425463, "acc_norm": 0.37272727272727274, "acc_norm_stderr": 0.04631381319425463 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.4204081632653061, "acc_stderr": 0.03160106993449604, "acc_norm": 0.4204081632653061, "acc_norm_stderr": 0.03160106993449604 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.472636815920398, "acc_stderr": 0.035302355173346824, "acc_norm": 0.472636815920398, "acc_norm_stderr": 0.035302355173346824 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.35542168674698793, "acc_stderr": 0.03726214354322415, "acc_norm": 0.35542168674698793, "acc_norm_stderr": 0.03726214354322415 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.32748538011695905, "acc_stderr": 0.035993357714560276, "acc_norm": 0.32748538011695905, "acc_norm_stderr": 0.035993357714560276 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.28886168910648713, "mc1_stderr": 0.01586634640138431, "mc2": 0.45373679597767685, "mc2_stderr": 0.015753224924844992 }, "harness\|winogrande\|5": { "acc": 0.5422257300710339, "acc_stderr": 0.014002284504422435 }, "harness\|drop\|3": { "em": 0.21046560402684564, "em_stderr": 0.004174608410380015, "f1": 0.267364723154363, "f1_stderr": 0.004242093940617827 }, "harness\|gsm8k\|5": { "acc": 0.015163002274450341, "acc_stderr": 0.0033660229497263225 } } ``` ### 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]
andstor/smart_contracts	--- annotations_creators: [] language_creators: [] language: - en multilinguality: - monolingual pretty_name: Smart Contracts size_categories: - 100K<n<1M source_datasets: - original task_categories: - text-generation task_ids: - language-modeling paperswithcode_id: verified-smart-contracts --- # Dataset Card for Smart Contracts ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [flattened](#flattened) - [flattened_plain_text](#flattened_plain_text) - [inflated](#inflated) - [inflated_plain_text](#inflated_plain_text) - [parsed](#parsed) - [Data Fields](#data-fields) - [flattened](#flattened-1) - [flattened_plain_text](#flattened_plain_text-1) - [inflated](#inflated-1) - [inflated_plain_text](#inflated_plain_text-1) - [parsed](#parsed-1) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://andstor.github.io/smart-contracts - Repository: https://github.com/andstor/verified-smart-contracts - Paper: - Leaderboard: - Point of Contact: [André Storhaug](mailto:andr3.storhaug@gmail.com) ### Dataset Summary This is a dataset of verified Smart Contracts from Etherscan.io that are deployed to the Ethereum blockchain. A set of about 100,000 to 200,000 contracts are provided, containing both Solidity and Vyper code. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances #### flattened ``` { 'contract_name': 'MiaKhalifaDAO', 'contract_address': '0xb3862ca215d5ed2de22734ed001d701adf0a30b4', 'language': 'Solidity', 'source_code': '// File: @openzeppelin/contracts/utils/Strings.sol\r\n\r\n\r\n// OpenZeppelin Contracts v4.4.1 (utils/Strings.sol)\r\n\r\npragma solidity ^0.8.0;\r\n\r\n/*\r\n @dev String operations.\r\n /\r\nlibrary Strings {\r\n...', 'abi': '[{"inputs":[{"internalType":"uint256","name":"maxBatchSize_","type":"uint256"}...]', 'compiler_version': 'v0.8.7+commit.e28d00a7', 'optimization_used': False, 'runs': 200, 'constructor_arguments': '000000000000000000000000000000000000000000000000000000000000000a000...', 'evm_version': 'Default', 'library': '', 'license_type': 'MIT', 'proxy': False, 'implementation': '', 'swarm_source': 'ipfs://e490df69bd9ca50e1831a1ac82177e826fee459b0b085a00bd7a727c80d74089' } ``` #### flattened_extended Same fields as `flattened` but with the following additional fields: ``` { ... 'tx_count': 1074, 'balance': 38 } ``` #### flattened_plain_text ``` { 'language': 'Solidity', 'text': '// File: SafeMath.sol\r\npragma solidity =0.5.16;\r\n\r\n// a library for performing overflow-safe math...' } ``` #### inflated ``` { 'contract_name': 'PinkLemonade', 'file_path': 'PinkLemonade.sol', 'contract_address': '0x9a5be3cc368f01a0566a613aad7183783cff7eec', 'language': 'Solidity', 'source_code': '/\r\n\r\nt.me/pinklemonadecoin\r\n/\r\n\r\n// SPDX-License-Identifier: MIT\r\npragma solidity ^0.8.0;\r\n\r\n\r\n/\r\n @dev Provides information about the current execution context, including the\r\n * sender of the transaction and its data. While these are generally available...', 'abi': '[{"inputs":[],"stateMutability":"nonpayable","type":"constructor"}...]', 'compiler_version': 'v0.8.4+commit.c7e474f2', 'optimization_used': False, 'runs': 200, 'constructor_arguments': '', 'evm_version': 'Default', 'library': '', 'license_type': 'MIT', 'proxy': False, 'implementation': '', 'swarm_source': 'ipfs://eb0ac9491a04e7a196280fd27ce355a85d79b34c7b0a83ab606d27972a06050c' } ``` #### inflated_plain_text ``` { 'language': 'Solidity', 'text': '\\npragma solidity ^0.4.11;\\n\\ncontract ERC721 {\\n // Required methods\\n function totalSupply() public view returns (uint256 total);...' } ``` #### parsed ``` { 'contract_name': 'BondedECDSAKeep', 'file_path': '@keep-network/keep-core/contracts/StakeDelegatable.sol', 'contract_address': '0x61935dc4ffc5c5f1d141ac060c0eef04a792d8ee', 'language': 'Solidity', 'class_name': 'StakeDelegatable', 'class_code': 'contract StakeDelegatable {\n using OperatorParams for uint256;\n\n mapping(address => Operator) internal operators;\n\n struct Operator {\n uint256 packedParams;\n address owner;\n address payable beneficiary;\n address authorizer;\n }\n\n...', 'class_documentation': '/// @title Stake Delegatable\n/// @notice A base contract to allow stake delegation for staking contracts.', 'class_documentation_type': 'NatSpecSingleLine', 'func_name': 'balanceOf', 'func_code': 'function balanceOf(address _address) public view returns (uint256 balance) {\n return operators[_address].packedParams.getAmount();\n }', 'func_documentation': '/// @notice Gets the stake balance of the specified address.\n/// @param _address The address to query the balance of.\n/// @return An uint256 representing the amount staked by the passed address.', 'func_documentation_type': 'NatSpecSingleLine', 'compiler_version': 'v0.5.17+commit.d19bba13', 'license_type': 'MIT', 'swarm_source': 'bzzr://63a152bdeccda501f3e5b77f97918c5500bb7ae07637beba7fae76dbe818bda4' } ``` ### Data Fields #### flattened - `contract_name` (`string`): containing the smart contract name. - `contract_address` (`string`): containing the Ethereum address for the smart contract. - `language` (`string`): containing the language of the smart contract. - `source_code ` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `abi` (`string`): containing the Application Binary Interface (ABI) of the smart contract. - `compiler_version` (`string`): containing the compiler version used to compile the smart contract. - `optimization_used` (`boolean`): indicating if the smart contract used optimization. - `runs` (`number`): containing the number of optimization steps used. - `constructor_arguments` (`string`): containing the constructor arguments of the smart contract. - `evm_version` (`string`): containing the EVM version used to compile the smart contract. - `library` (`string`): containing the `name:address` of libraries used separated by `;`. - `license_type` (`string`): containing the license type of the smart contract. - `proxy` (`boolean`): indicating if the smart contract is a proxy. - `implementation` (`string`): containing the implementation of the smart contract if it is a proxy. - `swarm_source` (`string`): containing the swarm source of the smart contract. #### flattened_extended Same fields as `flattened` but with the following additional fields: - `tx_count` (`number`): containing the number of transactions made to the smart contract. - `balance` (`string`): containing the ether balancce of the smart contract. #### flattened_plain_text - `text` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `language` (`string`): containing the language of the smart contract. #### inflated Same fields as `flattened` but with the following additional fields: - `file_path` (`string`): containing the original path to the file. #### inflated_plain_text - `text` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `language` (`string`): containing the language of the smart contract. #### parsed - `contract_name` (`string`): containing the smart contract name. - `file_path` (`string`): containing the original path to the file. - `contract_address` (`string`): containing the Ethereum address for the smart contract. - `language` (`string`): containing the language of the smart contract. - `class_name` (`string`): containing the name of the "class" (contract). - `class_code` (`string`): containing the source code of the "class" (contract). - `class_documentation` (`string`): containing the documentation (code comment) of the "class" (contract). - `class_documentation_type` (`string`): containing the documentation type of the "class" (contract). Can be one of: `NatSpecMultiLine`, `NatSpecSingleLine`, `LineComment` or `Comment`. - `func_name` (`string`): containing the name of the function definition. - `func_code` (`string`): containing the source code of the function. - `func_documentation` (`string`): containing the documentation (code comment) of the contract definition (or "class"). - `func_documentation_type` (`string`): containing the documentation type of the function. Can be one of: `NatSpecMultiLine`, `NatSpecSingleLine`, `LineComment` or `Comment`. - `compiler_version` (`string`): containing the compiler version used to compile the smart contract. - `license_type` (`string`): containing the license type of the smart contract. - `swarm_source` (`string`): containing the swarm source of the smart contract. ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information ```bibtex @misc{storhaug2023efficient, title={Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decoding}, author={André Storhaug and Jingyue Li and Tianyuan Hu}, year={2023}, eprint={2309.09826}, archivePrefix={arXiv}, primaryClass={cs.CR} } ``` ### Contributions Thanks to [@andstor](https://github.com/andstor) for adding this dataset.
leey4n/KR3	--- annotations_creators: [] language_creators: [] language: - ko license: - cc-by-nc-sa-4.0 multilinguality: - monolingual pretty_name: KR3 size_categories: - 100K<n<1m source_datasets: [] task_categories: - text-classification task_ids: - sentiment-classification --- ### KR3: Korean Restaurant Reviews with Ratings Korean sentiment classification dataset - Size: 460K(+180K) - Language: Korean-centric ### ⚠️ Caution with `Rating` Column 0 stands for negative review, 1 stands for positive review, and 2 stands for ambiguous review. Note that rating 2 is not intended to be used directly for supervised learning(classification). This data is included for additional pre-training purpose or other usage. In other words, this dataset is basically a binary sentiment classification task where labels are 0 and 1. ### 🔍 See More See all the codes for crawling/preprocessing the dataset and experiments with KR3 in [GitHub Repo](https://github.com/Wittgensteinian/kr3). See Kaggle dataset in [Kaggle Dataset](https://www.kaggle.com/ninetyninenewton/kr3-korean-restaurant-reviews-with-ratings). ### Usage ```python from datasets import load_dataset kr3 = load_dataset("leey4n/KR3", name='kr3', split='train') kr3 = kr3.remove_columns(['__index_level_0__']) # Original file didn't include this column. Suspect it's a hugging face issue. ``` ```python # drop reviews with ambiguous label kr3_binary = kr3.filter(lambda example: example['Rating'] != 2) ``` ### License CC BY-NC-SA 4.0 ### Legal Issues We concluded that the non-commerical usage and release of KR3 fall into the range of fair use (공정 이용) stated in the Korean copyright act (저작권법). We further clarify that we did not agree to the terms of service from any websites which might prohibit web crawling. In other words, web crawling we've done was proceeded without logging in to the website. Despite all of these, feel free to contact to any of the contributors if you notice any legal issues. ### Contributors & Acknowledgement (Alphabetical order) [Dongin Jung](https://github.com/dongin1009) [Hyunwoo Kwak](https://github.com/Kwak-Hyun-woo) [Kaeun Lee](https://github.com/Kaeun-Lee) [Yejoon Lee](https://github.com/wittgensteinian) This work was done as DIYA 4기. Compute resources needed for the work was supported by [DIYA](https://blog.diyaml.com) and surromind.ai.
pattern90/test4	--- dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 380878.0 num_examples: 6 download_size: 80720 dataset_size: 380878.0 --- # Dataset Card for "oct" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
NobodyExistsOnTheInternet/KTO-PRM	--- dataset_info: features: - name: prompt dtype: string - name: completion dtype: string - name: label dtype: bool splits: - name: train num_bytes: 379985094.2914787 num_examples: 473458 download_size: 70204316 dataset_size: 379985094.2914787 configs: - config_name: default data_files: - split: train path: data/train-* ---
ai4bharat/IndicCOPA	--- annotations_creators: - expert-generated language: - as - bn - en - gom - gu - hi - kn - mai - ml - mr - ne - or - pa - sa - sat - sd - ta - te - ur language_creators: - expert-generated license: - cc-by-4.0 multilinguality: - multilingual pretty_name: IndicXCOPA size_categories: - 1K<n<10K source_datasets: - extended\|xcopa tags: [] task_categories: - multiple-choice task_ids: - multiple-choice-qa --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
deven367/babylm-100M-children-stories	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 17676869 num_examples: 76758 - name: valid num_bytes: 1425137 num_examples: 5996 - name: test num_bytes: 1804421 num_examples: 7959 download_size: 12749002 dataset_size: 20906427 --- # Dataset Card for "babylm-100M-children-stories" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
pkufool/librilight-text	--- license: apache-2.0 ---
TheDKBR/thedkbr	--- license: openrail ---
ramixpe/sp_llama_simple	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: text dtype: string splits: - name: train num_bytes: 10031378 num_examples: 20551 download_size: 2324224 dataset_size: 10031378 configs: - config_name: default data_files: - split: train path: data/train-* ---
saurabhRaj11/MobiusBpmndataset	--- license: mit ---
KaleidoSG/Deepmind	--- license: other language: - en pretty_name: Deepmind size_categories: - 1M<n<10M configs: - config_name: default data_files: - split: train path: - train/OpenOrca/.csv - train/dolphin/.csv - train/flan_zsnoopt_data/.csv - train/t0_zsnoopt_data/.csv --- # Deepmind Dataset ## Overview The Deepmind dataset is a curated collection of high-quality datasets meticulously selected to suit a wide range of research and application needs. These datasets have been chosen for their relevance, diversity, and overall data quality. The Deepmind dataset is provided in the Stanford Alpaca format, ensuring consistency and ease of use across various projects and applications. # License The Deepmind dataset is made available under the Apache License 2.0, which allows for flexible usage, modification, and distribution while maintaining attribution to the original data sources. # Dataset Details Here's a snapshot of some of the top datasets included in the Deepmind collection: \| Dataset \| Files \| Size \| \|---------------\|-------\|---------\| \| Open_Orca \| 2 \| 6.9 GB \| \| Dolphin \| 2 \| 5.7 GB \| \| FLAN \| 78 \| 15.1 GB \| \| t0 \| 124 \| 25.9 GB \| \| Total \| 206 \| 53.6 GB \| The datasets in the Deepmind collection span a diverse array of domains and are carefully selected for their high quality. These datasets cater to various research and application needs, each offering unique insights and applications. # Citation ``` Deepmind Dataset. 2023 Deepmind Retrieved from huggingface.co/datasets/NewstaR/Deepmind Apache 2.0 License ```
Chaoticka/test	--- license: artistic-2.0 tags: - art pretty_name: Chaos Doll ---
huggingartists/ghostmane	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/ghostmane" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.027776 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://assets.genius.com/images/default_avatar_300.png?1631290285')"> </div> </div> <a href="https://huggingface.co/huggingartists/ghostmane"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Ghostmane</div> <a href="https://genius.com/artists/ghostmane"> <div style="text-align: center; font-size: 14px;">@ghostmane</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/ghostmane). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/ghostmane") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|2\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/ghostmane") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)
suwitlam/whisper-sun-system-dataset-sentence	--- license: cc0-1.0 ---
Tamnemtf/hcmue-qa-1	--- license: llama2 ---
jfloresf/burn-cems-1	--- license: cc-by-4.0 ---
FaalSa/dfaas3	--- dataset_info: features: - name: start dtype: timestamp[s] - name: target sequence: float32 - name: item_id dtype: string - name: feat_static_cat sequence: uint64 splits: - name: train num_bytes: 57633 num_examples: 1 - name: validation num_bytes: 58113 num_examples: 1 - name: test num_bytes: 58593 num_examples: 1 download_size: 35533 dataset_size: 174339 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
awacke1/eCQM-Code-Value-Semantic-Set.csv	--- license: mit --- eCQM-Code-Value-Semantic-Set.csv
GDGiangi/SEIRDB	--- language: - en - fr - it - el - es - ru pretty_name: SEIRDB size_categories: - 100K<n<1M task_categories: - audio-classification extra_gated_prompt: "To obtain an access token, the database licence must be purchased through https://gabegiangi.wordpress.com/2023/05/15/seir-db/" extra_gated_fields: Name: text Email: text Company: text Country: text Access Token: text I agree not to give access to any other entities: checkbox --- # Speech Emotion Intensity Recognition Database (SEIR-DB) ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: gabegiangi@gmail.com ### Dataset Summary The SEIR-DB is a comprehensive, multilingual speech emotion intensity recognition dataset containing over 600,000 instances from various sources. It is designed to support tasks related to speech emotion recognition and emotion intensity estimation. The database includes languages such as English, Russian, Mandarin, Greek, Italian, and French. ### Supported Tasks and Leaderboards The SEIR dataset is suitable for speech emotion recognition and speech emotion intensity estimation tasks (a subset of the dataset). ### Languages SEIR-DB encompasses multilingual data, featuring languages such as English, Russian, Mandarin, Greek, Italian, and French. ## Dataset Structure ### Data Instances The raw data collection comprises over 600,000 data instances (375 hours). Users of the database can access the raw audio data, which is stored in subdirectories of the data directory (in their respective datasets). After processing, cleaning, and formatting, the dataset contains approximately 120,000 training instances with an average audio utterance length of 3.8 seconds. ### Data Fields - ID: unique sample identifier - WAV: path to the audio file, located in the data directory - EMOTION: annotated emotion - INTENSITY: annotated intensity (ranging from 1-5), where 1 denotes low intensity, and 5 signifies high intensity; 0 indicates no annotation - LENGTH: duration of the audio utterance ### Data Splits The data is divided into train, test, and validation sets, located in the respective JSON manifest files. - Train: 80% - Validation: 10% - Test: 10% For added flexibility, unsplit data is also available in data.csv to allow custom splits. ## Dataset Creation ### Curation Rationale The SEIR-DB was curated to maximize the volume of data instances, addressing a significant limitation in speech emotion recognition (SER) experimentation—the lack of emotion data and the small size of available datasets. This database aims to resolve these issues by providing a large volume of emotion-annotated data that is cleanly formatted for experimentation. ### Source Data The dataset was compiled from various sources. ### Annotations #### Annotation process For details on the annotation process, please refer to the source for each dataset, as they were conducted differently. However, the entire database is human-annotated. #### Who are the annotators? Please consult the source documentation for information on the annotators. ### Personal and Sensitive Information No attempt was made to remove personal and sensitive information, as consent and recordings were not obtained internally. ## Considerations for Using the Data ### Social Impact of Dataset The SEIR-DB dataset can significantly impact the research and development of speech emotion recognition technologies by providing a large volume of annotated data. These technologies have the potential to enhance various applications, such as mental health monitoring, virtual assistants, customer support, and communication devices for people with disabilities. ### Discussion of Biases During the dataset cleaning process, efforts were made to balance the database concerning the number of samples for each dataset, emotion distribution (with a greater focus on primary emotions and less on secondary emotions), and language distribution. However, biases may still be present. ### Other Known Limitations No specific limitations have been identified at this time. ## Additional Information ### Dataset Curators Gabriel Giangi - Concordia University - Montreal, QC Canada - gabegiangi@gmail.com ### Licensing Information This dataset can be used for research and academic purposes. For commercial purposes, please contact gabegiangi@gmail.com . ### Citation Information Aljuhani, R. H., Alshutayri, A., & Alahdal, S. (2021). Arabic speech emotion recognition from Saudi dialect corpus. IEEE Access, 9, 127081-127085. Basu, S., Chakraborty, J., & Aftabuddin, M. (2017). Emotion recognition from speech using convolutional neural network with recurrent neural network architecture. In ICCES. Baevski, A., Zhou, H. H., & Collobert, R. (2020). Wav2vec 2.0: A framework for self-supervised learning of speech representations. In NeurIPS. Busso, C., Bulut, M., Lee, C. C., Kazemzadeh, A., Mower, E., Kim, S., ... & Narayanan, S. (2008). Iemocap: Interactive emotional dyadic motion capture database. In LREC. Cao, H., Cooper, D.G., Keutmann, M.K., Gur, R.C., Nenkova, A., & Verma, R. (2014). CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset. IEEE Transactions on Affective Computing, 5, 377-390. Chopra, S., Mathur, P., Sawhney, R., & Shah, R. R. (2021). Meta-Learning for Low-Resource Speech Emotion Recognition. In ICASSP. Costantini, G., Iaderola, I., Paoloni, A., & Todisco, M. (2014). EMOVO Corpus: an Italian Emotional Speech Database. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) (pp. 3501-3504). European Language Resources Association (ELRA). Reykjavik, Iceland. http://www.lrec-conf.org/proceedings/lrec2014/pdf/591_Paper.pdf Duville, Mathilde Marie; Alonso-Valerdi, Luz María; Ibarra-Zarate, David I. (2022), “Mexican Emotional Speech Database (MESD)”, Mendeley Data, V5, doi: 10.17632/cy34mh68j9.5 Gournay, Philippe, Lahaie, Olivier, & Lefebvre, Roch. (2018). A Canadian French Emotional Speech Dataset (1.1) [Data set]. ACM Multimedia Systems Conference (MMSys 2018) (MMSys'18), Amsterdam, The Netherlands. Zenodo. https://doi.org/10.5281/zenodo.1478765 Kandali, A., Routray, A., & Basu, T. (2008). Emotion recognition from Assamese speeches using MFCC features and GMM classifier. In TENCON. Kondratenko, V., Sokolov, A., Karpov, N., Kutuzov, O., Savushkin, N., & Minkin, F. (2022). Large Raw Emotional Dataset with Aggregation Mechanism. arXiv preprint arXiv:2212.12266. Kwon, S. (2021). MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach. Expert Systems with Applications, 167, 114177. Lee, Y., Lee, J. W., & Kim, S. (2019). Emotion recognition using convolutional neural network and multiple feature fusion. In ICASSP. Li, Y., Baidoo, C., Cai, T., & Kusi, G. A. (2019). Speech emotion recognition using 1d cnn with no attention. In ICSEC. Lian, Z., Tao, J., Liu, B., Huang, J., Yang, Z., & Li, R. (2020). Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition. In Interspeech. Livingstone, S. R., & Russo, F. A. (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. Peng, Z., Li, X., Zhu, Z., Unoki, M., Dang, J., & Akagi, M. (2020). Speech emotion recognition using 3d convolutions and attention-based sliding recurrent networks with auditory front-ends. IEEE Access, 8, 16560-16572. Poria, S., Hazarika, D., Majumder, N., Naik, G., Cambria, E., & Mihalcea, R. (2019). Meld: A multimodal multi-party dataset for emotion recognition in conversations. In ACL. Schneider, A., Baevski, A., & Collobert, R. (2019). Wav2vec: Unsupervised pre-training for speech recognition. In ICLR. Schuller, B., Rigoll, G., & Lang, M. (2010). Speech emotion recognition: Features and classification models. In Interspeech. Sinnott, R. O., Radulescu, A., & Kousidis, S. (2013). Surrey audiovisual expressed emotion (savee) database. In AVEC. Vryzas, N., Kotsakis, R., Liatsou, A., Dimoulas, C. A., & Kalliris, G. (2018). Speech emotion recognition for performance interaction. Journal of the Audio Engineering Society, 66(6), 457-467. Vryzas, N., Matsiola, M., Kotsakis, R., Dimoulas, C., & Kalliris, G. (2018, September). Subjective Evaluation of a Speech Emotion Recognition Interaction Framework. In Proceedings of the Audio Mostly 2018 on Sound in Immersion and Emotion (p. 34). ACM. Wang, Y., Yang, Y., Liu, Y., Chen, Y., Han, N., & Zhou, J. (2019). Speech emotion recognition using a combination of cnn and rnn. In Interspeech. Yoon, S., Byun, S., & Jung, K. (2018). Multimodal speech emotion recognition using audio and text. In SLT. Zhang, R., & Liu, M. (2020). Speech emotion recognition with self-attention. In ACL. ### Contributions Gabriel Giangi - Concordia University - Montreal, QC Canada - gabegiangi@gmail.com
acloudfan/hindi-to-english-translate	--- license: apache-2.0 ---
mask-distilled-onesec-cv12-each-chunk-uniq/chunk_265	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 948318804.0 num_examples: 186237 download_size: 967011151 dataset_size: 948318804.0 --- # Dataset Card for "chunk_265" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
deokhk/en_wiki_sentences_1000000	--- dataset_info: features: - name: sentence dtype: string splits: - name: train num_bytes: 124980032 num_examples: 1000000 - name: dev num_bytes: 123586 num_examples: 1000 download_size: 77463265 dataset_size: 125103618 --- # Dataset Card for "en_wiki_sentences_1000000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
TurkuNLP/genre-6	--- task_categories: - text-classification language: - en size_categories: - 10K<n<100K --- # Dataset Card for Dataset Name ## Dataset Summary Genre-6 dataset is an English dataset based on Kindletrends (UK & US). It contains more than 20k books and associated categories with ready-made binary classification and multilabel classification labels. ## Dataset Structure ### Data Instances `` {"text": "...", "categories": "Engineering & Transportation;Science & Math", "fiction": "non-fiction", "split1": ['Science & Math'], "split2" : ['Engineering & Transportation', 'Science & Math'], "split3": ['Science & Math']} `` ### Data Fields - text: Kindletrends text - categories: Kidletrends categories (1 to 2 categories per book) - fiction: binary label for fiction and non-fiction books - splits 1,2,3: multilabel for different subsets of the categories ### Data Splits The dataset contains train (80%), validation (10%) and test (10%) splits. The splits for multilabels are following: - split1: 'Biology & Nature & Biological Sciences','Computer Science', 'Fantasy','Medicine & Health Sciences','Philosophy','Science & Math'. - split2: 'Biology & Nature & Biological Sciences','Computer Science', 'Engineering & Transportation','Fantasy','Medicine & Health Sciences','Science & Math'. - split3: 'Biology & Nature & Biological Sciences','Computer Science', 'Fantasy','Medicine & Health Sciences', 'Poetry', 'Politics & Social Sciences', 'Science & Math'. More splits can be generated from the field "categories". ### Source Data [Kindletrends](https://kindletrends.com/categories/)
ebylmz/architects	--- license: mit ---
LLMao/2024_03_10_03_32_56_Archive	--- dataset_info: features: - name: page_content dtype: string - name: metadata struct: - name: source dtype: string - name: page dtype: int64 splits: - name: train num_bytes: 2578897 num_examples: 7 download_size: 1430198 dataset_size: 2578897 configs: - config_name: default data_files: - split: train path: data/train-* ---
hongboyang/CMRC2018_instruction1	--- dataset_info: features: - name: INPUT dtype: string - name: TARGET dtype: string splits: - name: train num_bytes: 17133521 num_examples: 10142 download_size: 4142597 dataset_size: 17133521 --- # Dataset Card for "CMRC2018_instruction1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ghbacct/financial-phrasebank-all-agree-clustering	--- dataset_info: features: - name: sentences sequence: string - name: labels sequence: int64 splits: - name: test num_bytes: 303379 num_examples: 1 download_size: 166862 dataset_size: 303379 --- # Dataset Card for "financial-phrasebank-all-agree-clustering" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Danieldlima21/mcmelody	--- license: openrail ---
zolak/twitter_dataset_81_1713085248	--- 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: 2664104 num_examples: 6535 download_size: 1316393 dataset_size: 2664104 configs: - config_name: default data_files: - split: train path: data/train-* ---
serhii-korobchenko/github-issues-embeddings	--- dataset_info: features: - name: html_url dtype: string - name: comments dtype: string - name: title dtype: string - name: body dtype: string - name: comment_length dtype: int64 - name: text dtype: string - name: embeddings sequence: float32 splits: - name: train num_bytes: 44924892 num_examples: 5034 download_size: 23623074 dataset_size: 44924892 configs: - config_name: default data_files: - split: train path: data/train-* ---
HamdanXI/paradetox-split	--- dataset_info: features: - name: en_toxic_comment dtype: string - name: en_neutral_comment dtype: string splits: - name: train num_bytes: 2082140.019398298 num_examples: 19073 - name: test num_bytes: 78390 num_examples: 671 download_size: 1237763 dataset_size: 2160530.019398298 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
eduzon/joaopauloo	--- license: openrail ---
Sachin7/story_dataset	--- dataset_info: features: - name: text dtype: string - name: 'Unnamed: 1' dtype: float64 splits: - name: train num_bytes: 143265.9775280899 num_examples: 62 - name: test num_bytes: 62390.02247191011 num_examples: 27 download_size: 145722 dataset_size: 205656.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
qnguyen3/alapaca-vi	--- license: mit ---
long292/PADNCH_5	--- dataset_info: features: - name: Phiên âm dtype: string - name: Dịch nghĩa dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1579554 num_examples: 7406 download_size: 925406 dataset_size: 1579554 configs: - config_name: default data_files: - split: train path: data/train-* ---
InceptiveDev/job_title	--- license: mit ---
LEAP/ClimSim_low-res	--- license: cc-by-4.0 --- Corresponding GitHub repo can be found here: https://github.com/leap-stc/ClimSim Read more: https://arxiv.org/abs/2306.08754.
soddokayo/crime2	--- dataset_info: features: - name: sentence dtype: string - name: tokens sequence: string - name: ner_tags sequence: int64 splits: - name: train num_bytes: 38639.2131147541 num_examples: 54 - name: test num_bytes: 5008.786885245901 num_examples: 7 download_size: 17337 dataset_size: 43648.0 --- # Dataset Card for "crime2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/gr_sl8_girlsfrontline	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of gr_sl8/GrSL8/SL8 (Girls' Frontline) This is the dataset of gr_sl8/GrSL8/SL8 (Girls' Frontline), containing 26 images and their tags. The core tags of this character are `breasts, purple_eyes, grey_hair, short_hair, medium_breasts, white_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 \| 26 \| 26.41 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 26 \| 17.87 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 58 \| 32.81 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 26 \| 24.86 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 58 \| 41.64 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_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/gr_sl8_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 \| 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, smile, cleavage, looking_at_viewer, jacket, navel, simple_background, teeth, white_background, holding \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| solo \| smile \| cleavage \| looking_at_viewer \| jacket \| navel \| simple_background \| teeth \| white_background \| holding \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:--------\|:-----------\|:--------------------\|:---------\|:--------\|:--------------------\|:--------\|:-------------------\|:----------\| \| 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 \|
mismatch-quest/SeeTRUE-Feedback	--- configs: - config_name: default data_files: - split: test path: "test/" annotations_creators: - crowdsourced language: - en language_creators: - found license: - cc-by-4.0 multilinguality: - monolingual paperswithcode_id: seetrue-feedback pretty_name: SeeTRUE-feedback size_categories: - 1K<n<10K source_datasets: - original tags: - text-image-matching task_ids: [] extra_gated_prompt: "By clicking on “Access repository” below, you also agree that you are using it solely for research purposes, and that SeeTRUE-Feedback should be used as a TEST SET*, not as a training set, and especially not to train commercial chatbots. Do not hessitate to contact briangordon@mail.tau.ac.il or yonatanbitton@google.com if you have questions about this license." --- # Dataset Card for SeeTRUE-Feedback - [Dataset Description](#dataset-description) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description The SeeTRUE-Feedback dataset is a diverse benchmark for the meta-evaluation of image-text matching/alignment feedback. It aims to overcome limitations in current benchmarks, which primarily focus on predicting a matching score between 0-1. SeeTRUE provides, for each row, the original caption, feedback related to text-image misalignment, and the caption+visual source of misalignments (including a bounding box for the visual misalignment). ### Languages The dataset supports English language. ## Dataset Structure ### Data Fields - image_caption - Caption associated with the image. - image_name: The name of the image file. - dataset_source: The source/origin dataset of the image. - id_in_source_dataset: The ID of the dataset where the row originates from. - image_url: An S3 link from which you can download the image. - human_feedback: Human-annotated feedbacks about image-text misalignment. - feedback: Summary of feedback consolidated into a single entry (Generated by LLM: PaLM-2) - feedback_clean: A parsed and "clean" version of `feedback` field. - caption_misalignment: Source of misalignment in the image caption. - visual_misalignment: Source of misalignment in the image. - bbox_GroundingDino: Detected visual misalignment bounding-box in GroundingDino output format. - bbox_PaLI: Detected visual misalignment bounding-box in PaLI output format. ### Data Splits SeeTRUE-Feedback contains a single split: TEST, and should not be used for training. ## Dataset Creation The dataset has been created by sourcing and matching images and text from multiple datasets. More information in the paper: <TODO> ### Licensing Information The dataset is under the CC-By 4.0 license. ### Citation Information TODO
HydraIndicLM/tamil_alpaca_dolly_51K	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: text dtype: string - name: system_prompt dtype: string splits: - name: train num_bytes: 287556653 num_examples: 51876 download_size: 84685617 dataset_size: 287556653 configs: - config_name: default data_files: - split: train path: data/train-* --- ## About This repo contains a 51K instruction set for Tamil, translated from Alpaca and Dolly. ## Citation If you find this repository useful, please consider giving 👏 and citing: ``` @misc{TamilAlpacaDolly, author = {Sambit Sekhar and Shantipriya Parida}, title = {Tamil Instruction Set Based on Alpaca and Dolly}, year = {2023}, publisher = {Hugging Face}, journal = {Hugging Face repository}, howpublished = {\url{https://huggingface.co/OdiaGenAI}}, } ```
open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml	--- pretty_name: Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v4-chatml dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [l3utterfly/mistral-7b-v0.1-layla-v4-chatml](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml)\ \ 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_l3utterfly__mistral-7b-v0.1-layla-v4-chatml\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-15T09:05:25.657589](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml/blob/main/results_2024-03-15T09-05-25.657589.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\": 0.637291875109227,\n\ \ \"acc_stderr\": 0.03233301893409507,\n \"acc_norm\": 0.6404117572756901,\n\ \ \"acc_norm_stderr\": 0.03298081985107007,\n \"mc1\": 0.2839657282741738,\n\ \ \"mc1_stderr\": 0.015785370858396725,\n \"mc2\": 0.4302819836285525,\n\ \ \"mc2_stderr\": 0.01426088687933726\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5827645051194539,\n \"acc_stderr\": 0.014409825518403079,\n\ \ \"acc_norm\": 0.6203071672354948,\n \"acc_norm_stderr\": 0.014182119866974872\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.630551682931687,\n\ \ \"acc_stderr\": 0.004816690123209757,\n \"acc_norm\": 0.8339972117108145,\n\ \ \"acc_norm_stderr\": 0.003713227064225392\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.046482319871173156\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6074074074074074,\n\ \ \"acc_stderr\": 0.0421850621536888,\n \"acc_norm\": 0.6074074074074074,\n\ \ \"acc_norm_stderr\": 0.0421850621536888\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.04923659639173309,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.04923659639173309\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\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.05021167315686779,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.05021167315686779\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|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_mathematics\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383887,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383887\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.042295258468165065,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.042295258468165065\n },\n \"harness\|hendrycksTest-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\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482758,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482758\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.3941798941798942,\n \"acc_stderr\": 0.025167982333894143,\n \"\ acc_norm\": 0.3941798941798942,\n \"acc_norm_stderr\": 0.025167982333894143\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7677419354838709,\n\ \ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\ \ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5024630541871922,\n \"acc_stderr\": 0.035179450386910616,\n\ \ \"acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.035179450386910616\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.02886977846026705,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.02886977846026705\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.02381447708659355,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.02381447708659355\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6358974358974359,\n \"acc_stderr\": 0.024396672985094764,\n\ \ \"acc_norm\": 0.6358974358974359,\n \"acc_norm_stderr\": 0.024396672985094764\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.362962962962963,\n \"acc_stderr\": 0.029318203645206865,\n \ \ \"acc_norm\": 0.362962962962963,\n \"acc_norm_stderr\": 0.029318203645206865\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \ \ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8238532110091743,\n \"acc_stderr\": 0.01633288239343138,\n \"\ acc_norm\": 0.8238532110091743,\n \"acc_norm_stderr\": 0.01633288239343138\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.803921568627451,\n \"acc_stderr\": 0.027865942286639318,\n \"\ acc_norm\": 0.803921568627451,\n \"acc_norm_stderr\": 0.027865942286639318\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7679324894514767,\n \"acc_stderr\": 0.027479744550808503,\n \ \ \"acc_norm\": 0.7679324894514767,\n \"acc_norm_stderr\": 0.027479744550808503\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159464,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159464\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8181818181818182,\n \"acc_stderr\": 0.03520893951097652,\n \"\ acc_norm\": 0.8181818181818182,\n \"acc_norm_stderr\": 0.03520893951097652\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243838,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243838\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7914110429447853,\n \"acc_stderr\": 0.031921934489347235,\n\ \ \"acc_norm\": 0.7914110429447853,\n \"acc_norm_stderr\": 0.031921934489347235\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\": 0.7961165048543689,\n \"acc_stderr\": 0.039891398595317706,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.039891398595317706\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8632478632478633,\n\ \ \"acc_stderr\": 0.022509033937077805,\n \"acc_norm\": 0.8632478632478633,\n\ \ \"acc_norm_stderr\": 0.022509033937077805\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.80970625798212,\n\ \ \"acc_stderr\": 0.014036945850381396,\n \"acc_norm\": 0.80970625798212,\n\ \ \"acc_norm_stderr\": 0.014036945850381396\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.684971098265896,\n \"acc_stderr\": 0.025009313790069713,\n\ \ \"acc_norm\": 0.684971098265896,\n \"acc_norm_stderr\": 0.025009313790069713\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.33854748603351953,\n\ \ \"acc_stderr\": 0.01582670009648135,\n \"acc_norm\": 0.33854748603351953,\n\ \ \"acc_norm_stderr\": 0.01582670009648135\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7483660130718954,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.7483660130718954,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7106109324758842,\n\ \ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\ \ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7283950617283951,\n \"acc_stderr\": 0.02474862449053737,\n\ \ \"acc_norm\": 0.7283950617283951,\n \"acc_norm_stderr\": 0.02474862449053737\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \ \ \"acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4654498044328553,\n\ \ \"acc_stderr\": 0.012739711554045706,\n \"acc_norm\": 0.4654498044328553,\n\ \ \"acc_norm_stderr\": 0.012739711554045706\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.02841820861940676,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.02841820861940676\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6748366013071896,\n \"acc_stderr\": 0.018950886770806308,\n \ \ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.018950886770806308\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\": 0.7346938775510204,\n \"acc_stderr\": 0.0282638899437846,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.0282638899437846\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\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5481927710843374,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.5481927710843374,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2839657282741738,\n\ \ \"mc1_stderr\": 0.015785370858396725,\n \"mc2\": 0.4302819836285525,\n\ \ \"mc2_stderr\": 0.01426088687933726\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7932123125493291,\n \"acc_stderr\": 0.011382566829235802\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.5382865807429871,\n \ \ \"acc_stderr\": 0.013732048227016682\n }\n}\n```" repo_url: https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|arc:challenge\|25_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-15T09-05-25.657589.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|gsm8k\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hellaswag\|10_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-15T09-05-25.657589.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-15T09-05-25.657589.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '/details_harness\|winogrande\|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-15T09-05-25.657589.parquet' - config_name: results data_files: - split: 2024_03_15T09_05_25.657589 path: - results_2024-03-15T09-05-25.657589.parquet - split: latest path: - results_2024-03-15T09-05-25.657589.parquet --- # Dataset Card for Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v4-chatml <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [l3utterfly/mistral-7b-v0.1-layla-v4-chatml](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml) 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_l3utterfly__mistral-7b-v0.1-layla-v4-chatml", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-15T09:05:25.657589](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml/blob/main/results_2024-03-15T09-05-25.657589.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": 0.637291875109227, "acc_stderr": 0.03233301893409507, "acc_norm": 0.6404117572756901, "acc_norm_stderr": 0.03298081985107007, "mc1": 0.2839657282741738, "mc1_stderr": 0.015785370858396725, "mc2": 0.4302819836285525, "mc2_stderr": 0.01426088687933726 }, "harness\|arc:challenge\|25": { "acc": 0.5827645051194539, "acc_stderr": 0.014409825518403079, "acc_norm": 0.6203071672354948, "acc_norm_stderr": 0.014182119866974872 }, "harness\|hellaswag\|10": { "acc": 0.630551682931687, "acc_stderr": 0.004816690123209757, "acc_norm": 0.8339972117108145, "acc_norm_stderr": 0.003713227064225392 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6074074074074074, "acc_stderr": 0.0421850621536888, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.0421850621536888 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "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": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383887, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383887 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.77, "acc_stderr": 0.042295258468165065, "acc_norm": 0.77, "acc_norm_stderr": 0.042295258468165065 }, "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": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482758, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482758 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.3941798941798942, "acc_stderr": 0.025167982333894143, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.025167982333894143 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7677419354838709, "acc_stderr": 0.024022256130308235, "acc_norm": 0.7677419354838709, "acc_norm_stderr": 0.024022256130308235 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5024630541871922, "acc_stderr": 0.035179450386910616, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.035179450386910616 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7929292929292929, "acc_stderr": 0.02886977846026705, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.02886977846026705 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8756476683937824, "acc_stderr": 0.02381447708659355, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.02381447708659355 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6358974358974359, "acc_stderr": 0.024396672985094764, "acc_norm": 0.6358974358974359, "acc_norm_stderr": 0.024396672985094764 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.362962962962963, "acc_stderr": 0.029318203645206865, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.029318203645206865 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6722689075630253, "acc_stderr": 0.03048991141767323, "acc_norm": 0.6722689075630253, "acc_norm_stderr": 0.03048991141767323 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8238532110091743, "acc_stderr": 0.01633288239343138, "acc_norm": 0.8238532110091743, "acc_norm_stderr": 0.01633288239343138 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.803921568627451, "acc_stderr": 0.027865942286639318, "acc_norm": 0.803921568627451, "acc_norm_stderr": 0.027865942286639318 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7679324894514767, "acc_stderr": 0.027479744550808503, "acc_norm": 0.7679324894514767, "acc_norm_stderr": 0.027479744550808503 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159464, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159464 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8181818181818182, "acc_stderr": 0.03520893951097652, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.03520893951097652 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243838, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243838 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7914110429447853, "acc_stderr": 0.031921934489347235, "acc_norm": 0.7914110429447853, "acc_norm_stderr": 0.031921934489347235 }, "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": 0.7961165048543689, "acc_stderr": 0.039891398595317706, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.039891398595317706 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8632478632478633, "acc_stderr": 0.022509033937077805, "acc_norm": 0.8632478632478633, "acc_norm_stderr": 0.022509033937077805 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.80970625798212, "acc_stderr": 0.014036945850381396, "acc_norm": 0.80970625798212, "acc_norm_stderr": 0.014036945850381396 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.684971098265896, "acc_stderr": 0.025009313790069713, "acc_norm": 0.684971098265896, "acc_norm_stderr": 0.025009313790069713 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.33854748603351953, "acc_stderr": 0.01582670009648135, "acc_norm": 0.33854748603351953, "acc_norm_stderr": 0.01582670009648135 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7483660130718954, "acc_stderr": 0.024848018263875195, "acc_norm": 0.7483660130718954, "acc_norm_stderr": 0.024848018263875195 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7106109324758842, "acc_stderr": 0.025755865922632945, "acc_norm": 0.7106109324758842, "acc_norm_stderr": 0.025755865922632945 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7283950617283951, "acc_stderr": 0.02474862449053737, "acc_norm": 0.7283950617283951, "acc_norm_stderr": 0.02474862449053737 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4787234042553192, "acc_stderr": 0.029800481645628693, "acc_norm": 0.4787234042553192, "acc_norm_stderr": 0.029800481645628693 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4654498044328553, "acc_stderr": 0.012739711554045706, "acc_norm": 0.4654498044328553, "acc_norm_stderr": 0.012739711554045706 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.02841820861940676, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.02841820861940676 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6748366013071896, "acc_stderr": 0.018950886770806308, "acc_norm": 0.6748366013071896, "acc_norm_stderr": 0.018950886770806308 }, "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": 0.7346938775510204, "acc_stderr": 0.0282638899437846, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.0282638899437846 }, "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": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5481927710843374, "acc_stderr": 0.03874371556587953, "acc_norm": 0.5481927710843374, "acc_norm_stderr": 0.03874371556587953 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2839657282741738, "mc1_stderr": 0.015785370858396725, "mc2": 0.4302819836285525, "mc2_stderr": 0.01426088687933726 }, "harness\|winogrande\|5": { "acc": 0.7932123125493291, "acc_stderr": 0.011382566829235802 }, "harness\|gsm8k\|5": { "acc": 0.5382865807429871, "acc_stderr": 0.013732048227016682 } } ``` ## 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]
gglab-ku/cogeval-human-SNLI-lalor	--- license: apache-2.0 ---
liuyanchen1015/MULTI_VALUE_mrpc_drop_aux_be_gonna	--- 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: 774 num_examples: 4 - name: train num_bytes: 3388 num_examples: 14 - name: validation num_bytes: 1008 num_examples: 4 download_size: 13603 dataset_size: 5170 --- # Dataset Card for "MULTI_VALUE_mrpc_drop_aux_be_gonna" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
bloyal/deeploc	--- license: cc-by-4.0 --- # DeepLoc-2.0 Training Data Dataset from https://services.healthtech.dtu.dk/services/DeepLoc-2.0/ used to train the DeepLoc-2.0 model. ## Data preparation Data downloaded and processed using the following Python script: ```python import pandas as pd df = pd.read_csv('https://services.healthtech.dtu.dk/services/DeepLoc-2.0/data/Swissprot_Train_Validation_dataset.csv').drop(['Unnamed: 0', 'Partition'], axis=1) df['labels'] = df[['Cell membrane', 'Cytoplasm','Endoplasmic reticulum', 'Extracellular', 'Golgi apparatus', 'Lysosome/Vacuole', 'Mitochondrion', 'Nucleus', 'Peroxisome', 'Plastid']].astype('float32').values.tolist() df['Membrane'] = df['Membrane'].astype('float32') df = df[['Kingdom', 'ACC', 'Sequence','Membrane','labels']] train = df.sample(frac=0.8) df = df.drop(train.index) val = df.sample(frac=0.5) test = df.drop(val.index) train = train.reset_index(drop=True) val = val.reset_index(drop=True) test = test.reset_index(drop=True) train.to_parquet('deeploc-train.parquet', index=False) val.to_parquet('deploc-val.parquet', index=False) test.to_parquet('deeploc-test.parquet', index=False) ``` ## Labels {'Cell membrane': 0, 'Cytoplasm': 1, 'Endoplasmic reticulum': 2, 'Extracellular': 3, 'Golgi apparatus': 4, 'Lysosome/Vacuole': 5, 'Mitochondrion': 6, 'Nucleus': 7, 'Peroxisome': 8, 'Plastid': 9} ## Citation DeepLoc-2.0: ``` Vineet Thumuluri and others, DeepLoc 2.0: multi-label subcellular localization prediction using protein language models, Nucleic Acids Research, Volume 50, Issue W1, 5 July 2022, Pages W228–W234, https://doi.org/10.1093/nar/gkac278 ``` The DeepLoc data is a derivative of the UniProt dataset: UniProt ``` The UniProt Consortium UniProt: the Universal Protein Knowledgebase in 2023 Nucleic Acids Res. 51:D523–D531 (2023) ```
Cognitive-Lab/Indic-MMLU	--- configs: - config_name: kn data_files: - split: test path: kn/test.json - split: validation path: kn/validation.json - split: dev path: kn/dev.json - config_name: hi data_files: - split: test path: hi/test.json - split: validation path: hi/validation.json - split: dev path: hi/dev.json - config_name: ta data_files: - split: test path: ta/test.json - split: validation path: ta/validation.json - split: dev path: ta/dev.json - config_name: te data_files: - split: test path: te/test.json - split: validation path: te/validation.json - split: dev path: te/dev.json - config_name: ml data_files: - split: test path: ml/test.json - split: validation path: ml/validation.json - split: dev path: ml/dev.json - config_name: gu data_files: - split: test path: gu/test.json - split: validation path: gu/validation.json - split: dev path: gu/dev.json - config_name: mr data_files: - split: test path: mr/test.json - split: validation path: mr/validation.json - split: dev path: mr/dev.json --- # MMLU Translated Citations: ``` @article{hendryckstest2021, title={Measuring Massive Multitask Language Understanding}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } @article{hendrycks2021ethics, title={Aligning AI With Shared Human Values}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } ``` Contributions:\ Thanks to [@Srinidhi9113](https://huggingface.co/Srinidhi9113) for adding the dataset.
TVRRaviteja/Mental-Health-Data	--- language: - en --- # Mental Health Queries and Personality Dataset ## Overview This dataset encompasses a collection of mental health queries paired with personality scores and responses generated by a Large Language Model (LLM). It aims to provide insights into the interplay between personality traits and mental health inquiries, facilitating research in personalized conversational agents and mental health support systems. ## Dataset Description Each record in the dataset contains: - A query from a Mental Health user. - A personality score across five types: Agreeableness, Extraversion, Openness, Conscientiousness, and Neuroticism. - A context interpretation based on the user's personality. - A tailored response from the Assistant. ## Potential Uses The dataset is particularly useful for researchers and developers working on: - Personalized conversational AI in mental health. - The impact of personality traits on mental health support. - Enhancing natural language understanding and response generation in the context of mental health. ## Access and Use This dataset is hosted on Hugging Face Datasets, available for academic and research purposes. Users are encouraged to cite the dataset when used in their research or projects. --- license: mit ---
TalTechNLP/dialogsum_ee	--- license: cc-by-4.0 dataset_info: features: - name: id dtype: string - name: dialogue dtype: string - name: summary dtype: string - name: topic dtype: string - name: en_dialogue dtype: string - name: en_summary dtype: string splits: - name: train num_bytes: 22666234 num_examples: 12460 - name: validation num_bytes: 881912 num_examples: 500 - name: test num_bytes: 2703111 num_examples: 1500 download_size: 14384437 dataset_size: 26251257 ---
subAxiom/central-bank-digital-currencies	--- license: cc task_categories: - text-generation language: - en tags: - finance pretty_name: Central Bank Digital Currencies size_categories: - n<1K --- # Dataset Card for Dataset Name ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [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]
chiragtubakad/flan-test-final	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: test num_bytes: 1196001.0504610357 num_examples: 1000 download_size: 552002 dataset_size: 1196001.0504610357 --- # Dataset Card for "flan-test-final" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
zhangshuoming/c_x86_exebench_json_cleaned	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 749238025.3045925 num_examples: 701744 download_size: 209658460 dataset_size: 749238025.3045925 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "c_x86_exebench_json_cleaned" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
pankajmathur/alpaca_orca	--- license: cc-by-nc-sa-4.0 task_categories: - text-generation language: - en size_categories: - 10K<n<100K --- Explain tuned Alpaca dataset ~52K created using approaches from Orca Research Paper. We leverage all of the 15 system instructions provided in Orca Research Paper. to generate custom datasets, in contrast to vanilla instruction tuning approaches used by original datasets. This helps student models like [orca_mini_13b](https://huggingface.co/psmathur/orca_mini_13b) to learn thought process from teacher model, which is ChatGPT (gpt-3.5-turbo-0301 version). Please see how the System prompt is added before each instruction.
thercyl/NVDA	--- dataset_info: features: - name: 'Unnamed: 0' dtype: float64 - name: Ticker dtype: string - name: Year dtype: string - name: Text dtype: string - name: Embedding dtype: string splits: - name: train num_bytes: 68921754 num_examples: 1979 download_size: 40675215 dataset_size: 68921754 --- # Dataset Card for "NVDA" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
joey234/mmlu-computer_security-neg-answer	--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: neg_answer dtype: string splits: - name: test num_bytes: 31239 num_examples: 100 download_size: 22397 dataset_size: 31239 --- # Dataset Card for "mmlu-computer_security-neg-answer" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
lowo/ncep-TestData1	--- license: mit ---
Moatazz/First	--- task_categories: - text-classification language: - en pretty_name: Trial size_categories: - n<1K ---
tner/bc5cdr	--- language: - en license: - other multilinguality: - monolingual size_categories: - 10K<n<100K task_categories: - token-classification task_ids: - named-entity-recognition pretty_name: BioCreative V CDR --- # Dataset Card for "tner/bc5cdr" ## Dataset Description - Repository: [T-NER](https://github.com/asahi417/tner) - Paper: [https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true](https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true) - Dataset: BioCreative V CDR - Domain: Biomedical - Number of Entity: 2 ### Dataset Summary BioCreative V CDR NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. The original dataset consists of long documents which cannot be fed on LM because of the length, so we split them into sentences to reduce their size. - Entity Types: `Chemical`, `Disease` ## Dataset Structure ### Data Instances An example of `train` looks as follows. ``` { 'tags': [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0], 'tokens': ['Fasciculations', 'in', 'six', 'areas', 'of', 'the', 'body', 'were', 'scored', 'from', '0', 'to', '3', 'and', 'summated', 'as', 'a', 'total', 'fasciculation', 'score', '.'] } ``` ### Label ID The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/bc5cdr/raw/main/dataset/label.json). ```python { "O": 0, "B-Chemical": 1, "B-Disease": 2, "I-Disease": 3, "I-Chemical": 4 } ``` ### Data Splits \| name \|train\|validation\|test\| \|---------\|----:\|---------:\|---:\| \|bc5cdr\|5228\| 5330\|5865\| ### Citation Information ``` @article{wei2016assessing, title={Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task}, author={Wei, Chih-Hsuan and Peng, Yifan and Leaman, Robert and Davis, Allan Peter and Mattingly, Carolyn J and Li, Jiao and Wiegers, Thomas C and Lu, Zhiyong}, journal={Database}, volume={2016}, year={2016}, publisher={Oxford Academic} } ```
davanstrien/on_the_books	--- license: cc-by-3.0 language: - en tags: - lam pretty_name: On the Books --- # Dataset Card for Dataset Name ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [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]
andrewrreed/fewnerd-person-names-augmented	--- dataset_info: features: - name: tokens sequence: string - name: ner_tags sequence: class_label: names: '0': O '1': B-PER '2': I-PER splits: - name: train num_bytes: 42959061.57005247 num_examples: 122254 - name: validation num_bytes: 4086233.0513204616 num_examples: 20417 - name: test num_bytes: 8454146.29895592 num_examples: 32293 download_size: 14382598 dataset_size: 55499440.92032885 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
shidowake/oasst2_answers_from_g-ronimo_subset_split_0	--- dataset_info: features: - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 7084599.121609153 num_examples: 2710 download_size: 3550248 dataset_size: 7084599.121609153 configs: - config_name: default data_files: - split: train path: data/train-* ---
niizam/fgo-story	--- license: cc-by-2.0 task_categories: - translation language: - en - ja - id tags: - story - conversation size_categories: - 1M<n<10M ---
lim4349/origin_added_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: 83769368 num_examples: 57923 - name: validation num_bytes: 9244735 num_examples: 6436 download_size: 57373216 dataset_size: 93014103 --- # Dataset Card for "origin_added_korquad" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Nexdata/Russian_Speech_Data_by_Mobile_Phone	--- YAML tags: - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging --- # Dataset Card for Nexdata/Russian_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/976?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1960 Russian native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, in-vehicle and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/976?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Russian ## 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 Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions
harshgulati/guanaco-llama2-1k	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1654448 num_examples: 1000 download_size: 966692 dataset_size: 1654448 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA	--- pretty_name: Evaluation run of quantumaikr/QuantumLM-llama2-70B-Korean-LoRA dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [quantumaikr/QuantumLM-llama2-70B-Korean-LoRA](https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA)\ \ 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_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-30T07:53:24.183560](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA/blob/main/results_2023-08-30T07%3A53%3A24.183560.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\": 0.6934168799483462,\n\ \ \"acc_stderr\": 0.03115919348812645,\n \"acc_norm\": 0.6971494359890498,\n\ \ \"acc_norm_stderr\": 0.031131669600877022,\n \"mc1\": 0.401468788249694,\n\ \ \"mc1_stderr\": 0.017160273901693654,\n \"mc2\": 0.5608488880093394,\n\ \ \"mc2_stderr\": 0.014874770245335572\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6749146757679181,\n \"acc_stderr\": 0.013688147309729119,\n\ \ \"acc_norm\": 0.7056313993174061,\n \"acc_norm_stderr\": 0.013318528460539422\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6743676558454491,\n\ \ \"acc_stderr\": 0.004676529200753001,\n \"acc_norm\": 0.8638717386974706,\n\ \ \"acc_norm_stderr\": 0.0034222387022263645\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5925925925925926,\n\ \ \"acc_stderr\": 0.04244633238353228,\n \"acc_norm\": 0.5925925925925926,\n\ \ \"acc_norm_stderr\": 0.04244633238353228\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.8289473684210527,\n \"acc_stderr\": 0.03064360707167709,\n\ \ \"acc_norm\": 0.8289473684210527,\n \"acc_norm_stderr\": 0.03064360707167709\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7245283018867924,\n \"acc_stderr\": 0.027495663683724057,\n\ \ \"acc_norm\": 0.7245283018867924,\n \"acc_norm_stderr\": 0.027495663683724057\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.031164899666948617,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.031164899666948617\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-college_mathematics\|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-college_medicine\|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082635,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082635\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.73,\n \"acc_stderr\": 0.04461960433384739,\n \"acc_norm\": 0.73,\n\ \ \"acc_norm_stderr\": 0.04461960433384739\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6808510638297872,\n \"acc_stderr\": 0.030472973363380045,\n\ \ \"acc_norm\": 0.6808510638297872,\n \"acc_norm_stderr\": 0.030472973363380045\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.4473684210526316,\n\ \ \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.4473684210526316,\n\ \ \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5862068965517241,\n \"acc_stderr\": 0.04104269211806232,\n\ \ \"acc_norm\": 0.5862068965517241,\n \"acc_norm_stderr\": 0.04104269211806232\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.43915343915343913,\n \"acc_stderr\": 0.02555992055053101,\n \"\ acc_norm\": 0.43915343915343913,\n \"acc_norm_stderr\": 0.02555992055053101\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\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.8451612903225807,\n\ \ \"acc_stderr\": 0.020579287326583227,\n \"acc_norm\": 0.8451612903225807,\n\ \ \"acc_norm_stderr\": 0.020579287326583227\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5320197044334976,\n \"acc_stderr\": 0.03510766597959217,\n\ \ \"acc_norm\": 0.5320197044334976,\n \"acc_norm_stderr\": 0.03510766597959217\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\"\ : 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8242424242424242,\n \"acc_stderr\": 0.02972094300622445,\n\ \ \"acc_norm\": 0.8242424242424242,\n \"acc_norm_stderr\": 0.02972094300622445\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.8636363636363636,\n \"acc_stderr\": 0.024450155973189835,\n \"\ acc_norm\": 0.8636363636363636,\n \"acc_norm_stderr\": 0.024450155973189835\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9430051813471503,\n \"acc_stderr\": 0.01673108529360756,\n\ \ \"acc_norm\": 0.9430051813471503,\n \"acc_norm_stderr\": 0.01673108529360756\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.7256410256410256,\n \"acc_stderr\": 0.022622765767493225,\n\ \ \"acc_norm\": 0.7256410256410256,\n \"acc_norm_stderr\": 0.022622765767493225\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.35185185185185186,\n \"acc_stderr\": 0.029116617606083015,\n \ \ \"acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.029116617606083015\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.7857142857142857,\n \"acc_stderr\": 0.026653531596715484,\n\ \ \"acc_norm\": 0.7857142857142857,\n \"acc_norm_stderr\": 0.026653531596715484\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.45695364238410596,\n \"acc_stderr\": 0.04067325174247443,\n \"\ acc_norm\": 0.45695364238410596,\n \"acc_norm_stderr\": 0.04067325174247443\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8844036697247707,\n \"acc_stderr\": 0.013708749534172636,\n \"\ acc_norm\": 0.8844036697247707,\n \"acc_norm_stderr\": 0.013708749534172636\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5879629629629629,\n \"acc_stderr\": 0.03356787758160831,\n \"\ acc_norm\": 0.5879629629629629,\n \"acc_norm_stderr\": 0.03356787758160831\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9068627450980392,\n \"acc_stderr\": 0.020397853969427,\n \"acc_norm\"\ : 0.9068627450980392,\n \"acc_norm_stderr\": 0.020397853969427\n },\n\ \ \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"acc\":\ \ 0.8734177215189873,\n \"acc_stderr\": 0.02164419572795517,\n \"\ acc_norm\": 0.8734177215189873,\n \"acc_norm_stderr\": 0.02164419572795517\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7757847533632287,\n\ \ \"acc_stderr\": 0.027991534258519517,\n \"acc_norm\": 0.7757847533632287,\n\ \ \"acc_norm_stderr\": 0.027991534258519517\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8320610687022901,\n \"acc_stderr\": 0.032785485373431386,\n\ \ \"acc_norm\": 0.8320610687022901,\n \"acc_norm_stderr\": 0.032785485373431386\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.8842975206611571,\n \"acc_stderr\": 0.029199802455622814,\n \"\ acc_norm\": 0.8842975206611571,\n \"acc_norm_stderr\": 0.029199802455622814\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8518518518518519,\n\ \ \"acc_stderr\": 0.03434300243631,\n \"acc_norm\": 0.8518518518518519,\n\ \ \"acc_norm_stderr\": 0.03434300243631\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\": 0.5267857142857143,\n\ \ \"acc_stderr\": 0.047389751192741546,\n \"acc_norm\": 0.5267857142857143,\n\ \ \"acc_norm_stderr\": 0.047389751192741546\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.0398913985953177,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.0398913985953177\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8717948717948718,\n\ \ \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n\ \ \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8531289910600255,\n\ \ \"acc_stderr\": 0.012658201736147278,\n \"acc_norm\": 0.8531289910600255,\n\ \ \"acc_norm_stderr\": 0.012658201736147278\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7687861271676301,\n \"acc_stderr\": 0.022698657167855713,\n\ \ \"acc_norm\": 0.7687861271676301,\n \"acc_norm_stderr\": 0.022698657167855713\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.5094972067039106,\n\ \ \"acc_stderr\": 0.01671948464334877,\n \"acc_norm\": 0.5094972067039106,\n\ \ \"acc_norm_stderr\": 0.01671948464334877\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7679738562091504,\n \"acc_stderr\": 0.024170840879340873,\n\ \ \"acc_norm\": 0.7679738562091504,\n \"acc_norm_stderr\": 0.024170840879340873\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7588424437299035,\n\ \ \"acc_stderr\": 0.024296594034763426,\n \"acc_norm\": 0.7588424437299035,\n\ \ \"acc_norm_stderr\": 0.024296594034763426\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8055555555555556,\n \"acc_stderr\": 0.022021366100220194,\n\ \ \"acc_norm\": 0.8055555555555556,\n \"acc_norm_stderr\": 0.022021366100220194\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5567375886524822,\n \"acc_stderr\": 0.02963483847376601,\n \ \ \"acc_norm\": 0.5567375886524822,\n \"acc_norm_stderr\": 0.02963483847376601\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.5560625814863103,\n\ \ \"acc_stderr\": 0.012689708167787677,\n \"acc_norm\": 0.5560625814863103,\n\ \ \"acc_norm_stderr\": 0.012689708167787677\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.7536764705882353,\n \"acc_stderr\": 0.02617343857052,\n\ \ \"acc_norm\": 0.7536764705882353,\n \"acc_norm_stderr\": 0.02617343857052\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.7630718954248366,\n \"acc_stderr\": 0.01720166216978977,\n \ \ \"acc_norm\": 0.7630718954248366,\n \"acc_norm_stderr\": 0.01720166216978977\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7181818181818181,\n\ \ \"acc_stderr\": 0.04309118709946458,\n \"acc_norm\": 0.7181818181818181,\n\ \ \"acc_norm_stderr\": 0.04309118709946458\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7755102040816326,\n \"acc_stderr\": 0.0267114305555384,\n\ \ \"acc_norm\": 0.7755102040816326,\n \"acc_norm_stderr\": 0.0267114305555384\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8955223880597015,\n\ \ \"acc_stderr\": 0.021628920516700643,\n \"acc_norm\": 0.8955223880597015,\n\ \ \"acc_norm_stderr\": 0.021628920516700643\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.93,\n \"acc_stderr\": 0.0256432399976243,\n \ \ \"acc_norm\": 0.93,\n \"acc_norm_stderr\": 0.0256432399976243\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.536144578313253,\n\ \ \"acc_stderr\": 0.038823108508905954,\n \"acc_norm\": 0.536144578313253,\n\ \ \"acc_norm_stderr\": 0.038823108508905954\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.02709729011807082,\n\ \ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.02709729011807082\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.401468788249694,\n\ \ \"mc1_stderr\": 0.017160273901693654,\n \"mc2\": 0.5608488880093394,\n\ \ \"mc2_stderr\": 0.014874770245335572\n }\n}\n```" repo_url: https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA 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_30T07_53_24.183560 path: - '/details_harness\|arc:challenge\|25_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hellaswag\|10_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T07:53:24.183560.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_30T07_53_24.183560 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-30T07:53:24.183560.parquet' - config_name: results data_files: - split: 2023_08_30T07_53_24.183560 path: - results_2023-08-30T07:53:24.183560.parquet - split: latest path: - results_2023-08-30T07:53:24.183560.parquet --- # Dataset Card for Evaluation run of quantumaikr/QuantumLM-llama2-70B-Korean-LoRA ## Dataset Description - Homepage: - Repository: https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA - 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 [quantumaikr/QuantumLM-llama2-70B-Korean-LoRA](https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA) 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_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-30T07:53:24.183560](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA/blob/main/results_2023-08-30T07%3A53%3A24.183560.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": 0.6934168799483462, "acc_stderr": 0.03115919348812645, "acc_norm": 0.6971494359890498, "acc_norm_stderr": 0.031131669600877022, "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5608488880093394, "mc2_stderr": 0.014874770245335572 }, "harness\|arc:challenge\|25": { "acc": 0.6749146757679181, "acc_stderr": 0.013688147309729119, "acc_norm": 0.7056313993174061, "acc_norm_stderr": 0.013318528460539422 }, "harness\|hellaswag\|10": { "acc": 0.6743676558454491, "acc_stderr": 0.004676529200753001, "acc_norm": 0.8638717386974706, "acc_norm_stderr": 0.0034222387022263645 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5925925925925926, "acc_stderr": 0.04244633238353228, "acc_norm": 0.5925925925925926, "acc_norm_stderr": 0.04244633238353228 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.8289473684210527, "acc_stderr": 0.03064360707167709, "acc_norm": 0.8289473684210527, "acc_norm_stderr": 0.03064360707167709 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7245283018867924, "acc_stderr": 0.027495663683724057, "acc_norm": 0.7245283018867924, "acc_norm_stderr": 0.027495663683724057 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.031164899666948617, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.031164899666948617 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082635, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082635 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.73, "acc_stderr": 0.04461960433384739, "acc_norm": 0.73, "acc_norm_stderr": 0.04461960433384739 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6808510638297872, "acc_stderr": 0.030472973363380045, "acc_norm": 0.6808510638297872, "acc_norm_stderr": 0.030472973363380045 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.4473684210526316, "acc_stderr": 0.04677473004491199, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.04677473004491199 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5862068965517241, "acc_stderr": 0.04104269211806232, "acc_norm": 0.5862068965517241, "acc_norm_stderr": 0.04104269211806232 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.43915343915343913, "acc_stderr": 0.02555992055053101, "acc_norm": 0.43915343915343913, "acc_norm_stderr": 0.02555992055053101 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.8451612903225807, "acc_stderr": 0.020579287326583227, "acc_norm": 0.8451612903225807, "acc_norm_stderr": 0.020579287326583227 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5320197044334976, "acc_stderr": 0.03510766597959217, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.03510766597959217 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8242424242424242, "acc_stderr": 0.02972094300622445, "acc_norm": 0.8242424242424242, "acc_norm_stderr": 0.02972094300622445 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9430051813471503, "acc_stderr": 0.01673108529360756, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.01673108529360756 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.7256410256410256, "acc_stderr": 0.022622765767493225, "acc_norm": 0.7256410256410256, "acc_norm_stderr": 0.022622765767493225 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.35185185185185186, "acc_stderr": 0.029116617606083015, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.029116617606083015 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.7857142857142857, "acc_stderr": 0.026653531596715484, "acc_norm": 0.7857142857142857, "acc_norm_stderr": 0.026653531596715484 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.45695364238410596, "acc_stderr": 0.04067325174247443, "acc_norm": 0.45695364238410596, "acc_norm_stderr": 0.04067325174247443 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8844036697247707, "acc_stderr": 0.013708749534172636, "acc_norm": 0.8844036697247707, "acc_norm_stderr": 0.013708749534172636 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5879629629629629, "acc_stderr": 0.03356787758160831, "acc_norm": 0.5879629629629629, "acc_norm_stderr": 0.03356787758160831 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9068627450980392, "acc_stderr": 0.020397853969427, "acc_norm": 0.9068627450980392, "acc_norm_stderr": 0.020397853969427 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8734177215189873, "acc_stderr": 0.02164419572795517, "acc_norm": 0.8734177215189873, "acc_norm_stderr": 0.02164419572795517 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7757847533632287, "acc_stderr": 0.027991534258519517, "acc_norm": 0.7757847533632287, "acc_norm_stderr": 0.027991534258519517 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8320610687022901, "acc_stderr": 0.032785485373431386, "acc_norm": 0.8320610687022901, "acc_norm_stderr": 0.032785485373431386 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.8842975206611571, "acc_stderr": 0.029199802455622814, "acc_norm": 0.8842975206611571, "acc_norm_stderr": 0.029199802455622814 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8518518518518519, "acc_stderr": 0.03434300243631, "acc_norm": 0.8518518518518519, "acc_norm_stderr": 0.03434300243631 }, "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": 0.5267857142857143, "acc_stderr": 0.047389751192741546, "acc_norm": 0.5267857142857143, "acc_norm_stderr": 0.047389751192741546 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7961165048543689, "acc_stderr": 0.0398913985953177, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.0398913985953177 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8717948717948718, "acc_stderr": 0.02190190511507333, "acc_norm": 0.8717948717948718, "acc_norm_stderr": 0.02190190511507333 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8531289910600255, "acc_stderr": 0.012658201736147278, "acc_norm": 0.8531289910600255, "acc_norm_stderr": 0.012658201736147278 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7687861271676301, "acc_stderr": 0.022698657167855713, "acc_norm": 0.7687861271676301, "acc_norm_stderr": 0.022698657167855713 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.5094972067039106, "acc_stderr": 0.01671948464334877, "acc_norm": 0.5094972067039106, "acc_norm_stderr": 0.01671948464334877 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7679738562091504, "acc_stderr": 0.024170840879340873, "acc_norm": 0.7679738562091504, "acc_norm_stderr": 0.024170840879340873 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7588424437299035, "acc_stderr": 0.024296594034763426, "acc_norm": 0.7588424437299035, "acc_norm_stderr": 0.024296594034763426 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8055555555555556, "acc_stderr": 0.022021366100220194, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.022021366100220194 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5567375886524822, "acc_stderr": 0.02963483847376601, "acc_norm": 0.5567375886524822, "acc_norm_stderr": 0.02963483847376601 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.5560625814863103, "acc_stderr": 0.012689708167787677, "acc_norm": 0.5560625814863103, "acc_norm_stderr": 0.012689708167787677 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.7536764705882353, "acc_stderr": 0.02617343857052, "acc_norm": 0.7536764705882353, "acc_norm_stderr": 0.02617343857052 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.7630718954248366, "acc_stderr": 0.01720166216978977, "acc_norm": 0.7630718954248366, "acc_norm_stderr": 0.01720166216978977 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7181818181818181, "acc_stderr": 0.04309118709946458, "acc_norm": 0.7181818181818181, "acc_norm_stderr": 0.04309118709946458 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7755102040816326, "acc_stderr": 0.0267114305555384, "acc_norm": 0.7755102040816326, "acc_norm_stderr": 0.0267114305555384 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8955223880597015, "acc_stderr": 0.021628920516700643, "acc_norm": 0.8955223880597015, "acc_norm_stderr": 0.021628920516700643 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.93, "acc_stderr": 0.0256432399976243, "acc_norm": 0.93, "acc_norm_stderr": 0.0256432399976243 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.536144578313253, "acc_stderr": 0.038823108508905954, "acc_norm": 0.536144578313253, "acc_norm_stderr": 0.038823108508905954 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8538011695906432, "acc_stderr": 0.02709729011807082, "acc_norm": 0.8538011695906432, "acc_norm_stderr": 0.02709729011807082 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5608488880093394, "mc2_stderr": 0.014874770245335572 } } ``` ### 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]
bigscience-data/roots_zh_ted_talks_iwslt	--- language: zh license: cc-by-nc-nd-4.0 extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience Ethical Charter. The charter can be found at: https://hf.co/spaces/bigscience/ethical-charter' extra_gated_fields: I have read and agree to abide by the BigScience Ethical Charter: checkbox --- ROOTS Subset: roots_zh_ted_talks_iwslt # WIT Ted Talks - Dataset uid: `ted_talks_iwslt` ### Description The Web Inventory Talk is a collection of the original Ted talks and their translated version. The translations are available in more than 109+ languages, though the distribution is not uniform. ### Homepage https://github.com/huggingface/datasets/blob/master/datasets/ted_talks_iwslt/README.md ### Licensing - open license - cc-by-nc-4.0: Creative Commons Attribution Non Commercial 4.0 International TED makes its collection of video recordings and transcripts of talks available under the Creative Commons BY-NC-ND license (look here). WIT3 acknowledges the authorship of TED talks (BY condition) and does not redistribute transcripts for commercial purposes (NC). As regards the integrity of the work (ND), WIT3 only changes the format of the container, while preserving the original contents. WIT3 aims to support research on human language processing as well as the diffusion of TED Talks! ### Speaker Locations - Southern Europe - Italy ### Sizes - 0.0305 % of total - 0.0736 % of ar - 0.2002 % of pt - 0.0128 % of zh - 0.2236 % of vi - 0.0330 % of fr - 0.0545 % of es - 0.0122 % of en - 0.3704 % of id - 0.0373 % of indic-hi - 0.0330 % of indic-ta - 0.1393 % of indic-mr - 0.0305 % of ca - 0.1179 % of indic-ur - 0.0147 % of indic-bn - 0.0240 % of indic-ml - 0.0244 % of indic-te - 0.0503 % of indic-gu - 0.0211 % of indic-kn - 0.0274 % of eu - 0.0023 % of indic-as - 0.0001 % of indic-pa ### BigScience processing steps #### Filters applied to: ar - dedup_document - dedup_template_soft - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: pt - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: zh - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: vi - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: fr - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: es - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: en - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: id - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-hi - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-ta - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-mr - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: ca - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: indic-ur - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-bn - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-ml - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-te - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-gu - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-kn - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: eu - dedup_document - filter_remove_empty_docs #### Filters applied to: indic-as - dedup_document - filter_remove_empty_docs #### Filters applied to: indic-pa - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300
japanese-asr/whisper_transcriptions.reazonspeech.all_12	--- 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: 30338653855.0 num_examples: 266555 download_size: 30101931897 dataset_size: 30338653855.0 configs: - config_name: all data_files: - split: train path: all/train-* ---
open-llm-leaderboard/details_NoIdeaLand__test-4k-fn	--- pretty_name: Evaluation run of NoIdeaLand/test-4k-fn dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NoIdeaLand/test-4k-fn](https://huggingface.co/NoIdeaLand/test-4k-fn) 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_NoIdeaLand__test-4k-fn\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-10-01T16:31:47.992543](https://huggingface.co/datasets/open-llm-leaderboard/details_NoIdeaLand__test-4k-fn/blob/main/results_2023-10-01T16-31-47.992543.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\": 0.2795859427889157,\n\ \ \"acc_stderr\": 0.03244654146727709,\n \"acc_norm\": 0.283431508310814,\n\ \ \"acc_norm_stderr\": 0.032446107426975616,\n \"mc1\": 0.23255813953488372,\n\ \ \"mc1_stderr\": 0.014789157531080512,\n \"mc2\": 0.38860179255046867,\n\ \ \"mc2_stderr\": 0.014093255696402213\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.35665529010238906,\n \"acc_stderr\": 0.01399805690262019,\n\ \ \"acc_norm\": 0.3993174061433447,\n \"acc_norm_stderr\": 0.014312094557946704\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4971121290579566,\n\ \ \"acc_stderr\": 0.004989698183207823,\n \"acc_norm\": 0.6813383788090022,\n\ \ \"acc_norm_stderr\": 0.004650052150094427\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816508,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816508\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.23703703703703705,\n\ \ \"acc_stderr\": 0.03673731683969506,\n \"acc_norm\": 0.23703703703703705,\n\ \ \"acc_norm_stderr\": 0.03673731683969506\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.18421052631578946,\n \"acc_stderr\": 0.0315469804508223,\n\ \ \"acc_norm\": 0.18421052631578946,\n \"acc_norm_stderr\": 0.0315469804508223\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.29056603773584905,\n \"acc_stderr\": 0.027943219989337145,\n\ \ \"acc_norm\": 0.29056603773584905,\n \"acc_norm_stderr\": 0.027943219989337145\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness\|hendrycksTest-college_chemistry\|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_computer_science\|5\": {\n \"acc\"\ : 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n\ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness\|hendrycksTest-college_mathematics\|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_medicine\|5\": {\n \"acc\": 0.2543352601156069,\n\ \ \"acc_stderr\": 0.0332055644308557,\n \"acc_norm\": 0.2543352601156069,\n\ \ \"acc_norm_stderr\": 0.0332055644308557\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617746,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617746\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.3021276595744681,\n \"acc_stderr\": 0.030017554471880557,\n\ \ \"acc_norm\": 0.3021276595744681,\n \"acc_norm_stderr\": 0.030017554471880557\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.21929824561403508,\n\ \ \"acc_stderr\": 0.03892431106518754,\n \"acc_norm\": 0.21929824561403508,\n\ \ \"acc_norm_stderr\": 0.03892431106518754\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.3103448275862069,\n \"acc_stderr\": 0.038552896163789485,\n\ \ \"acc_norm\": 0.3103448275862069,\n \"acc_norm_stderr\": 0.038552896163789485\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948365,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948365\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.03670066451047182,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.03670066451047182\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.24838709677419354,\n\ \ \"acc_stderr\": 0.024580028921481003,\n \"acc_norm\": 0.24838709677419354,\n\ \ \"acc_norm_stderr\": 0.024580028921481003\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.2019704433497537,\n \"acc_stderr\": 0.02824735012218027,\n\ \ \"acc_norm\": 0.2019704433497537,\n \"acc_norm_stderr\": 0.02824735012218027\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|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-high_school_european_history\|5\"\ : {\n \"acc\": 0.2727272727272727,\n \"acc_stderr\": 0.0347769116216366,\n\ \ \"acc_norm\": 0.2727272727272727,\n \"acc_norm_stderr\": 0.0347769116216366\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.23232323232323232,\n \"acc_stderr\": 0.030088629490217487,\n \"\ acc_norm\": 0.23232323232323232,\n \"acc_norm_stderr\": 0.030088629490217487\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.3471502590673575,\n \"acc_stderr\": 0.03435696168361355,\n\ \ \"acc_norm\": 0.3471502590673575,\n \"acc_norm_stderr\": 0.03435696168361355\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.31025641025641026,\n \"acc_stderr\": 0.023454674889404288,\n\ \ \"acc_norm\": 0.31025641025641026,\n \"acc_norm_stderr\": 0.023454674889404288\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\": 0.25630252100840334,\n \"acc_stderr\": 0.02835962087053395,\n\ \ \"acc_norm\": 0.25630252100840334,\n \"acc_norm_stderr\": 0.02835962087053395\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.036313298039696525,\n \"\ acc_norm\": 0.271523178807947,\n \"acc_norm_stderr\": 0.036313298039696525\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.24036697247706423,\n \"acc_stderr\": 0.01832060732096407,\n \"\ acc_norm\": 0.24036697247706423,\n \"acc_norm_stderr\": 0.01832060732096407\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.26851851851851855,\n \"acc_stderr\": 0.030225226160012397,\n \"\ acc_norm\": 0.26851851851851855,\n \"acc_norm_stderr\": 0.030225226160012397\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.24509803921568626,\n \"acc_stderr\": 0.03019028245350194,\n \"\ acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.03019028245350194\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.3037974683544304,\n \"acc_stderr\": 0.029936696387138605,\n \ \ \"acc_norm\": 0.3037974683544304,\n \"acc_norm_stderr\": 0.029936696387138605\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.3542600896860987,\n\ \ \"acc_stderr\": 0.03210062154134987,\n \"acc_norm\": 0.3542600896860987,\n\ \ \"acc_norm_stderr\": 0.03210062154134987\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.2900763358778626,\n \"acc_stderr\": 0.03980066246467765,\n\ \ \"acc_norm\": 0.2900763358778626,\n \"acc_norm_stderr\": 0.03980066246467765\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.35537190082644626,\n \"acc_stderr\": 0.04369236326573981,\n \"\ acc_norm\": 0.35537190082644626,\n \"acc_norm_stderr\": 0.04369236326573981\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.26851851851851855,\n\ \ \"acc_stderr\": 0.04284467968052192,\n \"acc_norm\": 0.26851851851851855,\n\ \ \"acc_norm_stderr\": 0.04284467968052192\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.27607361963190186,\n \"acc_stderr\": 0.0351238528370505,\n\ \ \"acc_norm\": 0.27607361963190186,\n \"acc_norm_stderr\": 0.0351238528370505\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.35714285714285715,\n\ \ \"acc_stderr\": 0.04547960999764376,\n \"acc_norm\": 0.35714285714285715,\n\ \ \"acc_norm_stderr\": 0.04547960999764376\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.22330097087378642,\n \"acc_stderr\": 0.04123553189891431,\n\ \ \"acc_norm\": 0.22330097087378642,\n \"acc_norm_stderr\": 0.04123553189891431\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.3803418803418803,\n\ \ \"acc_stderr\": 0.03180425204384099,\n \"acc_norm\": 0.3803418803418803,\n\ \ \"acc_norm_stderr\": 0.03180425204384099\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.24521072796934865,\n\ \ \"acc_stderr\": 0.015384352284543936,\n \"acc_norm\": 0.24521072796934865,\n\ \ \"acc_norm_stderr\": 0.015384352284543936\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.2543352601156069,\n \"acc_stderr\": 0.02344582627654555,\n\ \ \"acc_norm\": 0.2543352601156069,\n \"acc_norm_stderr\": 0.02344582627654555\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.3235294117647059,\n \"acc_stderr\": 0.02678745311190654,\n\ \ \"acc_norm\": 0.3235294117647059,\n \"acc_norm_stderr\": 0.02678745311190654\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.2508038585209003,\n\ \ \"acc_stderr\": 0.024619771956697165,\n \"acc_norm\": 0.2508038585209003,\n\ \ \"acc_norm_stderr\": 0.024619771956697165\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.22530864197530864,\n \"acc_stderr\": 0.02324620264781975,\n\ \ \"acc_norm\": 0.22530864197530864,\n \"acc_norm_stderr\": 0.02324620264781975\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.2553191489361702,\n \"acc_stderr\": 0.026011992930902013,\n \ \ \"acc_norm\": 0.2553191489361702,\n \"acc_norm_stderr\": 0.026011992930902013\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.2777053455019557,\n\ \ \"acc_stderr\": 0.011438741422769575,\n \"acc_norm\": 0.2777053455019557,\n\ \ \"acc_norm_stderr\": 0.011438741422769575\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.1948529411764706,\n \"acc_stderr\": 0.024060599423487428,\n\ \ \"acc_norm\": 0.1948529411764706,\n \"acc_norm_stderr\": 0.024060599423487428\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.28104575163398693,\n \"acc_stderr\": 0.018185218954318075,\n \ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.018185218954318075\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.3181818181818182,\n\ \ \"acc_stderr\": 0.044612721759105085,\n \"acc_norm\": 0.3181818181818182,\n\ \ \"acc_norm_stderr\": 0.044612721759105085\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.2530612244897959,\n \"acc_stderr\": 0.027833023871399677,\n\ \ \"acc_norm\": 0.2530612244897959,\n \"acc_norm_stderr\": 0.027833023871399677\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.27860696517412936,\n\ \ \"acc_stderr\": 0.031700561834973086,\n \"acc_norm\": 0.27860696517412936,\n\ \ \"acc_norm_stderr\": 0.031700561834973086\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.2891566265060241,\n\ \ \"acc_stderr\": 0.03529486801511114,\n \"acc_norm\": 0.2891566265060241,\n\ \ \"acc_norm_stderr\": 0.03529486801511114\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.3216374269005848,\n \"acc_stderr\": 0.03582529442573122,\n\ \ \"acc_norm\": 0.3216374269005848,\n \"acc_norm_stderr\": 0.03582529442573122\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.23255813953488372,\n\ \ \"mc1_stderr\": 0.014789157531080512,\n \"mc2\": 0.38860179255046867,\n\ \ \"mc2_stderr\": 0.014093255696402213\n }\n}\n```" repo_url: https://huggingface.co/NoIdeaLand/test-4k-fn 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_10_01T16_31_47.992543 path: - '/details_harness\|arc:challenge\|25_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hellaswag\|10_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T16-31-47.992543.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_01T16_31_47.992543 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T16-31-47.992543.parquet' - config_name: results data_files: - split: 2023_10_01T16_31_47.992543 path: - results_2023-10-01T16-31-47.992543.parquet - split: latest path: - results_2023-10-01T16-31-47.992543.parquet --- # Dataset Card for Evaluation run of NoIdeaLand/test-4k-fn ## Dataset Description - Homepage: - Repository: https://huggingface.co/NoIdeaLand/test-4k-fn - 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 [NoIdeaLand/test-4k-fn](https://huggingface.co/NoIdeaLand/test-4k-fn) 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_NoIdeaLand__test-4k-fn", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-10-01T16:31:47.992543](https://huggingface.co/datasets/open-llm-leaderboard/details_NoIdeaLand__test-4k-fn/blob/main/results_2023-10-01T16-31-47.992543.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": 0.2795859427889157, "acc_stderr": 0.03244654146727709, "acc_norm": 0.283431508310814, "acc_norm_stderr": 0.032446107426975616, "mc1": 0.23255813953488372, "mc1_stderr": 0.014789157531080512, "mc2": 0.38860179255046867, "mc2_stderr": 0.014093255696402213 }, "harness\|arc:challenge\|25": { "acc": 0.35665529010238906, "acc_stderr": 0.01399805690262019, "acc_norm": 0.3993174061433447, "acc_norm_stderr": 0.014312094557946704 }, "harness\|hellaswag\|10": { "acc": 0.4971121290579566, "acc_stderr": 0.004989698183207823, "acc_norm": 0.6813383788090022, "acc_norm_stderr": 0.004650052150094427 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816508, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816508 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.23703703703703705, "acc_stderr": 0.03673731683969506, "acc_norm": 0.23703703703703705, "acc_norm_stderr": 0.03673731683969506 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.18421052631578946, "acc_stderr": 0.0315469804508223, "acc_norm": 0.18421052631578946, "acc_norm_stderr": 0.0315469804508223 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.29056603773584905, "acc_stderr": 0.027943219989337145, "acc_norm": 0.29056603773584905, "acc_norm_stderr": 0.027943219989337145 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.037455547914624555, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.037455547914624555 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.2543352601156069, "acc_stderr": 0.0332055644308557, "acc_norm": 0.2543352601156069, "acc_norm_stderr": 0.0332055644308557 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617746, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617746 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3021276595744681, "acc_stderr": 0.030017554471880557, "acc_norm": 0.3021276595744681, "acc_norm_stderr": 0.030017554471880557 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.21929824561403508, "acc_stderr": 0.03892431106518754, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.03892431106518754 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.3103448275862069, "acc_stderr": 0.038552896163789485, "acc_norm": 0.3103448275862069, "acc_norm_stderr": 0.038552896163789485 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.21428571428571427, "acc_stderr": 0.03670066451047182, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.03670066451047182 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.24838709677419354, "acc_stderr": 0.024580028921481003, "acc_norm": 0.24838709677419354, "acc_norm_stderr": 0.024580028921481003 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.2019704433497537, "acc_stderr": 0.02824735012218027, "acc_norm": 0.2019704433497537, "acc_norm_stderr": 0.02824735012218027 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.2727272727272727, "acc_stderr": 0.0347769116216366, "acc_norm": 0.2727272727272727, "acc_norm_stderr": 0.0347769116216366 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.23232323232323232, "acc_stderr": 0.030088629490217487, "acc_norm": 0.23232323232323232, "acc_norm_stderr": 0.030088629490217487 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.3471502590673575, "acc_stderr": 0.03435696168361355, "acc_norm": 0.3471502590673575, "acc_norm_stderr": 0.03435696168361355 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.31025641025641026, "acc_stderr": 0.023454674889404288, "acc_norm": 0.31025641025641026, "acc_norm_stderr": 0.023454674889404288 }, "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": 0.25630252100840334, "acc_stderr": 0.02835962087053395, "acc_norm": 0.25630252100840334, "acc_norm_stderr": 0.02835962087053395 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.271523178807947, "acc_stderr": 0.036313298039696525, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.036313298039696525 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.24036697247706423, "acc_stderr": 0.01832060732096407, "acc_norm": 0.24036697247706423, "acc_norm_stderr": 0.01832060732096407 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.26851851851851855, "acc_stderr": 0.030225226160012397, "acc_norm": 0.26851851851851855, "acc_norm_stderr": 0.030225226160012397 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.03019028245350194, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.03019028245350194 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.3037974683544304, "acc_stderr": 0.029936696387138605, "acc_norm": 0.3037974683544304, "acc_norm_stderr": 0.029936696387138605 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.3542600896860987, "acc_stderr": 0.03210062154134987, "acc_norm": 0.3542600896860987, "acc_norm_stderr": 0.03210062154134987 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.2900763358778626, "acc_stderr": 0.03980066246467765, "acc_norm": 0.2900763358778626, "acc_norm_stderr": 0.03980066246467765 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.35537190082644626, "acc_stderr": 0.04369236326573981, "acc_norm": 0.35537190082644626, "acc_norm_stderr": 0.04369236326573981 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.26851851851851855, "acc_stderr": 0.04284467968052192, "acc_norm": 0.26851851851851855, "acc_norm_stderr": 0.04284467968052192 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.27607361963190186, "acc_stderr": 0.0351238528370505, "acc_norm": 0.27607361963190186, "acc_norm_stderr": 0.0351238528370505 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.35714285714285715, "acc_stderr": 0.04547960999764376, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.04547960999764376 }, "harness\|hendrycksTest-management\|5": { "acc": 0.22330097087378642, "acc_stderr": 0.04123553189891431, "acc_norm": 0.22330097087378642, "acc_norm_stderr": 0.04123553189891431 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.3803418803418803, "acc_stderr": 0.03180425204384099, "acc_norm": 0.3803418803418803, "acc_norm_stderr": 0.03180425204384099 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.24521072796934865, "acc_stderr": 0.015384352284543936, "acc_norm": 0.24521072796934865, "acc_norm_stderr": 0.015384352284543936 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.2543352601156069, "acc_stderr": 0.02344582627654555, "acc_norm": 0.2543352601156069, "acc_norm_stderr": 0.02344582627654555 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.3235294117647059, "acc_stderr": 0.02678745311190654, "acc_norm": 0.3235294117647059, "acc_norm_stderr": 0.02678745311190654 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.2508038585209003, "acc_stderr": 0.024619771956697165, "acc_norm": 0.2508038585209003, "acc_norm_stderr": 0.024619771956697165 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.22530864197530864, "acc_stderr": 0.02324620264781975, "acc_norm": 0.22530864197530864, "acc_norm_stderr": 0.02324620264781975 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.2553191489361702, "acc_stderr": 0.026011992930902013, "acc_norm": 0.2553191489361702, "acc_norm_stderr": 0.026011992930902013 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.2777053455019557, "acc_stderr": 0.011438741422769575, "acc_norm": 0.2777053455019557, "acc_norm_stderr": 0.011438741422769575 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.1948529411764706, "acc_stderr": 0.024060599423487428, "acc_norm": 0.1948529411764706, "acc_norm_stderr": 0.024060599423487428 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.28104575163398693, "acc_stderr": 0.018185218954318075, "acc_norm": 0.28104575163398693, "acc_norm_stderr": 0.018185218954318075 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.3181818181818182, "acc_stderr": 0.044612721759105085, "acc_norm": 0.3181818181818182, "acc_norm_stderr": 0.044612721759105085 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.2530612244897959, "acc_stderr": 0.027833023871399677, "acc_norm": 0.2530612244897959, "acc_norm_stderr": 0.027833023871399677 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.27860696517412936, "acc_stderr": 0.031700561834973086, "acc_norm": 0.27860696517412936, "acc_norm_stderr": 0.031700561834973086 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.2891566265060241, "acc_stderr": 0.03529486801511114, "acc_norm": 0.2891566265060241, "acc_norm_stderr": 0.03529486801511114 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.23255813953488372, "mc1_stderr": 0.014789157531080512, "mc2": 0.38860179255046867, "mc2_stderr": 0.014093255696402213 } } ``` ### 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]
umarigan/turkish_corpus	--- license: mit task_categories: - feature-extraction language: - tr pretty_name: Corpus size_categories: - 10M<n<100M ---
huggingface-course/documentation-images	--- license: apache-2.0 ---
RoryCochrane/pokemon-and-fakemon	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 480609633.745 num_examples: 4763 download_size: 391516344 dataset_size: 480609633.745 --- # Dataset Card for "pokemon-and-fakemon" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/hassan_of_the_serenity_fgo	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hassan_of_the_serenity/静謐のハサン/静谧哈桑 (Fate/Grand Order) This is the dataset of hassan_of_the_serenity/静謐のハサン/静谧哈桑 (Fate/Grand Order), containing 500 images and their tags. The core tags of this character are `purple_hair, dark_skin, dark-skinned_female, purple_eyes, short_hair, breasts, hair_between_eyes, hairband, medium_breasts, black_hairband, very_dark_skin`, 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 \| 578.80 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 1200 \| 500 \| 497.24 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1186 \| 977.63 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/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/hassan_of_the_serenity_fgo', 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 \| 23 \| ![](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, bare_shoulders, black_gloves, looking_at_viewer, center_opening, black_leotard, navel, white_background, simple_background, fingerless_gloves, holding, weapon, parted_lips \| \| 1 \| 6 \| ![](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, black_gloves, center_opening, fingerless_gloves, navel, solo, black_leotard, blush, cleavage, looking_at_viewer, open_mouth \| \| 2 \| 14 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, ass, backless_outfit, bare_back, bare_shoulders, black_gloves, fingerless_gloves, from_behind, solo, looking_at_viewer, looking_back, holding_weapon, leotard, sideboob, kunai, between_fingers, butt_crack, knife, simple_background, white_background, leggings, night, sky, toeless_legwear \| \| 3 \| 15 \| ![](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, sleeveless_dress, solo, white_dress, collarbone, white_background, looking_at_viewer, blush, sidelocks, simple_background, bare_arms, upper_body, closed_mouth, parted_lips, sundress \| \| 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, black_shirt, blush, closed_mouth, solo, white_background, looking_at_viewer, collarbone, long_sleeves, sidelocks, simple_background, sleeves_past_wrists, smile, hand_up, upper_body \| \| 5 \| 12 \| ![](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, puffy_long_sleeves, solo, hood_down, sleeves_past_wrists, smile, white_background, drawstring, simple_background, black_hoodie, closed_mouth, :>, v-shaped_eyebrows, hand_up \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| 1girl, collared_shirt, long_sleeves, looking_at_viewer, pleated_skirt, school_uniform, solo, white_background, white_shirt, blush, plaid_skirt, sleeves_past_wrists, smile, alternate_costume, blazer, closed_mouth, open_jacket, sidelocks, simple_background, black_jacket, black_skirt, bowtie, sweater \| \| 7 \| 42 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| 1girl, bare_shoulders, solo, detached_sleeves, official_alternate_costume, looking_at_viewer, detached_collar, hair_flower, long_sleeves, white_dress, ribbon, strapless_dress, blush, bow, red_apple, smile, ahoge, holding_fruit, closed_mouth, pink_dress \| \| 8 \| 10 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| 1girl, bare_shoulders, bell, looking_at_viewer, solo, blush, christmas, smile, white_thighhighs, white_panties, navel, ribbon-trimmed_legwear, red_bow, sheep_horns, underboob, closed_mouth, gift_box, sitting, stomach, bare_arms, colored_skin, fireplace, fur_collar, indoors, sidelocks \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| solo \| bare_shoulders \| black_gloves \| looking_at_viewer \| center_opening \| black_leotard \| navel \| white_background \| simple_background \| fingerless_gloves \| holding \| weapon \| parted_lips \| blush \| cleavage \| open_mouth \| ass \| backless_outfit \| bare_back \| from_behind \| looking_back \| holding_weapon \| leotard \| sideboob \| kunai \| between_fingers \| butt_crack \| knife \| leggings \| night \| sky \| toeless_legwear \| sleeveless_dress \| white_dress \| collarbone \| sidelocks \| bare_arms \| upper_body \| closed_mouth \| sundress \| black_shirt \| long_sleeves \| sleeves_past_wrists \| smile \| hand_up \| puffy_long_sleeves \| hood_down \| drawstring \| black_hoodie \| :> \| v-shaped_eyebrows \| collared_shirt \| pleated_skirt \| school_uniform \| white_shirt \| plaid_skirt \| alternate_costume \| blazer \| open_jacket \| black_jacket \| black_skirt \| bowtie \| sweater \| detached_sleeves \| official_alternate_costume \| detached_collar \| hair_flower \| ribbon \| strapless_dress \| bow \| red_apple \| ahoge \| holding_fruit \| pink_dress \| bell \| christmas \| white_thighhighs \| white_panties \| ribbon-trimmed_legwear \| red_bow \| sheep_horns \| underboob \| gift_box \| sitting \| stomach \| colored_skin \| fireplace \| fur_collar \| indoors \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:-----------------\|:---------------\|:--------------------\|:-----------------\|:----------------\|:--------\|:-------------------\|:--------------------\|:--------------------\|:----------\|:---------\|:--------------\|:--------\|:-----------\|:-------------\|:------\|:------------------\|:------------\|:--------------\|:---------------\|:-----------------\|:----------\|:-----------\|:--------\|:------------------\|:-------------\|:--------\|:-----------\|:--------\|:------\|:------------------\|:-------------------\|:--------------\|:-------------\|:------------\|:------------\|:-------------\|:---------------\|:-----------\|:--------------\|:---------------\|:----------------------\|:--------\|:----------\|:---------------------\|:------------\|:-------------\|:---------------\|:-----\|:--------------------\|:-----------------\|:----------------\|:-----------------\|:--------------\|:--------------\|:--------------------\|:---------\|:--------------\|:---------------\|:--------------\|:---------\|:----------\|:-------------------\|:-----------------------------\|:------------------\|:--------------\|:---------\|:------------------\|:------\|:------------\|:--------\|:----------------\|:-------------\|:-------\|:------------\|:-------------------\|:----------------\|:-------------------------\|:----------\|:--------------\|:------------\|:-----------\|:----------\|:----------\|:---------------\|:------------\|:-------------\|:----------\| \| 0 \| 23 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 6 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| X \| \| \| \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 14 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| X \| X \| X \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 15 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 12 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| X \| X \| \| \| X \| \| \| \| X \| X \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| X \| \| \| X \| X \| X \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 7 \| 42 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| X \| X \| X \| \| X \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| X \| \| \| X \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 8 \| 10 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| X \| X \| X \| \| X \| \| \| X \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| X \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
cgulse/alpaca-cleaned-tr	--- license: cc-by-4.0 language: - tr tags: - alpaca - instruction-finetuning pretty_name: Turkish Alpaca-cleaned size_categories: - 10K<n<100K --- Alpaca Cleaned Dataset. Machine Translated facebook/nllb-200-3.3B Languages Turkish
open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2	--- pretty_name: Evaluation run of g-ronimo/phi-2-OpenHermes-2.5-v2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [g-ronimo/phi-2-OpenHermes-2.5-v2](https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2)\ \ 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_g-ronimo__phi-2-OpenHermes-2.5-v2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-10T00:49:09.888984](https://huggingface.co/datasets/open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2/blob/main/results_2024-03-10T00-49-09.888984.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\": 0.564734458241999,\n\ \ \"acc_stderr\": 0.03391431521091429,\n \"acc_norm\": 0.5676857564160381,\n\ \ \"acc_norm_stderr\": 0.03461774832252384,\n \"mc1\": 0.3011015911872705,\n\ \ \"mc1_stderr\": 0.01605899902610061,\n \"mc2\": 0.44887128521126124,\n\ \ \"mc2_stderr\": 0.015342799330160783\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5699658703071673,\n \"acc_stderr\": 0.01446763155913799,\n\ \ \"acc_norm\": 0.5844709897610921,\n \"acc_norm_stderr\": 0.014401366641216388\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5592511451902011,\n\ \ \"acc_stderr\": 0.004954622308738996,\n \"acc_norm\": 0.7456681935869349,\n\ \ \"acc_norm_stderr\": 0.004345949382382379\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.48148148148148145,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5657894736842105,\n \"acc_stderr\": 0.0403356566784832,\n\ \ \"acc_norm\": 0.5657894736842105,\n \"acc_norm_stderr\": 0.0403356566784832\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|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-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5735849056603773,\n \"acc_stderr\": 0.03043779434298305,\n\ \ \"acc_norm\": 0.5735849056603773,\n \"acc_norm_stderr\": 0.03043779434298305\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\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|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-college_mathematics\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5491329479768786,\n\ \ \"acc_stderr\": 0.03794012674697031,\n \"acc_norm\": 0.5491329479768786,\n\ \ \"acc_norm_stderr\": 0.03794012674697031\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3137254901960784,\n \"acc_stderr\": 0.04617034827006717,\n\ \ \"acc_norm\": 0.3137254901960784,\n \"acc_norm_stderr\": 0.04617034827006717\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5276595744680851,\n \"acc_stderr\": 0.03263597118409769,\n\ \ \"acc_norm\": 0.5276595744680851,\n \"acc_norm_stderr\": 0.03263597118409769\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.39473684210526316,\n\ \ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.39473684210526316,\n\ \ \"acc_norm_stderr\": 0.045981880578165414\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5103448275862069,\n \"acc_stderr\": 0.04165774775728763,\n\ \ \"acc_norm\": 0.5103448275862069,\n \"acc_norm_stderr\": 0.04165774775728763\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.40476190476190477,\n \"acc_stderr\": 0.025279850397404907,\n \"\ acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.025279850397404907\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.373015873015873,\n\ \ \"acc_stderr\": 0.04325506042017086,\n \"acc_norm\": 0.373015873015873,\n\ \ \"acc_norm_stderr\": 0.04325506042017086\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.6645161290322581,\n \"acc_stderr\": 0.026860206444724352,\n \"\ acc_norm\": 0.6645161290322581,\n \"acc_norm_stderr\": 0.026860206444724352\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.4630541871921182,\n \"acc_stderr\": 0.035083705204426656,\n \"\ acc_norm\": 0.4630541871921182,\n \"acc_norm_stderr\": 0.035083705204426656\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6606060606060606,\n \"acc_stderr\": 0.036974422050315967,\n\ \ \"acc_norm\": 0.6606060606060606,\n \"acc_norm_stderr\": 0.036974422050315967\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7373737373737373,\n \"acc_stderr\": 0.03135305009533086,\n \"\ acc_norm\": 0.7373737373737373,\n \"acc_norm_stderr\": 0.03135305009533086\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7564766839378239,\n \"acc_stderr\": 0.030975436386845436,\n\ \ \"acc_norm\": 0.7564766839378239,\n \"acc_norm_stderr\": 0.030975436386845436\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5615384615384615,\n \"acc_stderr\": 0.025158266016868578,\n\ \ \"acc_norm\": 0.5615384615384615,\n \"acc_norm_stderr\": 0.025158266016868578\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2962962962962963,\n \"acc_stderr\": 0.027840811495871916,\n \ \ \"acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.027840811495871916\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5882352941176471,\n \"acc_stderr\": 0.03196876989195778,\n \ \ \"acc_norm\": 0.5882352941176471,\n \"acc_norm_stderr\": 0.03196876989195778\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7834862385321101,\n \"acc_stderr\": 0.017658710594443128,\n \"\ acc_norm\": 0.7834862385321101,\n \"acc_norm_stderr\": 0.017658710594443128\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4537037037037037,\n \"acc_stderr\": 0.033953227263757976,\n \"\ acc_norm\": 0.4537037037037037,\n \"acc_norm_stderr\": 0.033953227263757976\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.6617647058823529,\n \"acc_stderr\": 0.03320574612945431,\n \"\ acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.03320574612945431\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7341772151898734,\n \"acc_stderr\": 0.028756799629658342,\n \ \ \"acc_norm\": 0.7341772151898734,\n \"acc_norm_stderr\": 0.028756799629658342\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6502242152466368,\n\ \ \"acc_stderr\": 0.03200736719484503,\n \"acc_norm\": 0.6502242152466368,\n\ \ \"acc_norm_stderr\": 0.03200736719484503\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6335877862595419,\n \"acc_stderr\": 0.04225875451969638,\n\ \ \"acc_norm\": 0.6335877862595419,\n \"acc_norm_stderr\": 0.04225875451969638\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302871,\n \"acc_norm\"\ : 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302871\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.043300437496507416,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.043300437496507416\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615623,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615623\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.6990291262135923,\n \"acc_stderr\": 0.04541609446503948,\n\ \ \"acc_norm\": 0.6990291262135923,\n \"acc_norm_stderr\": 0.04541609446503948\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8205128205128205,\n\ \ \"acc_stderr\": 0.025140935950335428,\n \"acc_norm\": 0.8205128205128205,\n\ \ \"acc_norm_stderr\": 0.025140935950335428\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.63,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.6756066411238825,\n\ \ \"acc_stderr\": 0.016740929047162696,\n \"acc_norm\": 0.6756066411238825,\n\ \ \"acc_norm_stderr\": 0.016740929047162696\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.661849710982659,\n \"acc_stderr\": 0.02546977014940017,\n\ \ \"acc_norm\": 0.661849710982659,\n \"acc_norm_stderr\": 0.02546977014940017\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2212290502793296,\n\ \ \"acc_stderr\": 0.01388216459888727,\n \"acc_norm\": 0.2212290502793296,\n\ \ \"acc_norm_stderr\": 0.01388216459888727\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6013071895424836,\n \"acc_stderr\": 0.02803609227389177,\n\ \ \"acc_norm\": 0.6013071895424836,\n \"acc_norm_stderr\": 0.02803609227389177\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6237942122186495,\n\ \ \"acc_stderr\": 0.02751392568354943,\n \"acc_norm\": 0.6237942122186495,\n\ \ \"acc_norm_stderr\": 0.02751392568354943\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6203703703703703,\n \"acc_stderr\": 0.027002521034516468,\n\ \ \"acc_norm\": 0.6203703703703703,\n \"acc_norm_stderr\": 0.027002521034516468\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4078014184397163,\n \"acc_stderr\": 0.02931601177634356,\n \ \ \"acc_norm\": 0.4078014184397163,\n \"acc_norm_stderr\": 0.02931601177634356\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.40808344198174706,\n\ \ \"acc_stderr\": 0.012552598958563662,\n \"acc_norm\": 0.40808344198174706,\n\ \ \"acc_norm_stderr\": 0.012552598958563662\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.44485294117647056,\n \"acc_stderr\": 0.03018753206032939,\n\ \ \"acc_norm\": 0.44485294117647056,\n \"acc_norm_stderr\": 0.03018753206032939\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5718954248366013,\n \"acc_stderr\": 0.0200176292142131,\n \ \ \"acc_norm\": 0.5718954248366013,\n \"acc_norm_stderr\": 0.0200176292142131\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.02950489645459595,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.02950489645459595\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.7412935323383084,\n\ \ \"acc_stderr\": 0.03096590312357303,\n \"acc_norm\": 0.7412935323383084,\n\ \ \"acc_norm_stderr\": 0.03096590312357303\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-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\": 0.6842105263157895,\n \"acc_stderr\": 0.035650796707083106,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.035650796707083106\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3011015911872705,\n\ \ \"mc1_stderr\": 0.01605899902610061,\n \"mc2\": 0.44887128521126124,\n\ \ \"mc2_stderr\": 0.015342799330160783\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7521704814522494,\n \"acc_stderr\": 0.012134386019865353\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.4040940106141016,\n \ \ \"acc_stderr\": 0.013516752972721717\n }\n}\n```" repo_url: https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|arc:challenge\|25_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-10T00-49-09.888984.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|gsm8k\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hellaswag\|10_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-10T00-49-09.888984.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-10T00-49-09.888984.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '/details_harness\|winogrande\|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-10T00-49-09.888984.parquet' - config_name: results data_files: - split: 2024_03_10T00_49_09.888984 path: - results_2024-03-10T00-49-09.888984.parquet - split: latest path: - results_2024-03-10T00-49-09.888984.parquet --- # Dataset Card for Evaluation run of g-ronimo/phi-2-OpenHermes-2.5-v2 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [g-ronimo/phi-2-OpenHermes-2.5-v2](https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2) 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_g-ronimo__phi-2-OpenHermes-2.5-v2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-10T00:49:09.888984](https://huggingface.co/datasets/open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2/blob/main/results_2024-03-10T00-49-09.888984.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": 0.564734458241999, "acc_stderr": 0.03391431521091429, "acc_norm": 0.5676857564160381, "acc_norm_stderr": 0.03461774832252384, "mc1": 0.3011015911872705, "mc1_stderr": 0.01605899902610061, "mc2": 0.44887128521126124, "mc2_stderr": 0.015342799330160783 }, "harness\|arc:challenge\|25": { "acc": 0.5699658703071673, "acc_stderr": 0.01446763155913799, "acc_norm": 0.5844709897610921, "acc_norm_stderr": 0.014401366641216388 }, "harness\|hellaswag\|10": { "acc": 0.5592511451902011, "acc_stderr": 0.004954622308738996, "acc_norm": 0.7456681935869349, "acc_norm_stderr": 0.004345949382382379 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.48148148148148145, "acc_stderr": 0.043163785995113245, "acc_norm": 0.48148148148148145, "acc_norm_stderr": 0.043163785995113245 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5657894736842105, "acc_stderr": 0.0403356566784832, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.0403356566784832 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5735849056603773, "acc_stderr": 0.03043779434298305, "acc_norm": 0.5735849056603773, "acc_norm_stderr": 0.03043779434298305 }, "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": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5491329479768786, "acc_stderr": 0.03794012674697031, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.03794012674697031 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006717, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006717 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5276595744680851, "acc_stderr": 0.03263597118409769, "acc_norm": 0.5276595744680851, "acc_norm_stderr": 0.03263597118409769 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.39473684210526316, "acc_stderr": 0.045981880578165414, "acc_norm": 0.39473684210526316, "acc_norm_stderr": 0.045981880578165414 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5103448275862069, "acc_stderr": 0.04165774775728763, "acc_norm": 0.5103448275862069, "acc_norm_stderr": 0.04165774775728763 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.40476190476190477, "acc_stderr": 0.025279850397404907, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.025279850397404907 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.373015873015873, "acc_stderr": 0.04325506042017086, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.04325506042017086 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6645161290322581, "acc_stderr": 0.026860206444724352, "acc_norm": 0.6645161290322581, "acc_norm_stderr": 0.026860206444724352 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4630541871921182, "acc_stderr": 0.035083705204426656, "acc_norm": 0.4630541871921182, "acc_norm_stderr": 0.035083705204426656 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6606060606060606, "acc_stderr": 0.036974422050315967, "acc_norm": 0.6606060606060606, "acc_norm_stderr": 0.036974422050315967 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7373737373737373, "acc_stderr": 0.03135305009533086, "acc_norm": 0.7373737373737373, "acc_norm_stderr": 0.03135305009533086 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7564766839378239, "acc_stderr": 0.030975436386845436, "acc_norm": 0.7564766839378239, "acc_norm_stderr": 0.030975436386845436 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5615384615384615, "acc_stderr": 0.025158266016868578, "acc_norm": 0.5615384615384615, "acc_norm_stderr": 0.025158266016868578 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2962962962962963, "acc_stderr": 0.027840811495871916, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.027840811495871916 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5882352941176471, "acc_stderr": 0.03196876989195778, "acc_norm": 0.5882352941176471, "acc_norm_stderr": 0.03196876989195778 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7834862385321101, "acc_stderr": 0.017658710594443128, "acc_norm": 0.7834862385321101, "acc_norm_stderr": 0.017658710594443128 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4537037037037037, "acc_stderr": 0.033953227263757976, "acc_norm": 0.4537037037037037, "acc_norm_stderr": 0.033953227263757976 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.6617647058823529, "acc_stderr": 0.03320574612945431, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.03320574612945431 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7341772151898734, "acc_stderr": 0.028756799629658342, "acc_norm": 0.7341772151898734, "acc_norm_stderr": 0.028756799629658342 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6502242152466368, "acc_stderr": 0.03200736719484503, "acc_norm": 0.6502242152466368, "acc_norm_stderr": 0.03200736719484503 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6335877862595419, "acc_stderr": 0.04225875451969638, "acc_norm": 0.6335877862595419, "acc_norm_stderr": 0.04225875451969638 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.743801652892562, "acc_stderr": 0.03984979653302871, "acc_norm": 0.743801652892562, "acc_norm_stderr": 0.03984979653302871 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7222222222222222, "acc_stderr": 0.043300437496507416, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.043300437496507416 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615623, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615623 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness\|hendrycksTest-management\|5": { "acc": 0.6990291262135923, "acc_stderr": 0.04541609446503948, "acc_norm": 0.6990291262135923, "acc_norm_stderr": 0.04541609446503948 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8205128205128205, "acc_stderr": 0.025140935950335428, "acc_norm": 0.8205128205128205, "acc_norm_stderr": 0.025140935950335428 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.6756066411238825, "acc_stderr": 0.016740929047162696, "acc_norm": 0.6756066411238825, "acc_norm_stderr": 0.016740929047162696 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.661849710982659, "acc_stderr": 0.02546977014940017, "acc_norm": 0.661849710982659, "acc_norm_stderr": 0.02546977014940017 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2212290502793296, "acc_stderr": 0.01388216459888727, "acc_norm": 0.2212290502793296, "acc_norm_stderr": 0.01388216459888727 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6013071895424836, "acc_stderr": 0.02803609227389177, "acc_norm": 0.6013071895424836, "acc_norm_stderr": 0.02803609227389177 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6237942122186495, "acc_stderr": 0.02751392568354943, "acc_norm": 0.6237942122186495, "acc_norm_stderr": 0.02751392568354943 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6203703703703703, "acc_stderr": 0.027002521034516468, "acc_norm": 0.6203703703703703, "acc_norm_stderr": 0.027002521034516468 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4078014184397163, "acc_stderr": 0.02931601177634356, "acc_norm": 0.4078014184397163, "acc_norm_stderr": 0.02931601177634356 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.40808344198174706, "acc_stderr": 0.012552598958563662, "acc_norm": 0.40808344198174706, "acc_norm_stderr": 0.012552598958563662 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.44485294117647056, "acc_stderr": 0.03018753206032939, "acc_norm": 0.44485294117647056, "acc_norm_stderr": 0.03018753206032939 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5718954248366013, "acc_stderr": 0.0200176292142131, "acc_norm": 0.5718954248366013, "acc_norm_stderr": 0.0200176292142131 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6938775510204082, "acc_stderr": 0.02950489645459595, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.02950489645459595 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.7412935323383084, "acc_stderr": 0.03096590312357303, "acc_norm": 0.7412935323383084, "acc_norm_stderr": 0.03096590312357303 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "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": 0.6842105263157895, "acc_stderr": 0.035650796707083106, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.035650796707083106 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3011015911872705, "mc1_stderr": 0.01605899902610061, "mc2": 0.44887128521126124, "mc2_stderr": 0.015342799330160783 }, "harness\|winogrande\|5": { "acc": 0.7521704814522494, "acc_stderr": 0.012134386019865353 }, "harness\|gsm8k\|5": { "acc": 0.4040940106141016, "acc_stderr": 0.013516752972721717 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address 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open-llm-leaderboard/details_Technoculture__MT7Bi-sft	--- pretty_name: Evaluation run of Technoculture/MT7Bi-sft dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Technoculture/MT7Bi-sft](https://huggingface.co/Technoculture/MT7Bi-sft) 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_Technoculture__MT7Bi-sft\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-01T14:25:40.116952](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MT7Bi-sft/blob/main/results_2024-02-01T14-25-40.116952.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\": 0.4105658357592459,\n\ \ \"acc_stderr\": 0.03434113134801399,\n \"acc_norm\": 0.416672739687421,\n\ \ \"acc_norm_stderr\": 0.03527569703844115,\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608767,\n \"mc2\": 0.4460516469060258,\n\ \ \"mc2_stderr\": 0.01603355318388596\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.3796928327645051,\n \"acc_stderr\": 0.014182119866974874,\n\ \ \"acc_norm\": 0.4180887372013652,\n \"acc_norm_stderr\": 0.014413988396996074\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4629555865365465,\n\ \ \"acc_stderr\": 0.004976067726432563,\n \"acc_norm\": 0.5683130850428202,\n\ \ \"acc_norm_stderr\": 0.004942990623131126\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.5185185185185185,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.5185185185185185,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.40131578947368424,\n \"acc_stderr\": 0.039889037033362836,\n\ \ \"acc_norm\": 0.40131578947368424,\n \"acc_norm_stderr\": 0.039889037033362836\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|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-clinical_knowledge\|5\"\ : {\n \"acc\": 0.5018867924528302,\n \"acc_stderr\": 0.03077265364207565,\n\ \ \"acc_norm\": 0.5018867924528302,\n \"acc_norm_stderr\": 0.03077265364207565\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.4236111111111111,\n\ \ \"acc_stderr\": 0.04132125019723369,\n \"acc_norm\": 0.4236111111111111,\n\ \ \"acc_norm_stderr\": 0.04132125019723369\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.41040462427745666,\n\ \ \"acc_stderr\": 0.03750757044895537,\n \"acc_norm\": 0.41040462427745666,\n\ \ \"acc_norm_stderr\": 0.03750757044895537\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.29411764705882354,\n \"acc_stderr\": 0.04533838195929774,\n\ \ \"acc_norm\": 0.29411764705882354,\n \"acc_norm_stderr\": 0.04533838195929774\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.3276595744680851,\n \"acc_stderr\": 0.030683020843231004,\n\ \ \"acc_norm\": 0.3276595744680851,\n \"acc_norm_stderr\": 0.030683020843231004\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.043036840335373146,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.043036840335373146\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.45517241379310347,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.45517241379310347,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2751322751322751,\n \"acc_stderr\": 0.02300008685906864,\n \"\ acc_norm\": 0.2751322751322751,\n \"acc_norm_stderr\": 0.02300008685906864\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.25396825396825395,\n\ \ \"acc_stderr\": 0.03893259610604674,\n \"acc_norm\": 0.25396825396825395,\n\ \ \"acc_norm_stderr\": 0.03893259610604674\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.4935483870967742,\n \"acc_stderr\": 0.02844163823354051,\n \"\ acc_norm\": 0.4935483870967742,\n \"acc_norm_stderr\": 0.02844163823354051\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.26108374384236455,\n \"acc_stderr\": 0.0309037969521145,\n \"\ acc_norm\": 0.26108374384236455,\n \"acc_norm_stderr\": 0.0309037969521145\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \"acc_norm\"\ : 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.47878787878787876,\n \"acc_stderr\": 0.039008289137373,\n\ \ \"acc_norm\": 0.47878787878787876,\n \"acc_norm_stderr\": 0.039008289137373\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.4797979797979798,\n \"acc_stderr\": 0.03559443565563921,\n \"\ acc_norm\": 0.4797979797979798,\n \"acc_norm_stderr\": 0.03559443565563921\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.47668393782383417,\n \"acc_stderr\": 0.03604513672442206,\n\ \ \"acc_norm\": 0.47668393782383417,\n \"acc_norm_stderr\": 0.03604513672442206\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.3435897435897436,\n \"acc_stderr\": 0.024078696580635484,\n\ \ \"acc_norm\": 0.3435897435897436,\n \"acc_norm_stderr\": 0.024078696580635484\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340496,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340496\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.3697478991596639,\n \"acc_stderr\": 0.031357095996135904,\n\ \ \"acc_norm\": 0.3697478991596639,\n \"acc_norm_stderr\": 0.031357095996135904\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.037579499229433426,\n \"\ acc_norm\": 0.304635761589404,\n \"acc_norm_stderr\": 0.037579499229433426\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5522935779816514,\n \"acc_stderr\": 0.021319754962425462,\n \"\ acc_norm\": 0.5522935779816514,\n \"acc_norm_stderr\": 0.021319754962425462\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.35648148148148145,\n \"acc_stderr\": 0.032664783315272714,\n \"\ acc_norm\": 0.35648148148148145,\n \"acc_norm_stderr\": 0.032664783315272714\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.37745098039215685,\n \"acc_stderr\": 0.03402272044340703,\n \"\ acc_norm\": 0.37745098039215685,\n \"acc_norm_stderr\": 0.03402272044340703\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.5780590717299579,\n \"acc_stderr\": 0.032148146302403695,\n \ \ \"acc_norm\": 0.5780590717299579,\n \"acc_norm_stderr\": 0.032148146302403695\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.47533632286995514,\n\ \ \"acc_stderr\": 0.033516951676526276,\n \"acc_norm\": 0.47533632286995514,\n\ \ \"acc_norm_stderr\": 0.033516951676526276\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.5343511450381679,\n \"acc_stderr\": 0.043749285605997376,\n\ \ \"acc_norm\": 0.5343511450381679,\n \"acc_norm_stderr\": 0.043749285605997376\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.5867768595041323,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.5867768595041323,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.5370370370370371,\n\ \ \"acc_stderr\": 0.04820403072760628,\n \"acc_norm\": 0.5370370370370371,\n\ \ \"acc_norm_stderr\": 0.04820403072760628\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.4294478527607362,\n \"acc_stderr\": 0.038890666191127216,\n\ \ \"acc_norm\": 0.4294478527607362,\n \"acc_norm_stderr\": 0.038890666191127216\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.038946411200447915,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.038946411200447915\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.5048543689320388,\n \"acc_stderr\": 0.04950504382128921,\n\ \ \"acc_norm\": 0.5048543689320388,\n \"acc_norm_stderr\": 0.04950504382128921\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.6025641025641025,\n\ \ \"acc_stderr\": 0.03205953453789293,\n \"acc_norm\": 0.6025641025641025,\n\ \ \"acc_norm_stderr\": 0.03205953453789293\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.4661558109833972,\n\ \ \"acc_stderr\": 0.017838956009136805,\n \"acc_norm\": 0.4661558109833972,\n\ \ \"acc_norm_stderr\": 0.017838956009136805\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.44508670520231214,\n \"acc_stderr\": 0.02675625512966377,\n\ \ \"acc_norm\": 0.44508670520231214,\n \"acc_norm_stderr\": 0.02675625512966377\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2335195530726257,\n\ \ \"acc_stderr\": 0.014149575348976259,\n \"acc_norm\": 0.2335195530726257,\n\ \ \"acc_norm_stderr\": 0.014149575348976259\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.4869281045751634,\n \"acc_stderr\": 0.028620130800700246,\n\ \ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.028620130800700246\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.4437299035369775,\n\ \ \"acc_stderr\": 0.028217683556652308,\n \"acc_norm\": 0.4437299035369775,\n\ \ \"acc_norm_stderr\": 0.028217683556652308\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.42901234567901236,\n \"acc_stderr\": 0.027538925613470863,\n\ \ \"acc_norm\": 0.42901234567901236,\n \"acc_norm_stderr\": 0.027538925613470863\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.33687943262411346,\n \"acc_stderr\": 0.028195534873966734,\n \ \ \"acc_norm\": 0.33687943262411346,\n \"acc_norm_stderr\": 0.028195534873966734\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3057366362451108,\n\ \ \"acc_stderr\": 0.011766973847072914,\n \"acc_norm\": 0.3057366362451108,\n\ \ \"acc_norm_stderr\": 0.011766973847072914\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4227941176470588,\n \"acc_stderr\": 0.030008562845003486,\n\ \ \"acc_norm\": 0.4227941176470588,\n \"acc_norm_stderr\": 0.030008562845003486\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.39705882352941174,\n \"acc_stderr\": 0.01979448890002411,\n \ \ \"acc_norm\": 0.39705882352941174,\n \"acc_norm_stderr\": 0.01979448890002411\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.43636363636363634,\n\ \ \"acc_stderr\": 0.04750185058907297,\n \"acc_norm\": 0.43636363636363634,\n\ \ \"acc_norm_stderr\": 0.04750185058907297\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.49795918367346936,\n \"acc_stderr\": 0.0320089533497105,\n\ \ \"acc_norm\": 0.49795918367346936,\n \"acc_norm_stderr\": 0.0320089533497105\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.5472636815920398,\n\ \ \"acc_stderr\": 0.03519702717576915,\n \"acc_norm\": 0.5472636815920398,\n\ \ \"acc_norm_stderr\": 0.03519702717576915\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562427,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562427\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.3855421686746988,\n\ \ \"acc_stderr\": 0.037891344246115496,\n \"acc_norm\": 0.3855421686746988,\n\ \ \"acc_norm_stderr\": 0.037891344246115496\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.49122807017543857,\n \"acc_stderr\": 0.03834234744164993,\n\ \ \"acc_norm\": 0.49122807017543857,\n \"acc_norm_stderr\": 0.03834234744164993\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608767,\n \"mc2\": 0.4460516469060258,\n\ \ \"mc2_stderr\": 0.01603355318388596\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6045777426992897,\n \"acc_stderr\": 0.013741678387545352\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/Technoculture/MT7Bi-sft 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_01T14_25_40.116952 path: - '/details_harness\|arc:challenge\|25_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-01T14-25-40.116952.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|gsm8k\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hellaswag\|10_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-01T14-25-40.116952.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-01T14-25-40.116952.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '/details_harness\|winogrande\|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-01T14-25-40.116952.parquet' - config_name: results data_files: - split: 2024_02_01T14_25_40.116952 path: - results_2024-02-01T14-25-40.116952.parquet - split: latest path: - results_2024-02-01T14-25-40.116952.parquet --- # Dataset Card for Evaluation run of Technoculture/MT7Bi-sft <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Technoculture/MT7Bi-sft](https://huggingface.co/Technoculture/MT7Bi-sft) 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_Technoculture__MT7Bi-sft", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-01T14:25:40.116952](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MT7Bi-sft/blob/main/results_2024-02-01T14-25-40.116952.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": 0.4105658357592459, "acc_stderr": 0.03434113134801399, "acc_norm": 0.416672739687421, "acc_norm_stderr": 0.03527569703844115, "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608767, "mc2": 0.4460516469060258, "mc2_stderr": 0.01603355318388596 }, "harness\|arc:challenge\|25": { "acc": 0.3796928327645051, "acc_stderr": 0.014182119866974874, "acc_norm": 0.4180887372013652, "acc_norm_stderr": 0.014413988396996074 }, "harness\|hellaswag\|10": { "acc": 0.4629555865365465, "acc_stderr": 0.004976067726432563, "acc_norm": 0.5683130850428202, "acc_norm_stderr": 0.004942990623131126 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5185185185185185, "acc_stderr": 0.043163785995113245, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.043163785995113245 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.40131578947368424, "acc_stderr": 0.039889037033362836, "acc_norm": 0.40131578947368424, "acc_norm_stderr": 0.039889037033362836 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.5018867924528302, "acc_stderr": 0.03077265364207565, "acc_norm": 0.5018867924528302, "acc_norm_stderr": 0.03077265364207565 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.4236111111111111, "acc_stderr": 0.04132125019723369, "acc_norm": 0.4236111111111111, "acc_norm_stderr": 0.04132125019723369 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.41040462427745666, "acc_stderr": 0.03750757044895537, "acc_norm": 0.41040462427745666, "acc_norm_stderr": 0.03750757044895537 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929774, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929774 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3276595744680851, "acc_stderr": 0.030683020843231004, "acc_norm": 0.3276595744680851, "acc_norm_stderr": 0.030683020843231004 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2982456140350877, "acc_stderr": 0.043036840335373146, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.043036840335373146 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2751322751322751, "acc_stderr": 0.02300008685906864, "acc_norm": 0.2751322751322751, "acc_norm_stderr": 0.02300008685906864 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.4935483870967742, "acc_stderr": 0.02844163823354051, "acc_norm": 0.4935483870967742, "acc_norm_stderr": 0.02844163823354051 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.26108374384236455, "acc_stderr": 0.0309037969521145, "acc_norm": 0.26108374384236455, "acc_norm_stderr": 0.0309037969521145 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.47878787878787876, "acc_stderr": 0.039008289137373, "acc_norm": 0.47878787878787876, "acc_norm_stderr": 0.039008289137373 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.4797979797979798, "acc_stderr": 0.03559443565563921, "acc_norm": 0.4797979797979798, "acc_norm_stderr": 0.03559443565563921 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.47668393782383417, "acc_stderr": 0.03604513672442206, "acc_norm": 0.47668393782383417, "acc_norm_stderr": 0.03604513672442206 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.3435897435897436, "acc_stderr": 0.024078696580635484, "acc_norm": 0.3435897435897436, "acc_norm_stderr": 0.024078696580635484 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340496, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340496 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.3697478991596639, "acc_stderr": 0.031357095996135904, "acc_norm": 0.3697478991596639, "acc_norm_stderr": 0.031357095996135904 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.304635761589404, "acc_stderr": 0.037579499229433426, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.037579499229433426 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5522935779816514, "acc_stderr": 0.021319754962425462, "acc_norm": 0.5522935779816514, "acc_norm_stderr": 0.021319754962425462 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.35648148148148145, "acc_stderr": 0.032664783315272714, "acc_norm": 0.35648148148148145, "acc_norm_stderr": 0.032664783315272714 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.37745098039215685, "acc_stderr": 0.03402272044340703, "acc_norm": 0.37745098039215685, "acc_norm_stderr": 0.03402272044340703 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.5780590717299579, "acc_stderr": 0.032148146302403695, "acc_norm": 0.5780590717299579, "acc_norm_stderr": 0.032148146302403695 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.47533632286995514, "acc_stderr": 0.033516951676526276, "acc_norm": 0.47533632286995514, "acc_norm_stderr": 0.033516951676526276 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.5343511450381679, "acc_stderr": 0.043749285605997376, "acc_norm": 0.5343511450381679, "acc_norm_stderr": 0.043749285605997376 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.5867768595041323, "acc_stderr": 0.04495087843548408, "acc_norm": 0.5867768595041323, "acc_norm_stderr": 0.04495087843548408 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.5370370370370371, "acc_stderr": 0.04820403072760628, "acc_norm": 0.5370370370370371, "acc_norm_stderr": 0.04820403072760628 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.4294478527607362, "acc_stderr": 0.038890666191127216, "acc_norm": 0.4294478527607362, "acc_norm_stderr": 0.038890666191127216 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.21428571428571427, "acc_stderr": 0.038946411200447915, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.038946411200447915 }, "harness\|hendrycksTest-management\|5": { "acc": 0.5048543689320388, "acc_stderr": 0.04950504382128921, "acc_norm": 0.5048543689320388, "acc_norm_stderr": 0.04950504382128921 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.6025641025641025, "acc_stderr": 0.03205953453789293, "acc_norm": 0.6025641025641025, "acc_norm_stderr": 0.03205953453789293 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.4661558109833972, "acc_stderr": 0.017838956009136805, "acc_norm": 0.4661558109833972, "acc_norm_stderr": 0.017838956009136805 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.44508670520231214, "acc_stderr": 0.02675625512966377, "acc_norm": 0.44508670520231214, "acc_norm_stderr": 0.02675625512966377 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2335195530726257, "acc_stderr": 0.014149575348976259, "acc_norm": 0.2335195530726257, "acc_norm_stderr": 0.014149575348976259 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.4869281045751634, "acc_stderr": 0.028620130800700246, "acc_norm": 0.4869281045751634, "acc_norm_stderr": 0.028620130800700246 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.4437299035369775, "acc_stderr": 0.028217683556652308, "acc_norm": 0.4437299035369775, "acc_norm_stderr": 0.028217683556652308 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.42901234567901236, "acc_stderr": 0.027538925613470863, "acc_norm": 0.42901234567901236, "acc_norm_stderr": 0.027538925613470863 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.33687943262411346, "acc_stderr": 0.028195534873966734, "acc_norm": 0.33687943262411346, "acc_norm_stderr": 0.028195534873966734 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3057366362451108, "acc_stderr": 0.011766973847072914, "acc_norm": 0.3057366362451108, "acc_norm_stderr": 0.011766973847072914 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4227941176470588, "acc_stderr": 0.030008562845003486, "acc_norm": 0.4227941176470588, "acc_norm_stderr": 0.030008562845003486 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.39705882352941174, "acc_stderr": 0.01979448890002411, "acc_norm": 0.39705882352941174, "acc_norm_stderr": 0.01979448890002411 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.43636363636363634, "acc_stderr": 0.04750185058907297, "acc_norm": 0.43636363636363634, "acc_norm_stderr": 0.04750185058907297 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.49795918367346936, "acc_stderr": 0.0320089533497105, "acc_norm": 0.49795918367346936, "acc_norm_stderr": 0.0320089533497105 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.5472636815920398, "acc_stderr": 0.03519702717576915, "acc_norm": 0.5472636815920398, "acc_norm_stderr": 0.03519702717576915 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.57, "acc_stderr": 0.04975698519562427, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562427 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.3855421686746988, "acc_stderr": 0.037891344246115496, "acc_norm": 0.3855421686746988, "acc_norm_stderr": 0.037891344246115496 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.49122807017543857, "acc_stderr": 0.03834234744164993, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.03834234744164993 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608767, "mc2": 0.4460516469060258, "mc2_stderr": 0.01603355318388596 }, "harness\|winogrande\|5": { "acc": 0.6045777426992897, "acc_stderr": 0.013741678387545352 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section 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]

passionMan/usda_tokenized_source

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string - name: label dtype: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 1314644 num_examples: 5628 - name: test num_bytes: 437798 num_examples: 1876 download_size: 434891 dataset_size: 1752442 --- # Dataset Card for "usda_tokenized_source" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

bigfish87/test

--- license: openrail ---

anan-2024/twitter_dataset_1712976471

--- 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: 276649 num_examples: 759 download_size: 151493 dataset_size: 276649 configs: - config_name: default data_files: - split: train path: data/train-* ---

liuyanchen1015/MULTI_VALUE_stsb_invariant_tag_amnt

--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: score dtype: float64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: dev num_bytes: 162 num_examples: 1 - name: test num_bytes: 192 num_examples: 1 download_size: 5842 dataset_size: 354 --- # Dataset Card for "MULTI_VALUE_stsb_invariant_tag_amnt" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

RevEng-23-24/Dataset48K

--- dataset_info: features: - name: assembly dtype: string - name: c_source_code dtype: string splits: - name: train num_bytes: 54615105 num_examples: 30657 - name: val num_bytes: 14102616 num_examples: 7665 - name: test num_bytes: 17112427 num_examples: 9581 download_size: 24803662 dataset_size: 85830148 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* - split: test path: data/test-* ---

ronniewy/chinese_nli

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

kanxue/muep_cot_checkpoint

--- license: apache-2.0 ---

Circularmachines/batch_indexing_machine_224x224_images

--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 1200580554.73 num_examples: 72510 download_size: 1200450555 dataset_size: 1200580554.73 --- # Dataset Card for "batch_indexing_machine_224x224_images" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

sethapun/imdb_misspelled_30

--- dataset_info: features: - name: text dtype: string - name: label dtype: class_label: names: '0': neg '1': pos - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 33632801 num_examples: 25000 - name: validation num_bytes: 32851081 num_examples: 25000 download_size: 47443707 dataset_size: 66483882 --- # Dataset Card for "imdb_misspelled_30" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Cynaptics/Test2Sql

--- license: apache-2.0 dataset_info: features: - name: schema dtype: string - name: query dtype: string - name: question dtype: string splits: - name: small_validation num_bytes: 1171681 num_examples: 1000 - name: train num_bytes: 572158109 num_examples: 489956 - name: small_train num_bytes: 11702337 num_examples: 10000 - name: spider_test num_bytes: 759534287 num_examples: 4840 - name: sql_eval_test num_bytes: 18048597 num_examples: 3509 download_size: 150973260 dataset_size: 1362615011 configs: - config_name: default data_files: - split: small_validation path: data/small_validation-* - split: train path: data/train-* - split: small_train path: data/small_train-* - split: spider_test path: data/spider_test-* - split: sql_eval_test path: data/sql_eval_test-* ---

Rounak28/bengaliAI-preprocessed-whisper-medium-0-50000

--- dataset_info: features: - name: id dtype: string - name: sentence dtype: string - name: split dtype: string - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 48065858980 num_examples: 50000 download_size: 6861840289 dataset_size: 48065858980 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "bengaliAI-preprocessed-whisper-medium-0-50000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Falcon96/cidmoreira

--- license: openrail ---

open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B

--- pretty_name: Evaluation run of feeltheAGI/Maverick-Math-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [feeltheAGI/Maverick-Math-7B](https://huggingface.co/feeltheAGI/Maverick-Math-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_feeltheAGI__Maverick-Math-7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-14T10:55:45.107983](https://huggingface.co/datasets/open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B/blob/main/results_2024-03-14T10-55-45.107983.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\": 0.6296804564180761,\n\ \ \"acc_stderr\": 0.03245152465151836,\n \"acc_norm\": 0.6301031619229365,\n\ \ \"acc_norm_stderr\": 0.033115363797357654,\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769625,\n \"mc2\": 0.5596682871042189,\n\ \ \"mc2_stderr\": 0.015333014253402569\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6220136518771331,\n \"acc_stderr\": 0.0141696645203031,\n\ \ \"acc_norm\": 0.6527303754266212,\n \"acc_norm_stderr\": 0.013913034529620455\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6515634335789683,\n\ \ \"acc_stderr\": 0.004755013243022125,\n \"acc_norm\": 0.8454491137223661,\n\ \ \"acc_norm_stderr\": 0.0036073726062950976\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.562962962962963,\n\ \ \"acc_stderr\": 0.04284958639753401,\n \"acc_norm\": 0.562962962962963,\n\ \ \"acc_norm_stderr\": 0.04284958639753401\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.690566037735849,\n \"acc_stderr\": 0.028450154794118637,\n\ \ \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118637\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.03745554791462456,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.03745554791462456\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\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.35294117647058826,\n \"acc_stderr\": 0.04755129616062946,\n\ \ \"acc_norm\": 0.35294117647058826,\n \"acc_norm_stderr\": 0.04755129616062946\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.42105263157894735,\n\ \ \"acc_stderr\": 0.046446020912223177,\n \"acc_norm\": 0.42105263157894735,\n\ \ \"acc_norm_stderr\": 0.046446020912223177\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42857142857142855,\n \"acc_stderr\": 0.025487187147859375,\n \"\ acc_norm\": 0.42857142857142855,\n \"acc_norm_stderr\": 0.025487187147859375\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.42063492063492064,\n\ \ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\ \ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7483870967741936,\n\ \ \"acc_stderr\": 0.024685979286239963,\n \"acc_norm\": 0.7483870967741936,\n\ \ \"acc_norm_stderr\": 0.024685979286239963\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\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\ : 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7878787878787878,\n \"acc_stderr\": 0.031922715695483016,\n\ \ \"acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.031922715695483016\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7828282828282829,\n \"acc_stderr\": 0.02937661648494563,\n \"\ acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.02937661648494563\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9067357512953368,\n \"acc_stderr\": 0.02098685459328972,\n\ \ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.02098685459328972\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6410256410256411,\n \"acc_stderr\": 0.024321738484602357,\n\ \ \"acc_norm\": 0.6410256410256411,\n \"acc_norm_stderr\": 0.024321738484602357\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3,\n \"acc_stderr\": 0.02794045713622841,\n \"acc_norm\"\ : 0.3,\n \"acc_norm_stderr\": 0.02794045713622841\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\ : {\n \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.03077805742293167,\n\ \ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.03077805742293167\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8293577981651377,\n \"acc_stderr\": 0.016129271025099864,\n \"\ acc_norm\": 0.8293577981651377,\n \"acc_norm_stderr\": 0.016129271025099864\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.8088235294117647,\n\ \ \"acc_stderr\": 0.027599174300640763,\n \"acc_norm\": 0.8088235294117647,\n\ \ \"acc_norm_stderr\": 0.027599174300640763\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.7932489451476793,\n \"acc_stderr\": 0.0263616516683891,\n\ \ \"acc_norm\": 0.7932489451476793,\n \"acc_norm_stderr\": 0.0263616516683891\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7557251908396947,\n \"acc_stderr\": 0.03768335959728744,\n\ \ \"acc_norm\": 0.7557251908396947,\n \"acc_norm_stderr\": 0.03768335959728744\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228733,\n \"\ acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228733\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615624,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615624\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5178571428571429,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.5178571428571429,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.043546310772605956,\n\ \ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.043546310772605956\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.021586494001281382,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.021586494001281382\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8212005108556832,\n\ \ \"acc_stderr\": 0.013702643715368985,\n \"acc_norm\": 0.8212005108556832,\n\ \ \"acc_norm_stderr\": 0.013702643715368985\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6878612716763006,\n \"acc_stderr\": 0.02494679222527231,\n\ \ \"acc_norm\": 0.6878612716763006,\n \"acc_norm_stderr\": 0.02494679222527231\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.35083798882681566,\n\ \ \"acc_stderr\": 0.01596103667523096,\n \"acc_norm\": 0.35083798882681566,\n\ \ \"acc_norm_stderr\": 0.01596103667523096\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6895424836601307,\n \"acc_stderr\": 0.026493033225145898,\n\ \ \"acc_norm\": 0.6895424836601307,\n \"acc_norm_stderr\": 0.026493033225145898\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7202572347266881,\n\ \ \"acc_stderr\": 0.025494259350694912,\n \"acc_norm\": 0.7202572347266881,\n\ \ \"acc_norm_stderr\": 0.025494259350694912\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7037037037037037,\n \"acc_stderr\": 0.02540719779889016,\n\ \ \"acc_norm\": 0.7037037037037037,\n \"acc_norm_stderr\": 0.02540719779889016\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303062,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303062\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4602346805736636,\n\ \ \"acc_stderr\": 0.012729785386598559,\n \"acc_norm\": 0.4602346805736636,\n\ \ \"acc_norm_stderr\": 0.012729785386598559\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6433823529411765,\n \"acc_stderr\": 0.029097209568411952,\n\ \ \"acc_norm\": 0.6433823529411765,\n \"acc_norm_stderr\": 0.029097209568411952\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6552287581699346,\n \"acc_stderr\": 0.019228322018696644,\n \ \ \"acc_norm\": 0.6552287581699346,\n \"acc_norm_stderr\": 0.019228322018696644\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\": 0.6979591836734694,\n \"acc_stderr\": 0.0293936093198798,\n\ \ \"acc_norm\": 0.6979591836734694,\n \"acc_norm_stderr\": 0.0293936093198798\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.835820895522388,\n\ \ \"acc_stderr\": 0.02619392354445412,\n \"acc_norm\": 0.835820895522388,\n\ \ \"acc_norm_stderr\": 0.02619392354445412\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5301204819277109,\n\ \ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\ \ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7894736842105263,\n \"acc_stderr\": 0.03126781714663179,\n\ \ \"acc_norm\": 0.7894736842105263,\n \"acc_norm_stderr\": 0.03126781714663179\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.39167686658506734,\n\ \ \"mc1_stderr\": 0.017087795881769625,\n \"mc2\": 0.5596682871042189,\n\ \ \"mc2_stderr\": 0.015333014253402569\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7971586424625099,\n \"acc_stderr\": 0.011301439925936645\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6618650492797574,\n \ \ \"acc_stderr\": 0.013030829145172208\n }\n}\n```" repo_url: https://huggingface.co/feeltheAGI/Maverick-Math-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_03_14T10_55_45.107983 path: - '**/details_harness|arc:challenge|25_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-14T10-55-45.107983.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|gsm8k|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hellaswag|10_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-14T10-55-45.107983.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-management|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-14T10-55-45.107983.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|truthfulqa:mc|0_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-14T10-55-45.107983.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_14T10_55_45.107983 path: - '**/details_harness|winogrande|5_2024-03-14T10-55-45.107983.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-14T10-55-45.107983.parquet' - config_name: results data_files: - split: 2024_03_14T10_55_45.107983 path: - results_2024-03-14T10-55-45.107983.parquet - split: latest path: - results_2024-03-14T10-55-45.107983.parquet --- # Dataset Card for Evaluation run of feeltheAGI/Maverick-Math-7B  Dataset automatically created during the evaluation run of model [feeltheAGI/Maverick-Math-7B](https://huggingface.co/feeltheAGI/Maverick-Math-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_feeltheAGI__Maverick-Math-7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-14T10:55:45.107983](https://huggingface.co/datasets/open-llm-leaderboard/details_feeltheAGI__Maverick-Math-7B/blob/main/results_2024-03-14T10-55-45.107983.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": 0.6296804564180761, "acc_stderr": 0.03245152465151836, "acc_norm": 0.6301031619229365, "acc_norm_stderr": 0.033115363797357654, "mc1": 0.39167686658506734, "mc1_stderr": 0.017087795881769625, "mc2": 0.5596682871042189, "mc2_stderr": 0.015333014253402569 }, "harness|arc:challenge|25": { "acc": 0.6220136518771331, "acc_stderr": 0.0141696645203031, "acc_norm": 0.6527303754266212, "acc_norm_stderr": 0.013913034529620455 }, "harness|hellaswag|10": { "acc": 0.6515634335789683, "acc_stderr": 0.004755013243022125, "acc_norm": 0.8454491137223661, "acc_norm_stderr": 0.0036073726062950976 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.690566037735849, "acc_stderr": 0.028450154794118637, "acc_norm": 0.690566037735849, "acc_norm_stderr": 0.028450154794118637 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03745554791462456, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03745554791462456 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.04755129616062946, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.04755129616062946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5531914893617021, "acc_stderr": 0.0325005368436584, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.0325005368436584 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.42105263157894735, "acc_stderr": 0.046446020912223177, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.046446020912223177 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42857142857142855, "acc_stderr": 0.025487187147859375, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.025487187147859375 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7483870967741936, "acc_stderr": 0.024685979286239963, "acc_norm": 0.7483870967741936, "acc_norm_stderr": 0.024685979286239963 }, "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": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7878787878787878, "acc_stderr": 0.031922715695483016, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.031922715695483016 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7828282828282829, "acc_stderr": 0.02937661648494563, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.02937661648494563 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9067357512953368, "acc_stderr": 0.02098685459328972, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.02098685459328972 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6410256410256411, "acc_stderr": 0.024321738484602357, "acc_norm": 0.6410256410256411, "acc_norm_stderr": 0.024321738484602357 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3, "acc_stderr": 0.02794045713622841, "acc_norm": 0.3, "acc_norm_stderr": 0.02794045713622841 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6596638655462185, "acc_stderr": 0.03077805742293167, "acc_norm": 0.6596638655462185, "acc_norm_stderr": 0.03077805742293167 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8293577981651377, "acc_stderr": 0.016129271025099864, "acc_norm": 0.8293577981651377, "acc_norm_stderr": 0.016129271025099864 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4722222222222222, "acc_stderr": 0.0340470532865388, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.0340470532865388 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8088235294117647, "acc_stderr": 0.027599174300640763, "acc_norm": 0.8088235294117647, "acc_norm_stderr": 0.027599174300640763 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7932489451476793, "acc_stderr": 0.0263616516683891, "acc_norm": 0.7932489451476793, "acc_norm_stderr": 0.0263616516683891 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6905829596412556, "acc_stderr": 0.03102441174057221, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.03102441174057221 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7557251908396947, "acc_stderr": 0.03768335959728744, "acc_norm": 0.7557251908396947, "acc_norm_stderr": 0.03768335959728744 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7768595041322314, "acc_stderr": 0.03800754475228733, "acc_norm": 0.7768595041322314, "acc_norm_stderr": 0.03800754475228733 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615624, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615624 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5178571428571429, "acc_stderr": 0.047427623612430116, "acc_norm": 0.5178571428571429, "acc_norm_stderr": 0.047427623612430116 }, "harness|hendrycksTest-management|5": { "acc": 0.7378640776699029, "acc_stderr": 0.043546310772605956, "acc_norm": 0.7378640776699029, "acc_norm_stderr": 0.043546310772605956 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8760683760683761, "acc_stderr": 0.021586494001281382, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.021586494001281382 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8212005108556832, "acc_stderr": 0.013702643715368985, "acc_norm": 0.8212005108556832, "acc_norm_stderr": 0.013702643715368985 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6878612716763006, "acc_stderr": 0.02494679222527231, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.02494679222527231 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.35083798882681566, "acc_stderr": 0.01596103667523096, "acc_norm": 0.35083798882681566, "acc_norm_stderr": 0.01596103667523096 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6895424836601307, "acc_stderr": 0.026493033225145898, "acc_norm": 0.6895424836601307, "acc_norm_stderr": 0.026493033225145898 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7202572347266881, "acc_stderr": 0.025494259350694912, "acc_norm": 0.7202572347266881, "acc_norm_stderr": 0.025494259350694912 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7037037037037037, "acc_stderr": 0.02540719779889016, "acc_norm": 0.7037037037037037, "acc_norm_stderr": 0.02540719779889016 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303062, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303062 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4602346805736636, "acc_stderr": 0.012729785386598559, "acc_norm": 0.4602346805736636, "acc_norm_stderr": 0.012729785386598559 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6433823529411765, "acc_stderr": 0.029097209568411952, "acc_norm": 0.6433823529411765, "acc_norm_stderr": 0.029097209568411952 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6552287581699346, "acc_stderr": 0.019228322018696644, "acc_norm": 0.6552287581699346, "acc_norm_stderr": 0.019228322018696644 }, "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": 0.6979591836734694, "acc_stderr": 0.0293936093198798, "acc_norm": 0.6979591836734694, "acc_norm_stderr": 0.0293936093198798 }, "harness|hendrycksTest-sociology|5": { "acc": 0.835820895522388, "acc_stderr": 0.02619392354445412, "acc_norm": 0.835820895522388, "acc_norm_stderr": 0.02619392354445412 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness|hendrycksTest-virology|5": { "acc": 0.5301204819277109, "acc_stderr": 0.03885425420866767, "acc_norm": 0.5301204819277109, "acc_norm_stderr": 0.03885425420866767 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7894736842105263, "acc_stderr": 0.03126781714663179, "acc_norm": 0.7894736842105263, "acc_norm_stderr": 0.03126781714663179 }, "harness|truthfulqa:mc|0": { "mc1": 0.39167686658506734, "mc1_stderr": 0.017087795881769625, "mc2": 0.5596682871042189, "mc2_stderr": 0.015333014253402569 }, "harness|winogrande|5": { "acc": 0.7971586424625099, "acc_stderr": 0.011301439925936645 }, "harness|gsm8k|5": { "acc": 0.6618650492797574, "acc_stderr": 0.013030829145172208 } } ``` ## 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]

SkyWR/Pespi

--- license: openrail ---

open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged

--- pretty_name: Evaluation run of Korabbit/Llama-2-7b-chat-hf-afr-200step-merged dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Korabbit/Llama-2-7b-chat-hf-afr-200step-merged](https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 1 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged\"\ ,\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\ \ are the [latest results from run 2023-12-02T13:52:27.757521](https://huggingface.co/datasets/open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged/blob/main/results_2023-12-02T13-52-27.757521.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\": 0.18953752843062927,\n\ \ \"acc_stderr\": 0.010795837931896377\n },\n \"harness|gsm8k|5\":\ \ {\n \"acc\": 0.18953752843062927,\n \"acc_stderr\": 0.010795837931896377\n\ \ }\n}\n```" repo_url: https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_gsm8k_5 data_files: - split: 2023_12_02T13_52_27.757521 path: - '**/details_harness|gsm8k|5_2023-12-02T13-52-27.757521.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-02T13-52-27.757521.parquet' - config_name: results data_files: - split: 2023_12_02T13_52_27.757521 path: - results_2023-12-02T13-52-27.757521.parquet - split: latest path: - results_2023-12-02T13-52-27.757521.parquet --- # Dataset Card for Evaluation run of Korabbit/Llama-2-7b-chat-hf-afr-200step-merged ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged - **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 [Korabbit/Llama-2-7b-chat-hf-afr-200step-merged](https://huggingface.co/Korabbit/Llama-2-7b-chat-hf-afr-200step-merged) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 1 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged", "harness_gsm8k_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-02T13:52:27.757521](https://huggingface.co/datasets/open-llm-leaderboard/details_Korabbit__Llama-2-7b-chat-hf-afr-200step-merged/blob/main/results_2023-12-02T13-52-27.757521.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": 0.18953752843062927, "acc_stderr": 0.010795837931896377 }, "harness|gsm8k|5": { "acc": 0.18953752843062927, "acc_stderr": 0.010795837931896377 } } ``` ### 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]

BangumiBase/myheroacademia

--- license: mit tags: - art size_categories: - 10K<n<100K --- # Bangumi Image Base of My Hero Academia This is the image base of bangumi My Hero Academia, we detected 146 characters, 15676 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:----------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------| | 0 | 186 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 254 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 105 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 546 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 69 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 739 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 201 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 34 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 129 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 31 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 3091 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 71 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 174 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 211 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 878 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 130 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 75 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 63 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 69 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 540 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 274 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 286 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 140 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 25 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 81 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 30 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 60 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 26 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 41 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 52 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 81 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 26 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 86 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 65 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 32 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 41 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 74 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 259 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 26 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 11 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 26 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 78 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 29 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 24 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 41 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 24 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 450 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | ![preview 7](46/preview_7.png) | ![preview 8](46/preview_8.png) | | 47 | 21 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 43 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | 49 | 75 | [Download](49/dataset.zip) | ![preview 1](49/preview_1.png) | ![preview 2](49/preview_2.png) | ![preview 3](49/preview_3.png) | ![preview 4](49/preview_4.png) | ![preview 5](49/preview_5.png) | ![preview 6](49/preview_6.png) | ![preview 7](49/preview_7.png) | ![preview 8](49/preview_8.png) | | 50 | 85 | [Download](50/dataset.zip) | ![preview 1](50/preview_1.png) | ![preview 2](50/preview_2.png) | ![preview 3](50/preview_3.png) | ![preview 4](50/preview_4.png) | ![preview 5](50/preview_5.png) | ![preview 6](50/preview_6.png) | ![preview 7](50/preview_7.png) | ![preview 8](50/preview_8.png) | | 51 | 85 | [Download](51/dataset.zip) | ![preview 1](51/preview_1.png) | ![preview 2](51/preview_2.png) | ![preview 3](51/preview_3.png) | ![preview 4](51/preview_4.png) | ![preview 5](51/preview_5.png) | ![preview 6](51/preview_6.png) | ![preview 7](51/preview_7.png) | ![preview 8](51/preview_8.png) | | 52 | 41 | [Download](52/dataset.zip) | ![preview 1](52/preview_1.png) | ![preview 2](52/preview_2.png) | ![preview 3](52/preview_3.png) | ![preview 4](52/preview_4.png) | ![preview 5](52/preview_5.png) | ![preview 6](52/preview_6.png) | ![preview 7](52/preview_7.png) | ![preview 8](52/preview_8.png) | | 53 | 20 | [Download](53/dataset.zip) | ![preview 1](53/preview_1.png) | ![preview 2](53/preview_2.png) | ![preview 3](53/preview_3.png) | ![preview 4](53/preview_4.png) | ![preview 5](53/preview_5.png) | ![preview 6](53/preview_6.png) | ![preview 7](53/preview_7.png) | ![preview 8](53/preview_8.png) | | 54 | 79 | [Download](54/dataset.zip) | ![preview 1](54/preview_1.png) | ![preview 2](54/preview_2.png) | ![preview 3](54/preview_3.png) | ![preview 4](54/preview_4.png) | ![preview 5](54/preview_5.png) | ![preview 6](54/preview_6.png) | ![preview 7](54/preview_7.png) | ![preview 8](54/preview_8.png) | | 55 | 20 | [Download](55/dataset.zip) | ![preview 1](55/preview_1.png) | ![preview 2](55/preview_2.png) | ![preview 3](55/preview_3.png) | ![preview 4](55/preview_4.png) | ![preview 5](55/preview_5.png) | ![preview 6](55/preview_6.png) | ![preview 7](55/preview_7.png) | ![preview 8](55/preview_8.png) | | 56 | 117 | [Download](56/dataset.zip) | ![preview 1](56/preview_1.png) | ![preview 2](56/preview_2.png) | ![preview 3](56/preview_3.png) | ![preview 4](56/preview_4.png) | ![preview 5](56/preview_5.png) | ![preview 6](56/preview_6.png) | ![preview 7](56/preview_7.png) | ![preview 8](56/preview_8.png) | | 57 | 21 | [Download](57/dataset.zip) | ![preview 1](57/preview_1.png) | ![preview 2](57/preview_2.png) | ![preview 3](57/preview_3.png) | ![preview 4](57/preview_4.png) | ![preview 5](57/preview_5.png) | ![preview 6](57/preview_6.png) | ![preview 7](57/preview_7.png) | ![preview 8](57/preview_8.png) | | 58 | 159 | [Download](58/dataset.zip) | ![preview 1](58/preview_1.png) | ![preview 2](58/preview_2.png) | ![preview 3](58/preview_3.png) | ![preview 4](58/preview_4.png) | ![preview 5](58/preview_5.png) | ![preview 6](58/preview_6.png) | ![preview 7](58/preview_7.png) | ![preview 8](58/preview_8.png) | | 59 | 41 | [Download](59/dataset.zip) | ![preview 1](59/preview_1.png) | ![preview 2](59/preview_2.png) | ![preview 3](59/preview_3.png) | ![preview 4](59/preview_4.png) | ![preview 5](59/preview_5.png) | ![preview 6](59/preview_6.png) | ![preview 7](59/preview_7.png) | ![preview 8](59/preview_8.png) | | 60 | 14 | [Download](60/dataset.zip) | ![preview 1](60/preview_1.png) | ![preview 2](60/preview_2.png) | ![preview 3](60/preview_3.png) | ![preview 4](60/preview_4.png) | ![preview 5](60/preview_5.png) | ![preview 6](60/preview_6.png) | ![preview 7](60/preview_7.png) | ![preview 8](60/preview_8.png) | | 61 | 32 | [Download](61/dataset.zip) | ![preview 1](61/preview_1.png) | ![preview 2](61/preview_2.png) | ![preview 3](61/preview_3.png) | ![preview 4](61/preview_4.png) | ![preview 5](61/preview_5.png) | ![preview 6](61/preview_6.png) | ![preview 7](61/preview_7.png) | ![preview 8](61/preview_8.png) | | 62 | 29 | [Download](62/dataset.zip) | ![preview 1](62/preview_1.png) | ![preview 2](62/preview_2.png) | ![preview 3](62/preview_3.png) | ![preview 4](62/preview_4.png) | ![preview 5](62/preview_5.png) | ![preview 6](62/preview_6.png) | ![preview 7](62/preview_7.png) | ![preview 8](62/preview_8.png) | | 63 | 388 | [Download](63/dataset.zip) | ![preview 1](63/preview_1.png) | ![preview 2](63/preview_2.png) | ![preview 3](63/preview_3.png) | ![preview 4](63/preview_4.png) | ![preview 5](63/preview_5.png) | ![preview 6](63/preview_6.png) | ![preview 7](63/preview_7.png) | ![preview 8](63/preview_8.png) | | 64 | 42 | [Download](64/dataset.zip) | ![preview 1](64/preview_1.png) | ![preview 2](64/preview_2.png) | ![preview 3](64/preview_3.png) | ![preview 4](64/preview_4.png) | ![preview 5](64/preview_5.png) | ![preview 6](64/preview_6.png) | ![preview 7](64/preview_7.png) | ![preview 8](64/preview_8.png) | | 65 | 124 | [Download](65/dataset.zip) | ![preview 1](65/preview_1.png) | ![preview 2](65/preview_2.png) | ![preview 3](65/preview_3.png) | ![preview 4](65/preview_4.png) | ![preview 5](65/preview_5.png) | ![preview 6](65/preview_6.png) | ![preview 7](65/preview_7.png) | ![preview 8](65/preview_8.png) | | 66 | 24 | [Download](66/dataset.zip) | ![preview 1](66/preview_1.png) | ![preview 2](66/preview_2.png) | ![preview 3](66/preview_3.png) | ![preview 4](66/preview_4.png) | ![preview 5](66/preview_5.png) | ![preview 6](66/preview_6.png) | ![preview 7](66/preview_7.png) | ![preview 8](66/preview_8.png) | | 67 | 25 | [Download](67/dataset.zip) | ![preview 1](67/preview_1.png) | ![preview 2](67/preview_2.png) | ![preview 3](67/preview_3.png) | ![preview 4](67/preview_4.png) | ![preview 5](67/preview_5.png) | ![preview 6](67/preview_6.png) | ![preview 7](67/preview_7.png) | ![preview 8](67/preview_8.png) | | 68 | 20 | [Download](68/dataset.zip) | ![preview 1](68/preview_1.png) | ![preview 2](68/preview_2.png) | ![preview 3](68/preview_3.png) | ![preview 4](68/preview_4.png) | ![preview 5](68/preview_5.png) | ![preview 6](68/preview_6.png) | ![preview 7](68/preview_7.png) | ![preview 8](68/preview_8.png) | | 69 | 45 | [Download](69/dataset.zip) | ![preview 1](69/preview_1.png) | ![preview 2](69/preview_2.png) | ![preview 3](69/preview_3.png) | ![preview 4](69/preview_4.png) | ![preview 5](69/preview_5.png) | ![preview 6](69/preview_6.png) | ![preview 7](69/preview_7.png) | ![preview 8](69/preview_8.png) | | 70 | 20 | [Download](70/dataset.zip) | ![preview 1](70/preview_1.png) | ![preview 2](70/preview_2.png) | ![preview 3](70/preview_3.png) | ![preview 4](70/preview_4.png) | ![preview 5](70/preview_5.png) | ![preview 6](70/preview_6.png) | ![preview 7](70/preview_7.png) | ![preview 8](70/preview_8.png) | | 71 | 21 | [Download](71/dataset.zip) | ![preview 1](71/preview_1.png) | ![preview 2](71/preview_2.png) | ![preview 3](71/preview_3.png) | ![preview 4](71/preview_4.png) | ![preview 5](71/preview_5.png) | ![preview 6](71/preview_6.png) | ![preview 7](71/preview_7.png) | ![preview 8](71/preview_8.png) | | 72 | 31 | [Download](72/dataset.zip) | ![preview 1](72/preview_1.png) | ![preview 2](72/preview_2.png) | ![preview 3](72/preview_3.png) | ![preview 4](72/preview_4.png) | ![preview 5](72/preview_5.png) | ![preview 6](72/preview_6.png) | ![preview 7](72/preview_7.png) | ![preview 8](72/preview_8.png) | | 73 | 26 | [Download](73/dataset.zip) | ![preview 1](73/preview_1.png) | ![preview 2](73/preview_2.png) | ![preview 3](73/preview_3.png) | ![preview 4](73/preview_4.png) | ![preview 5](73/preview_5.png) | ![preview 6](73/preview_6.png) | ![preview 7](73/preview_7.png) | ![preview 8](73/preview_8.png) | | 74 | 14 | [Download](74/dataset.zip) | ![preview 1](74/preview_1.png) | ![preview 2](74/preview_2.png) | ![preview 3](74/preview_3.png) | ![preview 4](74/preview_4.png) | ![preview 5](74/preview_5.png) | ![preview 6](74/preview_6.png) | ![preview 7](74/preview_7.png) | ![preview 8](74/preview_8.png) | | 75 | 33 | [Download](75/dataset.zip) | ![preview 1](75/preview_1.png) | ![preview 2](75/preview_2.png) | ![preview 3](75/preview_3.png) | ![preview 4](75/preview_4.png) | ![preview 5](75/preview_5.png) | ![preview 6](75/preview_6.png) | ![preview 7](75/preview_7.png) | ![preview 8](75/preview_8.png) | | 76 | 21 | [Download](76/dataset.zip) | ![preview 1](76/preview_1.png) | ![preview 2](76/preview_2.png) | ![preview 3](76/preview_3.png) | ![preview 4](76/preview_4.png) | ![preview 5](76/preview_5.png) | ![preview 6](76/preview_6.png) | ![preview 7](76/preview_7.png) | ![preview 8](76/preview_8.png) | | 77 | 9 | [Download](77/dataset.zip) | ![preview 1](77/preview_1.png) | ![preview 2](77/preview_2.png) | ![preview 3](77/preview_3.png) | ![preview 4](77/preview_4.png) | ![preview 5](77/preview_5.png) | ![preview 6](77/preview_6.png) | ![preview 7](77/preview_7.png) | ![preview 8](77/preview_8.png) | | 78 | 17 | [Download](78/dataset.zip) | ![preview 1](78/preview_1.png) | ![preview 2](78/preview_2.png) | ![preview 3](78/preview_3.png) | ![preview 4](78/preview_4.png) | ![preview 5](78/preview_5.png) | ![preview 6](78/preview_6.png) | ![preview 7](78/preview_7.png) | ![preview 8](78/preview_8.png) | | 79 | 32 | [Download](79/dataset.zip) | ![preview 1](79/preview_1.png) | ![preview 2](79/preview_2.png) | ![preview 3](79/preview_3.png) | ![preview 4](79/preview_4.png) | ![preview 5](79/preview_5.png) | ![preview 6](79/preview_6.png) | ![preview 7](79/preview_7.png) | ![preview 8](79/preview_8.png) | | 80 | 24 | [Download](80/dataset.zip) | ![preview 1](80/preview_1.png) | ![preview 2](80/preview_2.png) | ![preview 3](80/preview_3.png) | ![preview 4](80/preview_4.png) | ![preview 5](80/preview_5.png) | ![preview 6](80/preview_6.png) | ![preview 7](80/preview_7.png) | ![preview 8](80/preview_8.png) | | 81 | 26 | [Download](81/dataset.zip) | ![preview 1](81/preview_1.png) | ![preview 2](81/preview_2.png) | ![preview 3](81/preview_3.png) | ![preview 4](81/preview_4.png) | ![preview 5](81/preview_5.png) | ![preview 6](81/preview_6.png) | ![preview 7](81/preview_7.png) | ![preview 8](81/preview_8.png) | | 82 | 21 | [Download](82/dataset.zip) | ![preview 1](82/preview_1.png) | ![preview 2](82/preview_2.png) | ![preview 3](82/preview_3.png) | ![preview 4](82/preview_4.png) | ![preview 5](82/preview_5.png) | ![preview 6](82/preview_6.png) | ![preview 7](82/preview_7.png) | ![preview 8](82/preview_8.png) | | 83 | 18 | [Download](83/dataset.zip) | ![preview 1](83/preview_1.png) | ![preview 2](83/preview_2.png) | ![preview 3](83/preview_3.png) | ![preview 4](83/preview_4.png) | ![preview 5](83/preview_5.png) | ![preview 6](83/preview_6.png) | ![preview 7](83/preview_7.png) | ![preview 8](83/preview_8.png) | | 84 | 331 | [Download](84/dataset.zip) | ![preview 1](84/preview_1.png) | ![preview 2](84/preview_2.png) | ![preview 3](84/preview_3.png) | ![preview 4](84/preview_4.png) | ![preview 5](84/preview_5.png) | ![preview 6](84/preview_6.png) | ![preview 7](84/preview_7.png) | ![preview 8](84/preview_8.png) | | 85 | 12 | [Download](85/dataset.zip) | ![preview 1](85/preview_1.png) | ![preview 2](85/preview_2.png) | ![preview 3](85/preview_3.png) | ![preview 4](85/preview_4.png) | ![preview 5](85/preview_5.png) | ![preview 6](85/preview_6.png) | ![preview 7](85/preview_7.png) | ![preview 8](85/preview_8.png) | | 86 | 20 | [Download](86/dataset.zip) | ![preview 1](86/preview_1.png) | ![preview 2](86/preview_2.png) | ![preview 3](86/preview_3.png) | ![preview 4](86/preview_4.png) | ![preview 5](86/preview_5.png) | ![preview 6](86/preview_6.png) | ![preview 7](86/preview_7.png) | ![preview 8](86/preview_8.png) | | 87 | 18 | [Download](87/dataset.zip) | ![preview 1](87/preview_1.png) | ![preview 2](87/preview_2.png) | ![preview 3](87/preview_3.png) | ![preview 4](87/preview_4.png) | ![preview 5](87/preview_5.png) | ![preview 6](87/preview_6.png) | ![preview 7](87/preview_7.png) | ![preview 8](87/preview_8.png) | | 88 | 101 | [Download](88/dataset.zip) | ![preview 1](88/preview_1.png) | ![preview 2](88/preview_2.png) | ![preview 3](88/preview_3.png) | ![preview 4](88/preview_4.png) | ![preview 5](88/preview_5.png) | ![preview 6](88/preview_6.png) | ![preview 7](88/preview_7.png) | ![preview 8](88/preview_8.png) | | 89 | 813 | [Download](89/dataset.zip) | ![preview 1](89/preview_1.png) | ![preview 2](89/preview_2.png) | ![preview 3](89/preview_3.png) | ![preview 4](89/preview_4.png) | ![preview 5](89/preview_5.png) | ![preview 6](89/preview_6.png) | ![preview 7](89/preview_7.png) | ![preview 8](89/preview_8.png) | | 90 | 19 | [Download](90/dataset.zip) | ![preview 1](90/preview_1.png) | ![preview 2](90/preview_2.png) | ![preview 3](90/preview_3.png) | ![preview 4](90/preview_4.png) | ![preview 5](90/preview_5.png) | ![preview 6](90/preview_6.png) | ![preview 7](90/preview_7.png) | ![preview 8](90/preview_8.png) | | 91 | 34 | [Download](91/dataset.zip) | ![preview 1](91/preview_1.png) | ![preview 2](91/preview_2.png) | ![preview 3](91/preview_3.png) | ![preview 4](91/preview_4.png) | ![preview 5](91/preview_5.png) | ![preview 6](91/preview_6.png) | ![preview 7](91/preview_7.png) | ![preview 8](91/preview_8.png) | | 92 | 13 | [Download](92/dataset.zip) | ![preview 1](92/preview_1.png) | ![preview 2](92/preview_2.png) | ![preview 3](92/preview_3.png) | ![preview 4](92/preview_4.png) | ![preview 5](92/preview_5.png) | ![preview 6](92/preview_6.png) | ![preview 7](92/preview_7.png) | ![preview 8](92/preview_8.png) | | 93 | 11 | [Download](93/dataset.zip) | ![preview 1](93/preview_1.png) | ![preview 2](93/preview_2.png) | ![preview 3](93/preview_3.png) | ![preview 4](93/preview_4.png) | ![preview 5](93/preview_5.png) | ![preview 6](93/preview_6.png) | ![preview 7](93/preview_7.png) | ![preview 8](93/preview_8.png) | | 94 | 13 | [Download](94/dataset.zip) | ![preview 1](94/preview_1.png) | ![preview 2](94/preview_2.png) | ![preview 3](94/preview_3.png) | ![preview 4](94/preview_4.png) | ![preview 5](94/preview_5.png) | ![preview 6](94/preview_6.png) | ![preview 7](94/preview_7.png) | ![preview 8](94/preview_8.png) | | 95 | 11 | [Download](95/dataset.zip) | ![preview 1](95/preview_1.png) | ![preview 2](95/preview_2.png) | ![preview 3](95/preview_3.png) | ![preview 4](95/preview_4.png) | ![preview 5](95/preview_5.png) | ![preview 6](95/preview_6.png) | ![preview 7](95/preview_7.png) | ![preview 8](95/preview_8.png) | | 96 | 33 | [Download](96/dataset.zip) | ![preview 1](96/preview_1.png) | ![preview 2](96/preview_2.png) | ![preview 3](96/preview_3.png) | ![preview 4](96/preview_4.png) | ![preview 5](96/preview_5.png) | ![preview 6](96/preview_6.png) | ![preview 7](96/preview_7.png) | ![preview 8](96/preview_8.png) | | 97 | 17 | [Download](97/dataset.zip) | ![preview 1](97/preview_1.png) | ![preview 2](97/preview_2.png) | ![preview 3](97/preview_3.png) | ![preview 4](97/preview_4.png) | ![preview 5](97/preview_5.png) | ![preview 6](97/preview_6.png) | ![preview 7](97/preview_7.png) | ![preview 8](97/preview_8.png) | | 98 | 21 | [Download](98/dataset.zip) | ![preview 1](98/preview_1.png) | ![preview 2](98/preview_2.png) | ![preview 3](98/preview_3.png) | ![preview 4](98/preview_4.png) | ![preview 5](98/preview_5.png) | ![preview 6](98/preview_6.png) | ![preview 7](98/preview_7.png) | ![preview 8](98/preview_8.png) | | 99 | 25 | [Download](99/dataset.zip) | ![preview 1](99/preview_1.png) | ![preview 2](99/preview_2.png) | ![preview 3](99/preview_3.png) | ![preview 4](99/preview_4.png) | ![preview 5](99/preview_5.png) | ![preview 6](99/preview_6.png) | ![preview 7](99/preview_7.png) | ![preview 8](99/preview_8.png) | | 100 | 25 | [Download](100/dataset.zip) | ![preview 1](100/preview_1.png) | ![preview 2](100/preview_2.png) | ![preview 3](100/preview_3.png) | ![preview 4](100/preview_4.png) | ![preview 5](100/preview_5.png) | ![preview 6](100/preview_6.png) | ![preview 7](100/preview_7.png) | ![preview 8](100/preview_8.png) | | 101 | 16 | [Download](101/dataset.zip) | ![preview 1](101/preview_1.png) | ![preview 2](101/preview_2.png) | ![preview 3](101/preview_3.png) | ![preview 4](101/preview_4.png) | ![preview 5](101/preview_5.png) | ![preview 6](101/preview_6.png) | ![preview 7](101/preview_7.png) | ![preview 8](101/preview_8.png) | | 102 | 34 | [Download](102/dataset.zip) | ![preview 1](102/preview_1.png) | ![preview 2](102/preview_2.png) | ![preview 3](102/preview_3.png) | ![preview 4](102/preview_4.png) | ![preview 5](102/preview_5.png) | ![preview 6](102/preview_6.png) | ![preview 7](102/preview_7.png) | ![preview 8](102/preview_8.png) | | 103 | 52 | [Download](103/dataset.zip) | ![preview 1](103/preview_1.png) | ![preview 2](103/preview_2.png) | ![preview 3](103/preview_3.png) | ![preview 4](103/preview_4.png) | ![preview 5](103/preview_5.png) | ![preview 6](103/preview_6.png) | ![preview 7](103/preview_7.png) | ![preview 8](103/preview_8.png) | | 104 | 199 | [Download](104/dataset.zip) | ![preview 1](104/preview_1.png) | ![preview 2](104/preview_2.png) | ![preview 3](104/preview_3.png) | ![preview 4](104/preview_4.png) | ![preview 5](104/preview_5.png) | ![preview 6](104/preview_6.png) | ![preview 7](104/preview_7.png) | ![preview 8](104/preview_8.png) | | 105 | 34 | [Download](105/dataset.zip) | ![preview 1](105/preview_1.png) | ![preview 2](105/preview_2.png) | ![preview 3](105/preview_3.png) | ![preview 4](105/preview_4.png) | ![preview 5](105/preview_5.png) | ![preview 6](105/preview_6.png) | ![preview 7](105/preview_7.png) | ![preview 8](105/preview_8.png) | | 106 | 36 | [Download](106/dataset.zip) | ![preview 1](106/preview_1.png) | ![preview 2](106/preview_2.png) | ![preview 3](106/preview_3.png) | ![preview 4](106/preview_4.png) | ![preview 5](106/preview_5.png) | ![preview 6](106/preview_6.png) | ![preview 7](106/preview_7.png) | ![preview 8](106/preview_8.png) | | 107 | 11 | [Download](107/dataset.zip) | ![preview 1](107/preview_1.png) | ![preview 2](107/preview_2.png) | ![preview 3](107/preview_3.png) | ![preview 4](107/preview_4.png) | ![preview 5](107/preview_5.png) | ![preview 6](107/preview_6.png) | ![preview 7](107/preview_7.png) | ![preview 8](107/preview_8.png) | | 108 | 31 | [Download](108/dataset.zip) | ![preview 1](108/preview_1.png) | ![preview 2](108/preview_2.png) | ![preview 3](108/preview_3.png) | ![preview 4](108/preview_4.png) | ![preview 5](108/preview_5.png) | ![preview 6](108/preview_6.png) | ![preview 7](108/preview_7.png) | ![preview 8](108/preview_8.png) | | 109 | 19 | [Download](109/dataset.zip) | ![preview 1](109/preview_1.png) | ![preview 2](109/preview_2.png) | ![preview 3](109/preview_3.png) | ![preview 4](109/preview_4.png) | ![preview 5](109/preview_5.png) | ![preview 6](109/preview_6.png) | ![preview 7](109/preview_7.png) | ![preview 8](109/preview_8.png) | | 110 | 22 | [Download](110/dataset.zip) | ![preview 1](110/preview_1.png) | ![preview 2](110/preview_2.png) | ![preview 3](110/preview_3.png) | ![preview 4](110/preview_4.png) | ![preview 5](110/preview_5.png) | ![preview 6](110/preview_6.png) | ![preview 7](110/preview_7.png) | ![preview 8](110/preview_8.png) | | 111 | 7 | [Download](111/dataset.zip) | ![preview 1](111/preview_1.png) | ![preview 2](111/preview_2.png) | ![preview 3](111/preview_3.png) | ![preview 4](111/preview_4.png) | ![preview 5](111/preview_5.png) | ![preview 6](111/preview_6.png) | ![preview 7](111/preview_7.png) | N/A | | 112 | 67 | [Download](112/dataset.zip) | ![preview 1](112/preview_1.png) | ![preview 2](112/preview_2.png) | ![preview 3](112/preview_3.png) | ![preview 4](112/preview_4.png) | ![preview 5](112/preview_5.png) | ![preview 6](112/preview_6.png) | ![preview 7](112/preview_7.png) | ![preview 8](112/preview_8.png) | | 113 | 23 | [Download](113/dataset.zip) | ![preview 1](113/preview_1.png) | ![preview 2](113/preview_2.png) | ![preview 3](113/preview_3.png) | ![preview 4](113/preview_4.png) | ![preview 5](113/preview_5.png) | ![preview 6](113/preview_6.png) | ![preview 7](113/preview_7.png) | ![preview 8](113/preview_8.png) | | 114 | 390 | [Download](114/dataset.zip) | ![preview 1](114/preview_1.png) | ![preview 2](114/preview_2.png) | ![preview 3](114/preview_3.png) | ![preview 4](114/preview_4.png) | ![preview 5](114/preview_5.png) | ![preview 6](114/preview_6.png) | ![preview 7](114/preview_7.png) | ![preview 8](114/preview_8.png) | | 115 | 18 | [Download](115/dataset.zip) | ![preview 1](115/preview_1.png) | ![preview 2](115/preview_2.png) | ![preview 3](115/preview_3.png) | ![preview 4](115/preview_4.png) | ![preview 5](115/preview_5.png) | ![preview 6](115/preview_6.png) | ![preview 7](115/preview_7.png) | ![preview 8](115/preview_8.png) | | 116 | 10 | [Download](116/dataset.zip) | ![preview 1](116/preview_1.png) | ![preview 2](116/preview_2.png) | ![preview 3](116/preview_3.png) | ![preview 4](116/preview_4.png) | ![preview 5](116/preview_5.png) | ![preview 6](116/preview_6.png) | ![preview 7](116/preview_7.png) | ![preview 8](116/preview_8.png) | | 117 | 31 | [Download](117/dataset.zip) | ![preview 1](117/preview_1.png) | ![preview 2](117/preview_2.png) | ![preview 3](117/preview_3.png) | ![preview 4](117/preview_4.png) | ![preview 5](117/preview_5.png) | ![preview 6](117/preview_6.png) | ![preview 7](117/preview_7.png) | ![preview 8](117/preview_8.png) | | 118 | 46 | [Download](118/dataset.zip) | ![preview 1](118/preview_1.png) | ![preview 2](118/preview_2.png) | ![preview 3](118/preview_3.png) | ![preview 4](118/preview_4.png) | ![preview 5](118/preview_5.png) | ![preview 6](118/preview_6.png) | ![preview 7](118/preview_7.png) | ![preview 8](118/preview_8.png) | | 119 | 16 | [Download](119/dataset.zip) | ![preview 1](119/preview_1.png) | ![preview 2](119/preview_2.png) | ![preview 3](119/preview_3.png) | ![preview 4](119/preview_4.png) | ![preview 5](119/preview_5.png) | ![preview 6](119/preview_6.png) | ![preview 7](119/preview_7.png) | ![preview 8](119/preview_8.png) | | 120 | 32 | [Download](120/dataset.zip) | ![preview 1](120/preview_1.png) | ![preview 2](120/preview_2.png) | ![preview 3](120/preview_3.png) | ![preview 4](120/preview_4.png) | ![preview 5](120/preview_5.png) | ![preview 6](120/preview_6.png) | ![preview 7](120/preview_7.png) | ![preview 8](120/preview_8.png) | | 121 | 10 | [Download](121/dataset.zip) | ![preview 1](121/preview_1.png) | ![preview 2](121/preview_2.png) | ![preview 3](121/preview_3.png) | ![preview 4](121/preview_4.png) | ![preview 5](121/preview_5.png) | ![preview 6](121/preview_6.png) | ![preview 7](121/preview_7.png) | ![preview 8](121/preview_8.png) | | 122 | 126 | [Download](122/dataset.zip) | ![preview 1](122/preview_1.png) | ![preview 2](122/preview_2.png) | ![preview 3](122/preview_3.png) | ![preview 4](122/preview_4.png) | ![preview 5](122/preview_5.png) | ![preview 6](122/preview_6.png) | ![preview 7](122/preview_7.png) | ![preview 8](122/preview_8.png) | | 123 | 48 | [Download](123/dataset.zip) | ![preview 1](123/preview_1.png) | ![preview 2](123/preview_2.png) | ![preview 3](123/preview_3.png) | ![preview 4](123/preview_4.png) | ![preview 5](123/preview_5.png) | ![preview 6](123/preview_6.png) | ![preview 7](123/preview_7.png) | ![preview 8](123/preview_8.png) | | 124 | 21 | [Download](124/dataset.zip) | ![preview 1](124/preview_1.png) | ![preview 2](124/preview_2.png) | ![preview 3](124/preview_3.png) | ![preview 4](124/preview_4.png) | ![preview 5](124/preview_5.png) | ![preview 6](124/preview_6.png) | ![preview 7](124/preview_7.png) | ![preview 8](124/preview_8.png) | | 125 | 10 | [Download](125/dataset.zip) | ![preview 1](125/preview_1.png) | ![preview 2](125/preview_2.png) | ![preview 3](125/preview_3.png) | ![preview 4](125/preview_4.png) | ![preview 5](125/preview_5.png) | ![preview 6](125/preview_6.png) | ![preview 7](125/preview_7.png) | ![preview 8](125/preview_8.png) | | 126 | 52 | [Download](126/dataset.zip) | ![preview 1](126/preview_1.png) | ![preview 2](126/preview_2.png) | ![preview 3](126/preview_3.png) | ![preview 4](126/preview_4.png) | ![preview 5](126/preview_5.png) | ![preview 6](126/preview_6.png) | ![preview 7](126/preview_7.png) | ![preview 8](126/preview_8.png) | | 127 | 42 | [Download](127/dataset.zip) | ![preview 1](127/preview_1.png) | ![preview 2](127/preview_2.png) | ![preview 3](127/preview_3.png) | ![preview 4](127/preview_4.png) | ![preview 5](127/preview_5.png) | ![preview 6](127/preview_6.png) | ![preview 7](127/preview_7.png) | ![preview 8](127/preview_8.png) | | 128 | 32 | [Download](128/dataset.zip) | ![preview 1](128/preview_1.png) | ![preview 2](128/preview_2.png) | ![preview 3](128/preview_3.png) | ![preview 4](128/preview_4.png) | ![preview 5](128/preview_5.png) | ![preview 6](128/preview_6.png) | ![preview 7](128/preview_7.png) | ![preview 8](128/preview_8.png) | | 129 | 28 | [Download](129/dataset.zip) | ![preview 1](129/preview_1.png) | ![preview 2](129/preview_2.png) | ![preview 3](129/preview_3.png) | ![preview 4](129/preview_4.png) | ![preview 5](129/preview_5.png) | ![preview 6](129/preview_6.png) | ![preview 7](129/preview_7.png) | ![preview 8](129/preview_8.png) | | 130 | 13 | [Download](130/dataset.zip) | ![preview 1](130/preview_1.png) | ![preview 2](130/preview_2.png) | ![preview 3](130/preview_3.png) | ![preview 4](130/preview_4.png) | ![preview 5](130/preview_5.png) | ![preview 6](130/preview_6.png) | ![preview 7](130/preview_7.png) | ![preview 8](130/preview_8.png) | | 131 | 9 | [Download](131/dataset.zip) | ![preview 1](131/preview_1.png) | ![preview 2](131/preview_2.png) | ![preview 3](131/preview_3.png) | ![preview 4](131/preview_4.png) | ![preview 5](131/preview_5.png) | ![preview 6](131/preview_6.png) | ![preview 7](131/preview_7.png) | ![preview 8](131/preview_8.png) | | 132 | 57 | [Download](132/dataset.zip) | ![preview 1](132/preview_1.png) | ![preview 2](132/preview_2.png) | ![preview 3](132/preview_3.png) | ![preview 4](132/preview_4.png) | ![preview 5](132/preview_5.png) | ![preview 6](132/preview_6.png) | ![preview 7](132/preview_7.png) | ![preview 8](132/preview_8.png) | | 133 | 32 | [Download](133/dataset.zip) | ![preview 1](133/preview_1.png) | ![preview 2](133/preview_2.png) | ![preview 3](133/preview_3.png) | ![preview 4](133/preview_4.png) | ![preview 5](133/preview_5.png) | ![preview 6](133/preview_6.png) | ![preview 7](133/preview_7.png) | ![preview 8](133/preview_8.png) | | 134 | 14 | [Download](134/dataset.zip) | ![preview 1](134/preview_1.png) | ![preview 2](134/preview_2.png) | ![preview 3](134/preview_3.png) | ![preview 4](134/preview_4.png) | ![preview 5](134/preview_5.png) | ![preview 6](134/preview_6.png) | ![preview 7](134/preview_7.png) | ![preview 8](134/preview_8.png) | | 135 | 138 | [Download](135/dataset.zip) | ![preview 1](135/preview_1.png) | ![preview 2](135/preview_2.png) | ![preview 3](135/preview_3.png) | ![preview 4](135/preview_4.png) | ![preview 5](135/preview_5.png) | ![preview 6](135/preview_6.png) | ![preview 7](135/preview_7.png) | ![preview 8](135/preview_8.png) | | 136 | 14 | [Download](136/dataset.zip) | ![preview 1](136/preview_1.png) | ![preview 2](136/preview_2.png) | ![preview 3](136/preview_3.png) | ![preview 4](136/preview_4.png) | ![preview 5](136/preview_5.png) | ![preview 6](136/preview_6.png) | ![preview 7](136/preview_7.png) | ![preview 8](136/preview_8.png) | | 137 | 11 | [Download](137/dataset.zip) | ![preview 1](137/preview_1.png) | ![preview 2](137/preview_2.png) | ![preview 3](137/preview_3.png) | ![preview 4](137/preview_4.png) | ![preview 5](137/preview_5.png) | ![preview 6](137/preview_6.png) | ![preview 7](137/preview_7.png) | ![preview 8](137/preview_8.png) | | 138 | 6 | [Download](138/dataset.zip) | ![preview 1](138/preview_1.png) | ![preview 2](138/preview_2.png) | ![preview 3](138/preview_3.png) | ![preview 4](138/preview_4.png) | ![preview 5](138/preview_5.png) | ![preview 6](138/preview_6.png) | N/A | N/A | | 139 | 33 | [Download](139/dataset.zip) | ![preview 1](139/preview_1.png) | ![preview 2](139/preview_2.png) | ![preview 3](139/preview_3.png) | ![preview 4](139/preview_4.png) | ![preview 5](139/preview_5.png) | ![preview 6](139/preview_6.png) | ![preview 7](139/preview_7.png) | ![preview 8](139/preview_8.png) | | 140 | 7 | [Download](140/dataset.zip) | ![preview 1](140/preview_1.png) | ![preview 2](140/preview_2.png) | ![preview 3](140/preview_3.png) | ![preview 4](140/preview_4.png) | ![preview 5](140/preview_5.png) | ![preview 6](140/preview_6.png) | ![preview 7](140/preview_7.png) | N/A | | 141 | 8 | [Download](141/dataset.zip) | ![preview 1](141/preview_1.png) | ![preview 2](141/preview_2.png) | ![preview 3](141/preview_3.png) | ![preview 4](141/preview_4.png) | ![preview 5](141/preview_5.png) | ![preview 6](141/preview_6.png) | ![preview 7](141/preview_7.png) | ![preview 8](141/preview_8.png) | | 142 | 8 | [Download](142/dataset.zip) | ![preview 1](142/preview_1.png) | ![preview 2](142/preview_2.png) | ![preview 3](142/preview_3.png) | ![preview 4](142/preview_4.png) | ![preview 5](142/preview_5.png) | ![preview 6](142/preview_6.png) | ![preview 7](142/preview_7.png) | ![preview 8](142/preview_8.png) | | 143 | 15 | [Download](143/dataset.zip) | ![preview 1](143/preview_1.png) | ![preview 2](143/preview_2.png) | ![preview 3](143/preview_3.png) | ![preview 4](143/preview_4.png) | ![preview 5](143/preview_5.png) | ![preview 6](143/preview_6.png) | ![preview 7](143/preview_7.png) | ![preview 8](143/preview_8.png) | | 144 | 17 | [Download](144/dataset.zip) | ![preview 1](144/preview_1.png) | ![preview 2](144/preview_2.png) | ![preview 3](144/preview_3.png) | ![preview 4](144/preview_4.png) | ![preview 5](144/preview_5.png) | ![preview 6](144/preview_6.png) | ![preview 7](144/preview_7.png) | ![preview 8](144/preview_8.png) | | noise | 467 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |

open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview

--- pretty_name: Evaluation run of cognitivecomputations/dolphin-2.8-experiment26-7b-preview dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [cognitivecomputations/dolphin-2.8-experiment26-7b-preview](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview)\ \ 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_cognitivecomputations__dolphin-2.8-experiment26-7b-preview\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-03T20:15:12.993951](https://huggingface.co/datasets/open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview/blob/main/results_2024-03-03T20-15-12.993951.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\": 0.6353244379094956,\n\ \ \"acc_stderr\": 0.032491657533462066,\n \"acc_norm\": 0.6360998788498634,\n\ \ \"acc_norm_stderr\": 0.033161036274808056,\n \"mc1\": 0.3769889840881273,\n\ \ \"mc1_stderr\": 0.016965517578930354,\n \"mc2\": 0.5487265863315941,\n\ \ \"mc2_stderr\": 0.015174281776839011\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6143344709897611,\n \"acc_stderr\": 0.014224250973257186,\n\ \ \"acc_norm\": 0.6450511945392492,\n \"acc_norm_stderr\": 0.013983036904094094\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6413065126468831,\n\ \ \"acc_stderr\": 0.004786368011500458,\n \"acc_norm\": 0.8378809002190799,\n\ \ \"acc_norm_stderr\": 0.00367806799442448\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5703703703703704,\n\ \ \"acc_stderr\": 0.04276349494376599,\n \"acc_norm\": 0.5703703703703704,\n\ \ \"acc_norm_stderr\": 0.04276349494376599\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.61,\n\ \ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.03621034121889507,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.03621034121889507\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \ \ \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.049999999999999996\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.56,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.630057803468208,\n\ \ \"acc_stderr\": 0.0368122963339432,\n \"acc_norm\": 0.630057803468208,\n\ \ \"acc_norm_stderr\": 0.0368122963339432\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.048786087144669955,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.048786087144669955\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n\ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108101,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108101\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.046920083813689104,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.046920083813689104\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4126984126984127,\n \"acc_stderr\": 0.025355741263055266,\n \"\ acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.025355741263055266\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\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.7419354838709677,\n \"acc_stderr\": 0.02489246917246283,\n \"\ acc_norm\": 0.7419354838709677,\n \"acc_norm_stderr\": 0.02489246917246283\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.5024630541871922,\n \"acc_stderr\": 0.03517945038691063,\n \"\ acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\ : 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7676767676767676,\n \"acc_stderr\": 0.030088629490217487,\n \"\ acc_norm\": 0.7676767676767676,\n \"acc_norm_stderr\": 0.030088629490217487\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.022473253332768763,\n\ \ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.022473253332768763\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.676923076923077,\n \"acc_stderr\": 0.02371088850197057,\n \ \ \"acc_norm\": 0.676923076923077,\n \"acc_norm_stderr\": 0.02371088850197057\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131143,\n \ \ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131143\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6512605042016807,\n \"acc_stderr\": 0.030956636328566545,\n\ \ \"acc_norm\": 0.6512605042016807,\n \"acc_norm_stderr\": 0.030956636328566545\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.038615575462551684,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.038615575462551684\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8403669724770643,\n \"acc_stderr\": 0.015703498348461763,\n \"\ acc_norm\": 0.8403669724770643,\n \"acc_norm_stderr\": 0.015703498348461763\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8431372549019608,\n \"acc_stderr\": 0.025524722324553346,\n \"\ acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.025524722324553346\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.02574490253229092,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.02574490253229092\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.031024411740572213,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.031024411740572213\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7480916030534351,\n \"acc_stderr\": 0.03807387116306086,\n\ \ \"acc_norm\": 0.7480916030534351,\n \"acc_norm_stderr\": 0.03807387116306086\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.039418975265163046,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.039418975265163046\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7300613496932515,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.7300613496932515,\n \"acc_norm_stderr\": 0.034878251684978906\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\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.020930193185179333,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.020930193185179333\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\": 0.8122605363984674,\n\ \ \"acc_stderr\": 0.013964393769899133,\n \"acc_norm\": 0.8122605363984674,\n\ \ \"acc_norm_stderr\": 0.013964393769899133\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7167630057803468,\n \"acc_stderr\": 0.024257901705323378,\n\ \ \"acc_norm\": 0.7167630057803468,\n \"acc_norm_stderr\": 0.024257901705323378\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2916201117318436,\n\ \ \"acc_stderr\": 0.015201032512520437,\n \"acc_norm\": 0.2916201117318436,\n\ \ \"acc_norm_stderr\": 0.015201032512520437\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7222222222222222,\n \"acc_stderr\": 0.025646863097137904,\n\ \ \"acc_norm\": 0.7222222222222222,\n \"acc_norm_stderr\": 0.025646863097137904\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6913183279742765,\n\ \ \"acc_stderr\": 0.026236965881153266,\n \"acc_norm\": 0.6913183279742765,\n\ \ \"acc_norm_stderr\": 0.026236965881153266\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.02517104191530968,\n\ \ \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.02517104191530968\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.48226950354609927,\n \"acc_stderr\": 0.02980873964223777,\n \ \ \"acc_norm\": 0.48226950354609927,\n \"acc_norm_stderr\": 0.02980873964223777\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4667535853976532,\n\ \ \"acc_stderr\": 0.012741974333897224,\n \"acc_norm\": 0.4667535853976532,\n\ \ \"acc_norm_stderr\": 0.012741974333897224\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6433823529411765,\n \"acc_stderr\": 0.02909720956841195,\n\ \ \"acc_norm\": 0.6433823529411765,\n \"acc_norm_stderr\": 0.02909720956841195\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6617647058823529,\n \"acc_stderr\": 0.019139943748487036,\n \ \ \"acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.019139943748487036\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\": 0.7306122448979592,\n \"acc_stderr\": 0.02840125202902294,\n\ \ \"acc_norm\": 0.7306122448979592,\n \"acc_norm_stderr\": 0.02840125202902294\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8009950248756219,\n\ \ \"acc_stderr\": 0.028231365092758406,\n \"acc_norm\": 0.8009950248756219,\n\ \ \"acc_norm_stderr\": 0.028231365092758406\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.83,\n \"acc_stderr\": 0.037752516806863715,\n \ \ \"acc_norm\": 0.83,\n \"acc_norm_stderr\": 0.037752516806863715\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3769889840881273,\n\ \ \"mc1_stderr\": 0.016965517578930354,\n \"mc2\": 0.5487265863315941,\n\ \ \"mc2_stderr\": 0.015174281776839011\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8161010260457774,\n \"acc_stderr\": 0.010887916013305892\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6360879454131918,\n \ \ \"acc_stderr\": 0.013252539227966195\n }\n}\n```" repo_url: https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|arc:challenge|25_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-03T20-15-12.993951.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|gsm8k|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hellaswag|10_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-03T20-15-12.993951.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-management|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-03T20-15-12.993951.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|truthfulqa:mc|0_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-03T20-15-12.993951.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_03T20_15_12.993951 path: - '**/details_harness|winogrande|5_2024-03-03T20-15-12.993951.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-03T20-15-12.993951.parquet' - config_name: results data_files: - split: 2024_03_03T20_15_12.993951 path: - results_2024-03-03T20-15-12.993951.parquet - split: latest path: - results_2024-03-03T20-15-12.993951.parquet --- # Dataset Card for Evaluation run of cognitivecomputations/dolphin-2.8-experiment26-7b-preview  Dataset automatically created during the evaluation run of model [cognitivecomputations/dolphin-2.8-experiment26-7b-preview](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b-preview) 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_cognitivecomputations__dolphin-2.8-experiment26-7b-preview", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-03T20:15:12.993951](https://huggingface.co/datasets/open-llm-leaderboard/details_cognitivecomputations__dolphin-2.8-experiment26-7b-preview/blob/main/results_2024-03-03T20-15-12.993951.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": 0.6353244379094956, "acc_stderr": 0.032491657533462066, "acc_norm": 0.6360998788498634, "acc_norm_stderr": 0.033161036274808056, "mc1": 0.3769889840881273, "mc1_stderr": 0.016965517578930354, "mc2": 0.5487265863315941, "mc2_stderr": 0.015174281776839011 }, "harness|arc:challenge|25": { "acc": 0.6143344709897611, "acc_stderr": 0.014224250973257186, "acc_norm": 0.6450511945392492, "acc_norm_stderr": 0.013983036904094094 }, "harness|hellaswag|10": { "acc": 0.6413065126468831, "acc_stderr": 0.004786368011500458, "acc_norm": 0.8378809002190799, "acc_norm_stderr": 0.00367806799442448 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5703703703703704, "acc_stderr": 0.04276349494376599, "acc_norm": 0.5703703703703704, "acc_norm_stderr": 0.04276349494376599 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.75, "acc_stderr": 0.03621034121889507, "acc_norm": 0.75, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.630057803468208, "acc_stderr": 0.0368122963339432, "acc_norm": 0.630057803468208, "acc_norm_stderr": 0.0368122963339432 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.048786087144669955, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.048786087144669955 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108101, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108101 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4649122807017544, "acc_stderr": 0.046920083813689104, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.046920083813689104 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4126984126984127, "acc_stderr": 0.025355741263055266, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.025355741263055266 }, "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": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7419354838709677, "acc_stderr": 0.02489246917246283, "acc_norm": 0.7419354838709677, "acc_norm_stderr": 0.02489246917246283 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5024630541871922, "acc_stderr": 0.03517945038691063, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.030088629490217487, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.030088629490217487 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8911917098445595, "acc_stderr": 0.022473253332768763, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.022473253332768763 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.676923076923077, "acc_stderr": 0.02371088850197057, "acc_norm": 0.676923076923077, "acc_norm_stderr": 0.02371088850197057 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131143, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.028897748741131143 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6512605042016807, "acc_stderr": 0.030956636328566545, "acc_norm": 0.6512605042016807, "acc_norm_stderr": 0.030956636328566545 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33774834437086093, "acc_stderr": 0.038615575462551684, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.038615575462551684 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8403669724770643, "acc_stderr": 0.015703498348461763, "acc_norm": 0.8403669724770643, "acc_norm_stderr": 0.015703498348461763 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8431372549019608, "acc_stderr": 0.025524722324553346, "acc_norm": 0.8431372549019608, "acc_norm_stderr": 0.025524722324553346 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8059071729957806, "acc_stderr": 0.02574490253229092, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.02574490253229092 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6905829596412556, "acc_stderr": 0.031024411740572213, "acc_norm": 0.6905829596412556, "acc_norm_stderr": 0.031024411740572213 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7480916030534351, "acc_stderr": 0.03807387116306086, "acc_norm": 0.7480916030534351, "acc_norm_stderr": 0.03807387116306086 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7520661157024794, "acc_stderr": 0.039418975265163046, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.039418975265163046 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7300613496932515, "acc_stderr": 0.034878251684978906, "acc_norm": 0.7300613496932515, "acc_norm_stderr": 0.034878251684978906 }, "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": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8846153846153846, "acc_stderr": 0.020930193185179333, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.020930193185179333 }, "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": 0.8122605363984674, "acc_stderr": 0.013964393769899133, "acc_norm": 0.8122605363984674, "acc_norm_stderr": 0.013964393769899133 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7167630057803468, "acc_stderr": 0.024257901705323378, "acc_norm": 0.7167630057803468, "acc_norm_stderr": 0.024257901705323378 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2916201117318436, "acc_stderr": 0.015201032512520437, "acc_norm": 0.2916201117318436, "acc_norm_stderr": 0.015201032512520437 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7222222222222222, "acc_stderr": 0.025646863097137904, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.025646863097137904 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6913183279742765, "acc_stderr": 0.026236965881153266, "acc_norm": 0.6913183279742765, "acc_norm_stderr": 0.026236965881153266 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7129629629629629, "acc_stderr": 0.02517104191530968, "acc_norm": 0.7129629629629629, "acc_norm_stderr": 0.02517104191530968 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.48226950354609927, "acc_stderr": 0.02980873964223777, "acc_norm": 0.48226950354609927, "acc_norm_stderr": 0.02980873964223777 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4667535853976532, "acc_stderr": 0.012741974333897224, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.012741974333897224 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6433823529411765, "acc_stderr": 0.02909720956841195, "acc_norm": 0.6433823529411765, "acc_norm_stderr": 0.02909720956841195 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6617647058823529, "acc_stderr": 0.019139943748487036, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.019139943748487036 }, "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": 0.7306122448979592, "acc_stderr": 0.02840125202902294, "acc_norm": 0.7306122448979592, "acc_norm_stderr": 0.02840125202902294 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8009950248756219, "acc_stderr": 0.028231365092758406, "acc_norm": 0.8009950248756219, "acc_norm_stderr": 0.028231365092758406 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.83, "acc_stderr": 0.037752516806863715, "acc_norm": 0.83, "acc_norm_stderr": 0.037752516806863715 }, "harness|hendrycksTest-virology|5": { "acc": 0.5120481927710844, "acc_stderr": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness|truthfulqa:mc|0": { "mc1": 0.3769889840881273, "mc1_stderr": 0.016965517578930354, "mc2": 0.5487265863315941, "mc2_stderr": 0.015174281776839011 }, "harness|winogrande|5": { "acc": 0.8161010260457774, "acc_stderr": 0.010887916013305892 }, "harness|gsm8k|5": { "acc": 0.6360879454131918, "acc_stderr": 0.013252539227966195 } } ``` ## 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]

vic0428/imdb-card-pred-decimal

--- dataset_info: features: - name: text dtype: string - name: prompt dtype: string - name: true_cardinality dtype: int64 splits: - name: train num_bytes: 39101954.4 num_examples: 80000 - name: test num_bytes: 9775488.6 num_examples: 20000 download_size: 8384711 dataset_size: 48877443.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "imdb-card-pred-decimal" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-html-90000

--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 666516 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---

runes/3D

--- license: cc ---

SUSTech/mt_bench

--- dataset_info: features: - name: question_id dtype: int64 - name: category dtype: string - name: turns list: - name: content dtype: string - name: role dtype: string - name: reference sequence: string splits: - name: train num_bytes: 46852 num_examples: 80 download_size: 31246 dataset_size: 46852 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "mt_bench" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

sid220/2713-2024-shot-prediction

--- license: mit ---

ovior/twitter_dataset_1713229857

--- 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: 2288515 num_examples: 7210 download_size: 1295624 dataset_size: 2288515 configs: - config_name: default data_files: - split: train path: data/train-* ---

MrOvkill/SVIG-v0.1

--- license: wtfpl ---

open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k

--- pretty_name: Evaluation run of NurtureAI/Orca-2-7B-16k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NurtureAI/Orca-2-7B-16k](https://huggingface.co/NurtureAI/Orca-2-7B-16k) 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 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_NurtureAI__Orca-2-7B-16k_public\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-11-25T21:39:02.599324](https://huggingface.co/datasets/open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k_public/blob/main/results_2023-11-25T21-39-02.599324.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\": 0.36746546712957223,\n\ \ \"acc_stderr\": 0.033751277531008754,\n \"acc_norm\": 0.3738175555586316,\n\ \ \"acc_norm_stderr\": 0.03459812342976094,\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.01586634640138431,\n \"mc2\": 0.45373679597767685,\n\ \ \"mc2_stderr\": 0.015753224924844992,\n \"em\": 0.21046560402684564,\n\ \ \"em_stderr\": 0.004174608410380015,\n \"f1\": 0.267364723154363,\n\ \ \"f1_stderr\": 0.004242093940617827\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.4735494880546075,\n \"acc_stderr\": 0.014590931358120174,\n\ \ \"acc_norm\": 0.5059726962457338,\n \"acc_norm_stderr\": 0.014610348300255795\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.47410874327823144,\n\ \ \"acc_stderr\": 0.004983087049281742,\n \"acc_norm\": 0.6389165504879506,\n\ \ \"acc_norm_stderr\": 0.00479333052565621\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952365,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952365\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.4342105263157895,\n \"acc_stderr\": 0.0403356566784832,\n\ \ \"acc_norm\": 0.4342105263157895,\n \"acc_norm_stderr\": 0.0403356566784832\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.41,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.41,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.39622641509433965,\n \"acc_stderr\": 0.030102793781791194,\n\ \ \"acc_norm\": 0.39622641509433965,\n \"acc_norm_stderr\": 0.030102793781791194\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3819444444444444,\n\ \ \"acc_stderr\": 0.040629907841466674,\n \"acc_norm\": 0.3819444444444444,\n\ \ \"acc_norm_stderr\": 0.040629907841466674\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \"acc_norm\": 0.31,\n\ \ \"acc_norm_stderr\": 0.046482319871173156\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932269,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932269\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3468208092485549,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.3468208092485549,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.30392156862745096,\n \"acc_stderr\": 0.045766654032077636,\n\ \ \"acc_norm\": 0.30392156862745096,\n \"acc_norm_stderr\": 0.045766654032077636\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n\ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.02951319662553935,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.02951319662553935\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2807017543859649,\n\ \ \"acc_stderr\": 0.04227054451232199,\n \"acc_norm\": 0.2807017543859649,\n\ \ \"acc_norm_stderr\": 0.04227054451232199\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.38620689655172413,\n \"acc_stderr\": 0.04057324734419035,\n\ \ \"acc_norm\": 0.38620689655172413,\n \"acc_norm_stderr\": 0.04057324734419035\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948368,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948368\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.23015873015873015,\n\ \ \"acc_stderr\": 0.037649508797906066,\n \"acc_norm\": 0.23015873015873015,\n\ \ \"acc_norm_stderr\": 0.037649508797906066\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.4,\n\ \ \"acc_stderr\": 0.02786932057166463,\n \"acc_norm\": 0.4,\n \ \ \"acc_norm_stderr\": 0.02786932057166463\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.33497536945812806,\n \"acc_stderr\": 0.033208527423483104,\n\ \ \"acc_norm\": 0.33497536945812806,\n \"acc_norm_stderr\": 0.033208527423483104\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.5454545454545454,\n \"acc_stderr\": 0.038881769216741004,\n\ \ \"acc_norm\": 0.5454545454545454,\n \"acc_norm_stderr\": 0.038881769216741004\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.4292929292929293,\n \"acc_stderr\": 0.03526552724601198,\n \"\ acc_norm\": 0.4292929292929293,\n \"acc_norm_stderr\": 0.03526552724601198\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.5284974093264249,\n \"acc_stderr\": 0.03602573571288441,\n\ \ \"acc_norm\": 0.5284974093264249,\n \"acc_norm_stderr\": 0.03602573571288441\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.34102564102564104,\n \"acc_stderr\": 0.024035489676335065,\n\ \ \"acc_norm\": 0.34102564102564104,\n \"acc_norm_stderr\": 0.024035489676335065\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275794,\n \ \ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275794\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.3067226890756303,\n \"acc_stderr\": 0.02995382389188704,\n \ \ \"acc_norm\": 0.3067226890756303,\n \"acc_norm_stderr\": 0.02995382389188704\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.036030385453603826,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.036030385453603826\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.5229357798165137,\n \"acc_stderr\": 0.0214147570581755,\n \"acc_norm\"\ : 0.5229357798165137,\n \"acc_norm_stderr\": 0.0214147570581755\n },\n\ \ \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\": 0.2916666666666667,\n\ \ \"acc_stderr\": 0.03099866630456052,\n \"acc_norm\": 0.2916666666666667,\n\ \ \"acc_norm_stderr\": 0.03099866630456052\n },\n \"harness|hendrycksTest-high_school_us_history|5\"\ : {\n \"acc\": 0.5490196078431373,\n \"acc_stderr\": 0.03492406104163613,\n\ \ \"acc_norm\": 0.5490196078431373,\n \"acc_norm_stderr\": 0.03492406104163613\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.6033755274261603,\n \"acc_stderr\": 0.03184399873811226,\n \ \ \"acc_norm\": 0.6033755274261603,\n \"acc_norm_stderr\": 0.03184399873811226\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4304932735426009,\n\ \ \"acc_stderr\": 0.033231973029429394,\n \"acc_norm\": 0.4304932735426009,\n\ \ \"acc_norm_stderr\": 0.033231973029429394\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.45038167938931295,\n \"acc_stderr\": 0.04363643698524779,\n\ \ \"acc_norm\": 0.45038167938931295,\n \"acc_norm_stderr\": 0.04363643698524779\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.4049586776859504,\n \"acc_stderr\": 0.04481137755942469,\n \"\ acc_norm\": 0.4049586776859504,\n \"acc_norm_stderr\": 0.04481137755942469\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4074074074074074,\n\ \ \"acc_stderr\": 0.04750077341199986,\n \"acc_norm\": 0.4074074074074074,\n\ \ \"acc_norm_stderr\": 0.04750077341199986\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.3803680981595092,\n \"acc_stderr\": 0.03814269893261837,\n\ \ \"acc_norm\": 0.3803680981595092,\n \"acc_norm_stderr\": 0.03814269893261837\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.25,\n\ \ \"acc_stderr\": 0.04109974682633932,\n \"acc_norm\": 0.25,\n \ \ \"acc_norm_stderr\": 0.04109974682633932\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.36893203883495146,\n \"acc_stderr\": 0.047776151811567386,\n\ \ \"acc_norm\": 0.36893203883495146,\n \"acc_norm_stderr\": 0.047776151811567386\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.43162393162393164,\n\ \ \"acc_stderr\": 0.0324483553531149,\n \"acc_norm\": 0.43162393162393164,\n\ \ \"acc_norm_stderr\": 0.0324483553531149\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768079,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768079\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.40485312899106,\n\ \ \"acc_stderr\": 0.017553246467720256,\n \"acc_norm\": 0.40485312899106,\n\ \ \"acc_norm_stderr\": 0.017553246467720256\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.3959537572254335,\n \"acc_stderr\": 0.026329813341946243,\n\ \ \"acc_norm\": 0.3959537572254335,\n \"acc_norm_stderr\": 0.026329813341946243\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24134078212290502,\n\ \ \"acc_stderr\": 0.014310999547961464,\n \"acc_norm\": 0.24134078212290502,\n\ \ \"acc_norm_stderr\": 0.014310999547961464\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.3954248366013072,\n \"acc_stderr\": 0.027996723180631438,\n\ \ \"acc_norm\": 0.3954248366013072,\n \"acc_norm_stderr\": 0.027996723180631438\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.36012861736334406,\n\ \ \"acc_stderr\": 0.027264297599804015,\n \"acc_norm\": 0.36012861736334406,\n\ \ \"acc_norm_stderr\": 0.027264297599804015\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.42592592592592593,\n \"acc_stderr\": 0.027513747284379424,\n\ \ \"acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.027513747284379424\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.31560283687943264,\n \"acc_stderr\": 0.02772498944950931,\n \ \ \"acc_norm\": 0.31560283687943264,\n \"acc_norm_stderr\": 0.02772498944950931\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.29921773142112124,\n\ \ \"acc_stderr\": 0.01169537463069603,\n \"acc_norm\": 0.29921773142112124,\n\ \ \"acc_norm_stderr\": 0.01169537463069603\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.3897058823529412,\n \"acc_stderr\": 0.029624663581159696,\n\ \ \"acc_norm\": 0.3897058823529412,\n \"acc_norm_stderr\": 0.029624663581159696\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.3349673202614379,\n \"acc_stderr\": 0.019094228167000325,\n \ \ \"acc_norm\": 0.3349673202614379,\n \"acc_norm_stderr\": 0.019094228167000325\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.37272727272727274,\n\ \ \"acc_stderr\": 0.04631381319425463,\n \"acc_norm\": 0.37272727272727274,\n\ \ \"acc_norm_stderr\": 0.04631381319425463\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.4204081632653061,\n \"acc_stderr\": 0.03160106993449604,\n\ \ \"acc_norm\": 0.4204081632653061,\n \"acc_norm_stderr\": 0.03160106993449604\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.472636815920398,\n\ \ \"acc_stderr\": 0.035302355173346824,\n \"acc_norm\": 0.472636815920398,\n\ \ \"acc_norm_stderr\": 0.035302355173346824\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.35542168674698793,\n\ \ \"acc_stderr\": 0.03726214354322415,\n \"acc_norm\": 0.35542168674698793,\n\ \ \"acc_norm_stderr\": 0.03726214354322415\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.32748538011695905,\n \"acc_stderr\": 0.035993357714560276,\n\ \ \"acc_norm\": 0.32748538011695905,\n \"acc_norm_stderr\": 0.035993357714560276\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.28886168910648713,\n\ \ \"mc1_stderr\": 0.01586634640138431,\n \"mc2\": 0.45373679597767685,\n\ \ \"mc2_stderr\": 0.015753224924844992\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.5422257300710339,\n \"acc_stderr\": 0.014002284504422435\n\ \ },\n \"harness|drop|3\": {\n \"em\": 0.21046560402684564,\n \ \ \"em_stderr\": 0.004174608410380015,\n \"f1\": 0.267364723154363,\n \ \ \"f1_stderr\": 0.004242093940617827\n },\n \"harness|gsm8k|5\": {\n\ \ \"acc\": 0.015163002274450341,\n \"acc_stderr\": 0.0033660229497263225\n\ \ }\n}\n```" repo_url: https://huggingface.co/NurtureAI/Orca-2-7B-16k 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_11_25T21_39_02.599324 path: - '**/details_harness|arc:challenge|25_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-11-25T21-39-02.599324.parquet' - config_name: harness_drop_3 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|drop|3_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|drop|3_2023-11-25T21-39-02.599324.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|gsm8k|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hellaswag|10_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-management|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-management|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-11-25T21-39-02.599324.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-international_law|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-management|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-marketing|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-sociology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-virology|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-11-25T21-39-02.599324.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|truthfulqa:mc|0_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-11-25T21-39-02.599324.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_11_25T21_39_02.599324 path: - '**/details_harness|winogrande|5_2023-11-25T21-39-02.599324.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-11-25T21-39-02.599324.parquet' - config_name: results data_files: - split: 2023_11_25T21_39_02.599324 path: - results_2023-11-25T21-39-02.599324.parquet - split: latest path: - results_2023-11-25T21-39-02.599324.parquet --- # Dataset Card for Evaluation run of NurtureAI/Orca-2-7B-16k ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/NurtureAI/Orca-2-7B-16k - **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 [NurtureAI/Orca-2-7B-16k](https://huggingface.co/NurtureAI/Orca-2-7B-16k) 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 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_NurtureAI__Orca-2-7B-16k_public", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-11-25T21:39:02.599324](https://huggingface.co/datasets/open-llm-leaderboard/details_NurtureAI__Orca-2-7B-16k_public/blob/main/results_2023-11-25T21-39-02.599324.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": 0.36746546712957223, "acc_stderr": 0.033751277531008754, "acc_norm": 0.3738175555586316, "acc_norm_stderr": 0.03459812342976094, "mc1": 0.28886168910648713, "mc1_stderr": 0.01586634640138431, "mc2": 0.45373679597767685, "mc2_stderr": 0.015753224924844992, "em": 0.21046560402684564, "em_stderr": 0.004174608410380015, "f1": 0.267364723154363, "f1_stderr": 0.004242093940617827 }, "harness|arc:challenge|25": { "acc": 0.4735494880546075, "acc_stderr": 0.014590931358120174, "acc_norm": 0.5059726962457338, "acc_norm_stderr": 0.014610348300255795 }, "harness|hellaswag|10": { "acc": 0.47410874327823144, "acc_stderr": 0.004983087049281742, "acc_norm": 0.6389165504879506, "acc_norm_stderr": 0.00479333052565621 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4342105263157895, "acc_stderr": 0.0403356566784832, "acc_norm": 0.4342105263157895, "acc_norm_stderr": 0.0403356566784832 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.39622641509433965, "acc_stderr": 0.030102793781791194, "acc_norm": 0.39622641509433965, "acc_norm_stderr": 0.030102793781791194 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3819444444444444, "acc_stderr": 0.040629907841466674, "acc_norm": 0.3819444444444444, "acc_norm_stderr": 0.040629907841466674 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.22, "acc_stderr": 0.04163331998932269, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932269 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3468208092485549, "acc_stderr": 0.036291466701596636, "acc_norm": 0.3468208092485549, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.30392156862745096, "acc_stderr": 0.045766654032077636, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.045766654032077636 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2851063829787234, "acc_stderr": 0.02951319662553935, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.02951319662553935 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.04227054451232199, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.04227054451232199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.38620689655172413, "acc_stderr": 0.04057324734419035, "acc_norm": 0.38620689655172413, "acc_norm_stderr": 0.04057324734419035 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948368, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948368 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.23015873015873015, "acc_stderr": 0.037649508797906066, "acc_norm": 0.23015873015873015, "acc_norm_stderr": 0.037649508797906066 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4, "acc_stderr": 0.02786932057166463, "acc_norm": 0.4, "acc_norm_stderr": 0.02786932057166463 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33497536945812806, "acc_stderr": 0.033208527423483104, "acc_norm": 0.33497536945812806, "acc_norm_stderr": 0.033208527423483104 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5454545454545454, "acc_stderr": 0.038881769216741004, "acc_norm": 0.5454545454545454, "acc_norm_stderr": 0.038881769216741004 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4292929292929293, "acc_stderr": 0.03526552724601198, "acc_norm": 0.4292929292929293, "acc_norm_stderr": 0.03526552724601198 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5284974093264249, "acc_stderr": 0.03602573571288441, "acc_norm": 0.5284974093264249, "acc_norm_stderr": 0.03602573571288441 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.34102564102564104, "acc_stderr": 0.024035489676335065, "acc_norm": 0.34102564102564104, "acc_norm_stderr": 0.024035489676335065 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24074074074074073, "acc_stderr": 0.026067159222275794, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.026067159222275794 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.3067226890756303, "acc_stderr": 0.02995382389188704, "acc_norm": 0.3067226890756303, "acc_norm_stderr": 0.02995382389188704 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.26490066225165565, "acc_stderr": 0.036030385453603826, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.036030385453603826 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.5229357798165137, "acc_stderr": 0.0214147570581755, "acc_norm": 0.5229357798165137, "acc_norm_stderr": 0.0214147570581755 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.2916666666666667, "acc_stderr": 0.03099866630456052, "acc_norm": 0.2916666666666667, "acc_norm_stderr": 0.03099866630456052 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.5490196078431373, "acc_stderr": 0.03492406104163613, "acc_norm": 0.5490196078431373, "acc_norm_stderr": 0.03492406104163613 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.6033755274261603, "acc_stderr": 0.03184399873811226, "acc_norm": 0.6033755274261603, "acc_norm_stderr": 0.03184399873811226 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4304932735426009, "acc_stderr": 0.033231973029429394, "acc_norm": 0.4304932735426009, "acc_norm_stderr": 0.033231973029429394 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.45038167938931295, "acc_stderr": 0.04363643698524779, "acc_norm": 0.45038167938931295, "acc_norm_stderr": 0.04363643698524779 }, "harness|hendrycksTest-international_law|5": { "acc": 0.4049586776859504, "acc_stderr": 0.04481137755942469, "acc_norm": 0.4049586776859504, "acc_norm_stderr": 0.04481137755942469 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4074074074074074, "acc_stderr": 0.04750077341199986, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.04750077341199986 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.3803680981595092, "acc_stderr": 0.03814269893261837, "acc_norm": 0.3803680981595092, "acc_norm_stderr": 0.03814269893261837 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.25, "acc_stderr": 0.04109974682633932, "acc_norm": 0.25, "acc_norm_stderr": 0.04109974682633932 }, "harness|hendrycksTest-management|5": { "acc": 0.36893203883495146, "acc_stderr": 0.047776151811567386, "acc_norm": 0.36893203883495146, "acc_norm_stderr": 0.047776151811567386 }, "harness|hendrycksTest-marketing|5": { "acc": 0.43162393162393164, "acc_stderr": 0.0324483553531149, "acc_norm": 0.43162393162393164, "acc_norm_stderr": 0.0324483553531149 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.40485312899106, "acc_stderr": 0.017553246467720256, "acc_norm": 0.40485312899106, "acc_norm_stderr": 0.017553246467720256 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.3959537572254335, "acc_stderr": 0.026329813341946243, "acc_norm": 0.3959537572254335, "acc_norm_stderr": 0.026329813341946243 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24134078212290502, "acc_stderr": 0.014310999547961464, "acc_norm": 0.24134078212290502, "acc_norm_stderr": 0.014310999547961464 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.3954248366013072, "acc_stderr": 0.027996723180631438, "acc_norm": 0.3954248366013072, "acc_norm_stderr": 0.027996723180631438 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.36012861736334406, "acc_stderr": 0.027264297599804015, "acc_norm": 0.36012861736334406, "acc_norm_stderr": 0.027264297599804015 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.42592592592592593, "acc_stderr": 0.027513747284379424, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.027513747284379424 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.31560283687943264, "acc_stderr": 0.02772498944950931, "acc_norm": 0.31560283687943264, "acc_norm_stderr": 0.02772498944950931 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.29921773142112124, "acc_stderr": 0.01169537463069603, "acc_norm": 0.29921773142112124, "acc_norm_stderr": 0.01169537463069603 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.3897058823529412, "acc_stderr": 0.029624663581159696, "acc_norm": 0.3897058823529412, "acc_norm_stderr": 0.029624663581159696 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.3349673202614379, "acc_stderr": 0.019094228167000325, "acc_norm": 0.3349673202614379, "acc_norm_stderr": 0.019094228167000325 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.37272727272727274, "acc_stderr": 0.04631381319425463, "acc_norm": 0.37272727272727274, "acc_norm_stderr": 0.04631381319425463 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.4204081632653061, "acc_stderr": 0.03160106993449604, "acc_norm": 0.4204081632653061, "acc_norm_stderr": 0.03160106993449604 }, "harness|hendrycksTest-sociology|5": { "acc": 0.472636815920398, "acc_stderr": 0.035302355173346824, "acc_norm": 0.472636815920398, "acc_norm_stderr": 0.035302355173346824 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-virology|5": { "acc": 0.35542168674698793, "acc_stderr": 0.03726214354322415, "acc_norm": 0.35542168674698793, "acc_norm_stderr": 0.03726214354322415 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.32748538011695905, "acc_stderr": 0.035993357714560276, "acc_norm": 0.32748538011695905, "acc_norm_stderr": 0.035993357714560276 }, "harness|truthfulqa:mc|0": { "mc1": 0.28886168910648713, "mc1_stderr": 0.01586634640138431, "mc2": 0.45373679597767685, "mc2_stderr": 0.015753224924844992 }, "harness|winogrande|5": { "acc": 0.5422257300710339, "acc_stderr": 0.014002284504422435 }, "harness|drop|3": { "em": 0.21046560402684564, "em_stderr": 0.004174608410380015, "f1": 0.267364723154363, "f1_stderr": 0.004242093940617827 }, "harness|gsm8k|5": { "acc": 0.015163002274450341, "acc_stderr": 0.0033660229497263225 } } ``` ### 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]

andstor/smart_contracts

--- annotations_creators: [] language_creators: [] language: - en multilinguality: - monolingual pretty_name: Smart Contracts size_categories: - 100K<n<1M source_datasets: - original task_categories: - text-generation task_ids: - language-modeling paperswithcode_id: verified-smart-contracts --- # Dataset Card for Smart Contracts ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [flattened](#flattened) - [flattened_plain_text](#flattened_plain_text) - [inflated](#inflated) - [inflated_plain_text](#inflated_plain_text) - [parsed](#parsed) - [Data Fields](#data-fields) - [flattened](#flattened-1) - [flattened_plain_text](#flattened_plain_text-1) - [inflated](#inflated-1) - [inflated_plain_text](#inflated_plain_text-1) - [parsed](#parsed-1) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://andstor.github.io/smart-contracts - **Repository:** https://github.com/andstor/verified-smart-contracts - **Paper:** - **Leaderboard:** - **Point of Contact:** [André Storhaug](mailto:andr3.storhaug@gmail.com) ### Dataset Summary This is a dataset of verified Smart Contracts from Etherscan.io that are deployed to the Ethereum blockchain. A set of about 100,000 to 200,000 contracts are provided, containing both Solidity and Vyper code. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances #### flattened ``` { 'contract_name': 'MiaKhalifaDAO', 'contract_address': '0xb3862ca215d5ed2de22734ed001d701adf0a30b4', 'language': 'Solidity', 'source_code': '// File: @openzeppelin/contracts/utils/Strings.sol\r\n\r\n\r\n// OpenZeppelin Contracts v4.4.1 (utils/Strings.sol)\r\n\r\npragma solidity ^0.8.0;\r\n\r\n/**\r\n * @dev String operations.\r\n */\r\nlibrary Strings {\r\n...', 'abi': '[{"inputs":[{"internalType":"uint256","name":"maxBatchSize_","type":"uint256"}...]', 'compiler_version': 'v0.8.7+commit.e28d00a7', 'optimization_used': False, 'runs': 200, 'constructor_arguments': '000000000000000000000000000000000000000000000000000000000000000a000...', 'evm_version': 'Default', 'library': '', 'license_type': 'MIT', 'proxy': False, 'implementation': '', 'swarm_source': 'ipfs://e490df69bd9ca50e1831a1ac82177e826fee459b0b085a00bd7a727c80d74089' } ``` #### flattened_extended Same fields as `flattened` but with the following additional fields: ``` { ... 'tx_count': 1074, 'balance': 38 } ``` #### flattened_plain_text ``` { 'language': 'Solidity', 'text': '// File: SafeMath.sol\r\npragma solidity =0.5.16;\r\n\r\n// a library for performing overflow-safe math...' } ``` #### inflated ``` { 'contract_name': 'PinkLemonade', 'file_path': 'PinkLemonade.sol', 'contract_address': '0x9a5be3cc368f01a0566a613aad7183783cff7eec', 'language': 'Solidity', 'source_code': '/**\r\n\r\nt.me/pinklemonadecoin\r\n*/\r\n\r\n// SPDX-License-Identifier: MIT\r\npragma solidity ^0.8.0;\r\n\r\n\r\n/*\r\n * @dev Provides information about the current execution context, including the\r\n * sender of the transaction and its data. While these are generally available...', 'abi': '[{"inputs":[],"stateMutability":"nonpayable","type":"constructor"}...]', 'compiler_version': 'v0.8.4+commit.c7e474f2', 'optimization_used': False, 'runs': 200, 'constructor_arguments': '', 'evm_version': 'Default', 'library': '', 'license_type': 'MIT', 'proxy': False, 'implementation': '', 'swarm_source': 'ipfs://eb0ac9491a04e7a196280fd27ce355a85d79b34c7b0a83ab606d27972a06050c' } ``` #### inflated_plain_text ``` { 'language': 'Solidity', 'text': '\\npragma solidity ^0.4.11;\\n\\ncontract ERC721 {\\n // Required methods\\n function totalSupply() public view returns (uint256 total);...' } ``` #### parsed ``` { 'contract_name': 'BondedECDSAKeep', 'file_path': '@keep-network/keep-core/contracts/StakeDelegatable.sol', 'contract_address': '0x61935dc4ffc5c5f1d141ac060c0eef04a792d8ee', 'language': 'Solidity', 'class_name': 'StakeDelegatable', 'class_code': 'contract StakeDelegatable {\n using OperatorParams for uint256;\n\n mapping(address => Operator) internal operators;\n\n struct Operator {\n uint256 packedParams;\n address owner;\n address payable beneficiary;\n address authorizer;\n }\n\n...', 'class_documentation': '/// @title Stake Delegatable\n/// @notice A base contract to allow stake delegation for staking contracts.', 'class_documentation_type': 'NatSpecSingleLine', 'func_name': 'balanceOf', 'func_code': 'function balanceOf(address _address) public view returns (uint256 balance) {\n return operators[_address].packedParams.getAmount();\n }', 'func_documentation': '/// @notice Gets the stake balance of the specified address.\n/// @param _address The address to query the balance of.\n/// @return An uint256 representing the amount staked by the passed address.', 'func_documentation_type': 'NatSpecSingleLine', 'compiler_version': 'v0.5.17+commit.d19bba13', 'license_type': 'MIT', 'swarm_source': 'bzzr://63a152bdeccda501f3e5b77f97918c5500bb7ae07637beba7fae76dbe818bda4' } ``` ### Data Fields #### flattened - `contract_name` (`string`): containing the smart contract name. - `contract_address` (`string`): containing the Ethereum address for the smart contract. - `language` (`string`): containing the language of the smart contract. - `source_code ` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `abi` (`string`): containing the Application Binary Interface (ABI) of the smart contract. - `compiler_version` (`string`): containing the compiler version used to compile the smart contract. - `optimization_used` (`boolean`): indicating if the smart contract used optimization. - `runs` (`number`): containing the number of optimization steps used. - `constructor_arguments` (`string`): containing the constructor arguments of the smart contract. - `evm_version` (`string`): containing the EVM version used to compile the smart contract. - `library` (`string`): containing the `name:address` of libraries used separated by `;`. - `license_type` (`string`): containing the license type of the smart contract. - `proxy` (`boolean`): indicating if the smart contract is a proxy. - `implementation` (`string`): containing the implementation of the smart contract if it is a proxy. - `swarm_source` (`string`): containing the swarm source of the smart contract. #### flattened_extended Same fields as `flattened` but with the following additional fields: - `tx_count` (`number`): containing the number of transactions made to the smart contract. - `balance` (`string`): containing the ether balancce of the smart contract. #### flattened_plain_text - `text` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `language` (`string`): containing the language of the smart contract. #### inflated Same fields as `flattened` but with the following additional fields: - `file_path` (`string`): containing the original path to the file. #### inflated_plain_text - `text` (`string`): containing the source code of the smart contract. This contains all code needed for compilation of the contract, including libraries. - `language` (`string`): containing the language of the smart contract. #### parsed - `contract_name` (`string`): containing the smart contract name. - `file_path` (`string`): containing the original path to the file. - `contract_address` (`string`): containing the Ethereum address for the smart contract. - `language` (`string`): containing the language of the smart contract. - `class_name` (`string`): containing the name of the "class" (contract). - `class_code` (`string`): containing the source code of the "class" (contract). - `class_documentation` (`string`): containing the documentation (code comment) of the "class" (contract). - `class_documentation_type` (`string`): containing the documentation type of the "class" (contract). Can be one of: `NatSpecMultiLine`, `NatSpecSingleLine`, `LineComment` or `Comment`. - `func_name` (`string`): containing the name of the function definition. - `func_code` (`string`): containing the source code of the function. - `func_documentation` (`string`): containing the documentation (code comment) of the contract definition (or "class"). - `func_documentation_type` (`string`): containing the documentation type of the function. Can be one of: `NatSpecMultiLine`, `NatSpecSingleLine`, `LineComment` or `Comment`. - `compiler_version` (`string`): containing the compiler version used to compile the smart contract. - `license_type` (`string`): containing the license type of the smart contract. - `swarm_source` (`string`): containing the swarm source of the smart contract. ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information ```bibtex @misc{storhaug2023efficient, title={Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decoding}, author={André Storhaug and Jingyue Li and Tianyuan Hu}, year={2023}, eprint={2309.09826}, archivePrefix={arXiv}, primaryClass={cs.CR} } ``` ### Contributions Thanks to [@andstor](https://github.com/andstor) for adding this dataset.

leey4n/KR3

--- annotations_creators: [] language_creators: [] language: - ko license: - cc-by-nc-sa-4.0 multilinguality: - monolingual pretty_name: KR3 size_categories: - 100K<n<1m source_datasets: [] task_categories: - text-classification task_ids: - sentiment-classification --- ### KR3: Korean Restaurant Reviews with Ratings Korean sentiment classification dataset - Size: 460K(+180K) - Language: Korean-centric ### ⚠️ Caution with `Rating` Column 0 stands for negative review, 1 stands for positive review, and 2 stands for ambiguous review. **Note that rating 2 is not intended to be used directly for supervised learning(classification).** This data is included for additional pre-training purpose or other usage. In other words, this dataset is basically a **binary** sentiment classification task where labels are 0 and 1. ### 🔍 See More See all the codes for crawling/preprocessing the dataset and experiments with KR3 in [GitHub Repo](https://github.com/Wittgensteinian/kr3). See Kaggle dataset in [Kaggle Dataset](https://www.kaggle.com/ninetyninenewton/kr3-korean-restaurant-reviews-with-ratings). ### Usage ```python from datasets import load_dataset kr3 = load_dataset("leey4n/KR3", name='kr3', split='train') kr3 = kr3.remove_columns(['__index_level_0__']) # Original file didn't include this column. Suspect it's a hugging face issue. ``` ```python # drop reviews with ambiguous label kr3_binary = kr3.filter(lambda example: example['Rating'] != 2) ``` ### License **CC BY-NC-SA 4.0** ### Legal Issues We concluded that the **non-commerical usage and release of KR3 fall into the range of fair use (공정 이용)** stated in the Korean copyright act (저작권법). We further clarify that we **did not agree to the terms of service** from any websites which might prohibit web crawling. In other words, web crawling we've done was proceeded without logging in to the website. Despite all of these, feel free to contact to any of the contributors if you notice any legal issues. ### Contributors & Acknowledgement (Alphabetical order) [Dongin Jung](https://github.com/dongin1009) [Hyunwoo Kwak](https://github.com/Kwak-Hyun-woo) [Kaeun Lee](https://github.com/Kaeun-Lee) [Yejoon Lee](https://github.com/wittgensteinian) This work was done as DIYA 4기. Compute resources needed for the work was supported by [DIYA](https://blog.diyaml.com) and surromind.ai.

pattern90/test4

--- dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 380878.0 num_examples: 6 download_size: 80720 dataset_size: 380878.0 --- # Dataset Card for "oct" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

NobodyExistsOnTheInternet/KTO-PRM

--- dataset_info: features: - name: prompt dtype: string - name: completion dtype: string - name: label dtype: bool splits: - name: train num_bytes: 379985094.2914787 num_examples: 473458 download_size: 70204316 dataset_size: 379985094.2914787 configs: - config_name: default data_files: - split: train path: data/train-* ---

ai4bharat/IndicCOPA

--- annotations_creators: - expert-generated language: - as - bn - en - gom - gu - hi - kn - mai - ml - mr - ne - or - pa - sa - sat - sd - ta - te - ur language_creators: - expert-generated license: - cc-by-4.0 multilinguality: - multilingual pretty_name: IndicXCOPA size_categories: - 1K<n<10K source_datasets: - extended|xcopa tags: [] task_categories: - multiple-choice task_ids: - multiple-choice-qa --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.

deven367/babylm-100M-children-stories

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 17676869 num_examples: 76758 - name: valid num_bytes: 1425137 num_examples: 5996 - name: test num_bytes: 1804421 num_examples: 7959 download_size: 12749002 dataset_size: 20906427 --- # Dataset Card for "babylm-100M-children-stories" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

pkufool/librilight-text

--- license: apache-2.0 ---

TheDKBR/thedkbr

--- license: openrail ---

ramixpe/sp_llama_simple

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: text dtype: string splits: - name: train num_bytes: 10031378 num_examples: 20551 download_size: 2324224 dataset_size: 10031378 configs: - config_name: default data_files: - split: train path: data/train-* ---

saurabhRaj11/MobiusBpmndataset

--- license: mit ---

KaleidoSG/Deepmind

--- license: other language: - en pretty_name: Deepmind size_categories: - 1M<n<10M configs: - config_name: default data_files: - split: train path: - train/OpenOrca/*.csv - train/dolphin/*.csv - train/flan_zsnoopt_data/*.csv - train/t0_zsnoopt_data/*.csv --- # Deepmind Dataset ## Overview The Deepmind dataset is a curated collection of high-quality datasets meticulously selected to suit a wide range of research and application needs. These datasets have been chosen for their relevance, diversity, and overall data quality. The Deepmind dataset is provided in the Stanford Alpaca format, ensuring consistency and ease of use across various projects and applications. # License The Deepmind dataset is made available under the Apache License 2.0, which allows for flexible usage, modification, and distribution while maintaining attribution to the original data sources. # Dataset Details Here's a snapshot of some of the top datasets included in the Deepmind collection: | Dataset | Files | Size | |---------------|-------|---------| | Open_Orca | 2 | 6.9 GB | | Dolphin | 2 | 5.7 GB | | FLAN | 78 | 15.1 GB | | t0 | 124 | 25.9 GB | | **Total** | 206 | 53.6 GB | The datasets in the Deepmind collection span a diverse array of domains and are carefully selected for their high quality. These datasets cater to various research and application needs, each offering unique insights and applications. # Citation ``` Deepmind Dataset. 2023 Deepmind Retrieved from huggingface.co/datasets/NewstaR/Deepmind Apache 2.0 License ```

Chaoticka/test

--- license: artistic-2.0 tags: - art pretty_name: Chaos Doll ---

huggingartists/ghostmane

--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/ghostmane" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [About](#about) ## Dataset Description - **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of the generated dataset:** 0.027776 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://assets.genius.com/images/default_avatar_300.png?1631290285')"> </div> </div> <a href="https://huggingface.co/huggingartists/ghostmane"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">Ghostmane</div> <a href="https://genius.com/artists/ghostmane"> <div style="text-align: center; font-size: 14px;">@ghostmane</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/ghostmane). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/ghostmane") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits | train |validation|test| |------:|---------:|---:| |2| -| -| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/ghostmane") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About *Built by Aleksey Korshuk* [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)

suwitlam/whisper-sun-system-dataset-sentence

--- license: cc0-1.0 ---

Tamnemtf/hcmue-qa-1

--- license: llama2 ---

jfloresf/burn-cems-1

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

FaalSa/dfaas3

--- dataset_info: features: - name: start dtype: timestamp[s] - name: target sequence: float32 - name: item_id dtype: string - name: feat_static_cat sequence: uint64 splits: - name: train num_bytes: 57633 num_examples: 1 - name: validation num_bytes: 58113 num_examples: 1 - name: test num_bytes: 58593 num_examples: 1 download_size: 35533 dataset_size: 174339 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

awacke1/eCQM-Code-Value-Semantic-Set.csv

--- license: mit --- eCQM-Code-Value-Semantic-Set.csv

GDGiangi/SEIRDB

--- language: - en - fr - it - el - es - ru pretty_name: SEIRDB size_categories: - 100K<n<1M task_categories: - audio-classification extra_gated_prompt: "To obtain an access token, the database licence must be purchased through https://gabegiangi.wordpress.com/2023/05/15/seir-db/" extra_gated_fields: Name: text Email: text Company: text Country: text Access Token: text I agree not to give access to any other entities: checkbox --- # Speech Emotion Intensity Recognition Database (SEIR-DB) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact: gabegiangi@gmail.com** ### Dataset Summary The SEIR-DB is a comprehensive, multilingual speech emotion intensity recognition dataset containing over 600,000 instances from various sources. It is designed to support tasks related to speech emotion recognition and emotion intensity estimation. The database includes languages such as English, Russian, Mandarin, Greek, Italian, and French. ### Supported Tasks and Leaderboards The SEIR dataset is suitable for speech emotion recognition and speech emotion intensity estimation tasks (a subset of the dataset). ### Languages SEIR-DB encompasses multilingual data, featuring languages such as English, Russian, Mandarin, Greek, Italian, and French. ## Dataset Structure ### Data Instances The raw data collection comprises over 600,000 data instances (375 hours). Users of the database can access the raw audio data, which is stored in subdirectories of the data directory (in their respective datasets). After processing, cleaning, and formatting, the dataset contains approximately 120,000 training instances with an average audio utterance length of 3.8 seconds. ### Data Fields - ID: unique sample identifier - WAV: path to the audio file, located in the data directory - EMOTION: annotated emotion - INTENSITY: annotated intensity (ranging from 1-5), where 1 denotes low intensity, and 5 signifies high intensity; 0 indicates no annotation - LENGTH: duration of the audio utterance ### Data Splits The data is divided into train, test, and validation sets, located in the respective JSON manifest files. - Train: 80% - Validation: 10% - Test: 10% For added flexibility, unsplit data is also available in data.csv to allow custom splits. ## Dataset Creation ### Curation Rationale The SEIR-DB was curated to maximize the volume of data instances, addressing a significant limitation in speech emotion recognition (SER) experimentation—the lack of emotion data and the small size of available datasets. This database aims to resolve these issues by providing a large volume of emotion-annotated data that is cleanly formatted for experimentation. ### Source Data The dataset was compiled from various sources. ### Annotations #### Annotation process For details on the annotation process, please refer to the source for each dataset, as they were conducted differently. However, the entire database is human-annotated. #### Who are the annotators? Please consult the source documentation for information on the annotators. ### Personal and Sensitive Information No attempt was made to remove personal and sensitive information, as consent and recordings were not obtained internally. ## Considerations for Using the Data ### Social Impact of Dataset The SEIR-DB dataset can significantly impact the research and development of speech emotion recognition technologies by providing a large volume of annotated data. These technologies have the potential to enhance various applications, such as mental health monitoring, virtual assistants, customer support, and communication devices for people with disabilities. ### Discussion of Biases During the dataset cleaning process, efforts were made to balance the database concerning the number of samples for each dataset, emotion distribution (with a greater focus on primary emotions and less on secondary emotions), and language distribution. However, biases may still be present. ### Other Known Limitations No specific limitations have been identified at this time. ## Additional Information ### Dataset Curators Gabriel Giangi - Concordia University - Montreal, QC Canada - gabegiangi@gmail.com ### Licensing Information This dataset can be used for research and academic purposes. For commercial purposes, please contact gabegiangi@gmail.com . ### Citation Information Aljuhani, R. H., Alshutayri, A., & Alahdal, S. (2021). Arabic speech emotion recognition from Saudi dialect corpus. IEEE Access, 9, 127081-127085. Basu, S., Chakraborty, J., & Aftabuddin, M. (2017). Emotion recognition from speech using convolutional neural network with recurrent neural network architecture. In ICCES. Baevski, A., Zhou, H. H., & Collobert, R. (2020). Wav2vec 2.0: A framework for self-supervised learning of speech representations. In NeurIPS. Busso, C., Bulut, M., Lee, C. C., Kazemzadeh, A., Mower, E., Kim, S., ... & Narayanan, S. (2008). Iemocap: Interactive emotional dyadic motion capture database. In LREC. Cao, H., Cooper, D.G., Keutmann, M.K., Gur, R.C., Nenkova, A., & Verma, R. (2014). CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset. IEEE Transactions on Affective Computing, 5, 377-390. Chopra, S., Mathur, P., Sawhney, R., & Shah, R. R. (2021). Meta-Learning for Low-Resource Speech Emotion Recognition. In ICASSP. Costantini, G., Iaderola, I., Paoloni, A., & Todisco, M. (2014). EMOVO Corpus: an Italian Emotional Speech Database. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) (pp. 3501-3504). European Language Resources Association (ELRA). Reykjavik, Iceland. http://www.lrec-conf.org/proceedings/lrec2014/pdf/591_Paper.pdf Duville, Mathilde Marie; Alonso-Valerdi, Luz María; Ibarra-Zarate, David I. (2022), “Mexican Emotional Speech Database (MESD)”, Mendeley Data, V5, doi: 10.17632/cy34mh68j9.5 Gournay, Philippe, Lahaie, Olivier, & Lefebvre, Roch. (2018). A Canadian French Emotional Speech Dataset (1.1) [Data set]. ACM Multimedia Systems Conference (MMSys 2018) (MMSys'18), Amsterdam, The Netherlands. Zenodo. https://doi.org/10.5281/zenodo.1478765 Kandali, A., Routray, A., & Basu, T. (2008). Emotion recognition from Assamese speeches using MFCC features and GMM classifier. In TENCON. Kondratenko, V., Sokolov, A., Karpov, N., Kutuzov, O., Savushkin, N., & Minkin, F. (2022). Large Raw Emotional Dataset with Aggregation Mechanism. arXiv preprint arXiv:2212.12266. Kwon, S. (2021). MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach. Expert Systems with Applications, 167, 114177. Lee, Y., Lee, J. W., & Kim, S. (2019). Emotion recognition using convolutional neural network and multiple feature fusion. In ICASSP. Li, Y., Baidoo, C., Cai, T., & Kusi, G. A. (2019). Speech emotion recognition using 1d cnn with no attention. In ICSEC. Lian, Z., Tao, J., Liu, B., Huang, J., Yang, Z., & Li, R. (2020). Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition. In Interspeech. Livingstone, S. R., & Russo, F. A. (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. Peng, Z., Li, X., Zhu, Z., Unoki, M., Dang, J., & Akagi, M. (2020). Speech emotion recognition using 3d convolutions and attention-based sliding recurrent networks with auditory front-ends. IEEE Access, 8, 16560-16572. Poria, S., Hazarika, D., Majumder, N., Naik, G., Cambria, E., & Mihalcea, R. (2019). Meld: A multimodal multi-party dataset for emotion recognition in conversations. In ACL. Schneider, A., Baevski, A., & Collobert, R. (2019). Wav2vec: Unsupervised pre-training for speech recognition. In ICLR. Schuller, B., Rigoll, G., & Lang, M. (2010). Speech emotion recognition: Features and classification models. In Interspeech. Sinnott, R. O., Radulescu, A., & Kousidis, S. (2013). Surrey audiovisual expressed emotion (savee) database. In AVEC. Vryzas, N., Kotsakis, R., Liatsou, A., Dimoulas, C. A., & Kalliris, G. (2018). Speech emotion recognition for performance interaction. Journal of the Audio Engineering Society, 66(6), 457-467. Vryzas, N., Matsiola, M., Kotsakis, R., Dimoulas, C., & Kalliris, G. (2018, September). Subjective Evaluation of a Speech Emotion Recognition Interaction Framework. In Proceedings of the Audio Mostly 2018 on Sound in Immersion and Emotion (p. 34). ACM. Wang, Y., Yang, Y., Liu, Y., Chen, Y., Han, N., & Zhou, J. (2019). Speech emotion recognition using a combination of cnn and rnn. In Interspeech. Yoon, S., Byun, S., & Jung, K. (2018). Multimodal speech emotion recognition using audio and text. In SLT. Zhang, R., & Liu, M. (2020). Speech emotion recognition with self-attention. In ACL. ### Contributions Gabriel Giangi - Concordia University - Montreal, QC Canada - gabegiangi@gmail.com

acloudfan/hindi-to-english-translate

--- license: apache-2.0 ---

mask-distilled-onesec-cv12-each-chunk-uniq/chunk_265

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 948318804.0 num_examples: 186237 download_size: 967011151 dataset_size: 948318804.0 --- # Dataset Card for "chunk_265" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

deokhk/en_wiki_sentences_1000000

--- dataset_info: features: - name: sentence dtype: string splits: - name: train num_bytes: 124980032 num_examples: 1000000 - name: dev num_bytes: 123586 num_examples: 1000 download_size: 77463265 dataset_size: 125103618 --- # Dataset Card for "en_wiki_sentences_1000000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

TurkuNLP/genre-6

--- task_categories: - text-classification language: - en size_categories: - 10K<n<100K --- # Dataset Card for Dataset Name ## Dataset Summary Genre-6 dataset is an English dataset based on Kindletrends (UK & US). It contains more than 20k books and associated categories with ready-made binary classification and multilabel classification labels. ## Dataset Structure ### Data Instances `` {"text": "...", "categories": "Engineering & Transportation;Science & Math", "fiction": "non-fiction", "split1": ['Science & Math'], "split2" : ['Engineering & Transportation', 'Science & Math'], "split3": ['Science & Math']} `` ### Data Fields - text: Kindletrends text - categories: Kidletrends categories (1 to 2 categories per book) - fiction: binary label for fiction and non-fiction books - splits 1,2,3: multilabel for different subsets of the categories ### Data Splits The dataset contains train (80%), validation (10%) and test (10%) splits. The splits for multilabels are following: - split1: 'Biology & Nature & Biological Sciences','Computer Science', 'Fantasy','Medicine & Health Sciences','Philosophy','Science & Math'. - split2: 'Biology & Nature & Biological Sciences','Computer Science', 'Engineering & Transportation','Fantasy','Medicine & Health Sciences','Science & Math'. - split3: 'Biology & Nature & Biological Sciences','Computer Science', 'Fantasy','Medicine & Health Sciences', 'Poetry', 'Politics & Social Sciences', 'Science & Math'. More splits can be generated from the field "categories". ### Source Data [Kindletrends](https://kindletrends.com/categories/)

ebylmz/architects

--- license: mit ---

LLMao/2024_03_10_03_32_56_Archive

--- dataset_info: features: - name: page_content dtype: string - name: metadata struct: - name: source dtype: string - name: page dtype: int64 splits: - name: train num_bytes: 2578897 num_examples: 7 download_size: 1430198 dataset_size: 2578897 configs: - config_name: default data_files: - split: train path: data/train-* ---

hongboyang/CMRC2018_instruction1

--- dataset_info: features: - name: INPUT dtype: string - name: TARGET dtype: string splits: - name: train num_bytes: 17133521 num_examples: 10142 download_size: 4142597 dataset_size: 17133521 --- # Dataset Card for "CMRC2018_instruction1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ghbacct/financial-phrasebank-all-agree-clustering

--- dataset_info: features: - name: sentences sequence: string - name: labels sequence: int64 splits: - name: test num_bytes: 303379 num_examples: 1 download_size: 166862 dataset_size: 303379 --- # Dataset Card for "financial-phrasebank-all-agree-clustering" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Danieldlima21/mcmelody

--- license: openrail ---

zolak/twitter_dataset_81_1713085248

--- 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: 2664104 num_examples: 6535 download_size: 1316393 dataset_size: 2664104 configs: - config_name: default data_files: - split: train path: data/train-* ---

serhii-korobchenko/github-issues-embeddings

--- dataset_info: features: - name: html_url dtype: string - name: comments dtype: string - name: title dtype: string - name: body dtype: string - name: comment_length dtype: int64 - name: text dtype: string - name: embeddings sequence: float32 splits: - name: train num_bytes: 44924892 num_examples: 5034 download_size: 23623074 dataset_size: 44924892 configs: - config_name: default data_files: - split: train path: data/train-* ---

HamdanXI/paradetox-split

--- dataset_info: features: - name: en_toxic_comment dtype: string - name: en_neutral_comment dtype: string splits: - name: train num_bytes: 2082140.019398298 num_examples: 19073 - name: test num_bytes: 78390 num_examples: 671 download_size: 1237763 dataset_size: 2160530.019398298 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

eduzon/joaopauloo

--- license: openrail ---

Sachin7/story_dataset

--- dataset_info: features: - name: text dtype: string - name: 'Unnamed: 1' dtype: float64 splits: - name: train num_bytes: 143265.9775280899 num_examples: 62 - name: test num_bytes: 62390.02247191011 num_examples: 27 download_size: 145722 dataset_size: 205656.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

qnguyen3/alapaca-vi

--- license: mit ---

long292/PADNCH_5

--- dataset_info: features: - name: Phiên âm dtype: string - name: Dịch nghĩa dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1579554 num_examples: 7406 download_size: 925406 dataset_size: 1579554 configs: - config_name: default data_files: - split: train path: data/train-* ---

InceptiveDev/job_title

--- license: mit ---

LEAP/ClimSim_low-res

--- license: cc-by-4.0 --- Corresponding GitHub repo can be found here: https://github.com/leap-stc/ClimSim Read more: https://arxiv.org/abs/2306.08754.

soddokayo/crime2

--- dataset_info: features: - name: sentence dtype: string - name: tokens sequence: string - name: ner_tags sequence: int64 splits: - name: train num_bytes: 38639.2131147541 num_examples: 54 - name: test num_bytes: 5008.786885245901 num_examples: 7 download_size: 17337 dataset_size: 43648.0 --- # Dataset Card for "crime2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/gr_sl8_girlsfrontline

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of gr_sl8/GrSL8/SL8 (Girls' Frontline) This is the dataset of gr_sl8/GrSL8/SL8 (Girls' Frontline), containing 26 images and their tags. The core tags of this character are `breasts, purple_eyes, grey_hair, short_hair, medium_breasts, white_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 | 26 | 26.41 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 26 | 17.87 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 58 | 32.81 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 26 | 24.86 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_girlsfrontline/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 58 | 41.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gr_sl8_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/gr_sl8_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 | 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, smile, cleavage, looking_at_viewer, jacket, navel, simple_background, teeth, white_background, holding | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | smile | cleavage | looking_at_viewer | jacket | navel | simple_background | teeth | white_background | holding | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------|:-----------|:--------------------|:---------|:--------|:--------------------|:--------|:-------------------|:----------| | 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 |

mismatch-quest/SeeTRUE-Feedback

--- configs: - config_name: default data_files: - split: test path: "test/*" annotations_creators: - crowdsourced language: - en language_creators: - found license: - cc-by-4.0 multilinguality: - monolingual paperswithcode_id: seetrue-feedback pretty_name: SeeTRUE-feedback size_categories: - 1K<n<10K source_datasets: - original tags: - text-image-matching task_ids: [] extra_gated_prompt: "By clicking on “Access repository” below, you also agree that you are using it solely for research purposes, and that SeeTRUE-Feedback should be used as a *TEST SET*, not as a training set, and especially not to train commercial chatbots. Do not hessitate to contact briangordon@mail.tau.ac.il or yonatanbitton@google.com if you have questions about this license." --- # Dataset Card for SeeTRUE-Feedback - [Dataset Description](#dataset-description) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description The SeeTRUE-Feedback dataset is a diverse benchmark for the meta-evaluation of image-text matching/alignment feedback. It aims to overcome limitations in current benchmarks, which primarily focus on predicting a matching score between 0-1. SeeTRUE provides, for each row, the original caption, feedback related to text-image misalignment, and the caption+visual source of misalignments (including a bounding box for the visual misalignment). ### Languages The dataset supports English language. ## Dataset Structure ### Data Fields - image_caption - Caption associated with the image. - image_name: The name of the image file. - dataset_source: The source/origin dataset of the image. - id_in_source_dataset: The ID of the dataset where the row originates from. - image_url: An S3 link from which you can download the image. - human_feedback: Human-annotated feedbacks about image-text misalignment. - feedback: Summary of feedback consolidated into a single entry (Generated by LLM: PaLM-2) - feedback_clean: A parsed and "clean" version of `feedback` field. - caption_misalignment: Source of misalignment in the image caption. - visual_misalignment: Source of misalignment in the image. - bbox_GroundingDino: Detected visual misalignment bounding-box in GroundingDino output format. - bbox_PaLI: Detected visual misalignment bounding-box in PaLI output format. ### Data Splits SeeTRUE-Feedback contains a single split: TEST, and should not be used for training. ## Dataset Creation The dataset has been created by sourcing and matching images and text from multiple datasets. More information in the paper: <TODO> ### Licensing Information The dataset is under the CC-By 4.0 license. ### Citation Information TODO

HydraIndicLM/tamil_alpaca_dolly_51K

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: text dtype: string - name: system_prompt dtype: string splits: - name: train num_bytes: 287556653 num_examples: 51876 download_size: 84685617 dataset_size: 287556653 configs: - config_name: default data_files: - split: train path: data/train-* --- ## About This repo contains a 51K instruction set for Tamil, translated from Alpaca and Dolly. ## Citation If you find this repository useful, please consider giving 👏 and citing: ``` @misc{TamilAlpacaDolly, author = {Sambit Sekhar and Shantipriya Parida}, title = {Tamil Instruction Set Based on Alpaca and Dolly}, year = {2023}, publisher = {Hugging Face}, journal = {Hugging Face repository}, howpublished = {\url{https://huggingface.co/OdiaGenAI}}, } ```

open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml

--- pretty_name: Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v4-chatml dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [l3utterfly/mistral-7b-v0.1-layla-v4-chatml](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml)\ \ 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_l3utterfly__mistral-7b-v0.1-layla-v4-chatml\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-15T09:05:25.657589](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml/blob/main/results_2024-03-15T09-05-25.657589.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\": 0.637291875109227,\n\ \ \"acc_stderr\": 0.03233301893409507,\n \"acc_norm\": 0.6404117572756901,\n\ \ \"acc_norm_stderr\": 0.03298081985107007,\n \"mc1\": 0.2839657282741738,\n\ \ \"mc1_stderr\": 0.015785370858396725,\n \"mc2\": 0.4302819836285525,\n\ \ \"mc2_stderr\": 0.01426088687933726\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5827645051194539,\n \"acc_stderr\": 0.014409825518403079,\n\ \ \"acc_norm\": 0.6203071672354948,\n \"acc_norm_stderr\": 0.014182119866974872\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.630551682931687,\n\ \ \"acc_stderr\": 0.004816690123209757,\n \"acc_norm\": 0.8339972117108145,\n\ \ \"acc_norm_stderr\": 0.003713227064225392\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.046482319871173156\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6074074074074074,\n\ \ \"acc_stderr\": 0.0421850621536888,\n \"acc_norm\": 0.6074074074074074,\n\ \ \"acc_norm_stderr\": 0.0421850621536888\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.04923659639173309,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.04923659639173309\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\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.05021167315686779,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.05021167315686779\n \ \ },\n \"harness|hendrycksTest-college_computer_science|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_mathematics|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6184971098265896,\n\ \ \"acc_stderr\": 0.03703851193099521,\n \"acc_norm\": 0.6184971098265896,\n\ \ \"acc_norm_stderr\": 0.03703851193099521\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383887,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383887\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.77,\n \"acc_stderr\": 0.042295258468165065,\n \"acc_norm\": 0.77,\n\ \ \"acc_norm_stderr\": 0.042295258468165065\n },\n \"harness|hendrycksTest-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\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482758,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482758\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3941798941798942,\n \"acc_stderr\": 0.025167982333894143,\n \"\ acc_norm\": 0.3941798941798942,\n \"acc_norm_stderr\": 0.025167982333894143\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7677419354838709,\n\ \ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\ \ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5024630541871922,\n \"acc_stderr\": 0.035179450386910616,\n\ \ \"acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.035179450386910616\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.02886977846026705,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.02886977846026705\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8756476683937824,\n \"acc_stderr\": 0.02381447708659355,\n\ \ \"acc_norm\": 0.8756476683937824,\n \"acc_norm_stderr\": 0.02381447708659355\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6358974358974359,\n \"acc_stderr\": 0.024396672985094764,\n\ \ \"acc_norm\": 0.6358974358974359,\n \"acc_norm_stderr\": 0.024396672985094764\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.362962962962963,\n \"acc_stderr\": 0.029318203645206865,\n \ \ \"acc_norm\": 0.362962962962963,\n \"acc_norm_stderr\": 0.029318203645206865\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \ \ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.31788079470198677,\n \"acc_stderr\": 0.038020397601079024,\n \"\ acc_norm\": 0.31788079470198677,\n \"acc_norm_stderr\": 0.038020397601079024\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8238532110091743,\n \"acc_stderr\": 0.01633288239343138,\n \"\ acc_norm\": 0.8238532110091743,\n \"acc_norm_stderr\": 0.01633288239343138\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.803921568627451,\n \"acc_stderr\": 0.027865942286639318,\n \"\ acc_norm\": 0.803921568627451,\n \"acc_norm_stderr\": 0.027865942286639318\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7679324894514767,\n \"acc_stderr\": 0.027479744550808503,\n \ \ \"acc_norm\": 0.7679324894514767,\n \"acc_norm_stderr\": 0.027479744550808503\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159464,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159464\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8181818181818182,\n \"acc_stderr\": 0.03520893951097652,\n \"\ acc_norm\": 0.8181818181818182,\n \"acc_norm_stderr\": 0.03520893951097652\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243838,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243838\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7914110429447853,\n \"acc_stderr\": 0.031921934489347235,\n\ \ \"acc_norm\": 0.7914110429447853,\n \"acc_norm_stderr\": 0.031921934489347235\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\": 0.7961165048543689,\n \"acc_stderr\": 0.039891398595317706,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.039891398595317706\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8632478632478633,\n\ \ \"acc_stderr\": 0.022509033937077805,\n \"acc_norm\": 0.8632478632478633,\n\ \ \"acc_norm_stderr\": 0.022509033937077805\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.80970625798212,\n\ \ \"acc_stderr\": 0.014036945850381396,\n \"acc_norm\": 0.80970625798212,\n\ \ \"acc_norm_stderr\": 0.014036945850381396\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.684971098265896,\n \"acc_stderr\": 0.025009313790069713,\n\ \ \"acc_norm\": 0.684971098265896,\n \"acc_norm_stderr\": 0.025009313790069713\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.33854748603351953,\n\ \ \"acc_stderr\": 0.01582670009648135,\n \"acc_norm\": 0.33854748603351953,\n\ \ \"acc_norm_stderr\": 0.01582670009648135\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7483660130718954,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.7483660130718954,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7106109324758842,\n\ \ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\ \ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7283950617283951,\n \"acc_stderr\": 0.02474862449053737,\n\ \ \"acc_norm\": 0.7283950617283951,\n \"acc_norm_stderr\": 0.02474862449053737\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \ \ \"acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4654498044328553,\n\ \ \"acc_stderr\": 0.012739711554045706,\n \"acc_norm\": 0.4654498044328553,\n\ \ \"acc_norm_stderr\": 0.012739711554045706\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.02841820861940676,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.02841820861940676\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6748366013071896,\n \"acc_stderr\": 0.018950886770806308,\n \ \ \"acc_norm\": 0.6748366013071896,\n \"acc_norm_stderr\": 0.018950886770806308\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\": 0.7346938775510204,\n \"acc_stderr\": 0.0282638899437846,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.0282638899437846\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\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5481927710843374,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.5481927710843374,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.029913127232368036,\n\ \ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.029913127232368036\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2839657282741738,\n\ \ \"mc1_stderr\": 0.015785370858396725,\n \"mc2\": 0.4302819836285525,\n\ \ \"mc2_stderr\": 0.01426088687933726\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7932123125493291,\n \"acc_stderr\": 0.011382566829235802\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.5382865807429871,\n \ \ \"acc_stderr\": 0.013732048227016682\n }\n}\n```" repo_url: https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|arc:challenge|25_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-15T09-05-25.657589.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|gsm8k|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hellaswag|10_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-15T09-05-25.657589.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-management|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-15T09-05-25.657589.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|truthfulqa:mc|0_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-15T09-05-25.657589.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_15T09_05_25.657589 path: - '**/details_harness|winogrande|5_2024-03-15T09-05-25.657589.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-15T09-05-25.657589.parquet' - config_name: results data_files: - split: 2024_03_15T09_05_25.657589 path: - results_2024-03-15T09-05-25.657589.parquet - split: latest path: - results_2024-03-15T09-05-25.657589.parquet --- # Dataset Card for Evaluation run of l3utterfly/mistral-7b-v0.1-layla-v4-chatml  Dataset automatically created during the evaluation run of model [l3utterfly/mistral-7b-v0.1-layla-v4-chatml](https://huggingface.co/l3utterfly/mistral-7b-v0.1-layla-v4-chatml) 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_l3utterfly__mistral-7b-v0.1-layla-v4-chatml", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-15T09:05:25.657589](https://huggingface.co/datasets/open-llm-leaderboard/details_l3utterfly__mistral-7b-v0.1-layla-v4-chatml/blob/main/results_2024-03-15T09-05-25.657589.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": 0.637291875109227, "acc_stderr": 0.03233301893409507, "acc_norm": 0.6404117572756901, "acc_norm_stderr": 0.03298081985107007, "mc1": 0.2839657282741738, "mc1_stderr": 0.015785370858396725, "mc2": 0.4302819836285525, "mc2_stderr": 0.01426088687933726 }, "harness|arc:challenge|25": { "acc": 0.5827645051194539, "acc_stderr": 0.014409825518403079, "acc_norm": 0.6203071672354948, "acc_norm_stderr": 0.014182119866974872 }, "harness|hellaswag|10": { "acc": 0.630551682931687, "acc_stderr": 0.004816690123209757, "acc_norm": 0.8339972117108145, "acc_norm_stderr": 0.003713227064225392 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.0421850621536888, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.0421850621536888 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "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": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383887, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383887 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.77, "acc_stderr": 0.042295258468165065, "acc_norm": 0.77, "acc_norm_stderr": 0.042295258468165065 }, "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": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482758, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482758 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3941798941798942, "acc_stderr": 0.025167982333894143, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.025167982333894143 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7677419354838709, "acc_stderr": 0.024022256130308235, "acc_norm": 0.7677419354838709, "acc_norm_stderr": 0.024022256130308235 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5024630541871922, "acc_stderr": 0.035179450386910616, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.035179450386910616 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7929292929292929, "acc_stderr": 0.02886977846026705, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.02886977846026705 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.02381447708659355, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.02381447708659355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6358974358974359, "acc_stderr": 0.024396672985094764, "acc_norm": 0.6358974358974359, "acc_norm_stderr": 0.024396672985094764 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.362962962962963, "acc_stderr": 0.029318203645206865, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.029318203645206865 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6722689075630253, "acc_stderr": 0.03048991141767323, "acc_norm": 0.6722689075630253, "acc_norm_stderr": 0.03048991141767323 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.31788079470198677, "acc_stderr": 0.038020397601079024, "acc_norm": 0.31788079470198677, "acc_norm_stderr": 0.038020397601079024 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8238532110091743, "acc_stderr": 0.01633288239343138, "acc_norm": 0.8238532110091743, "acc_norm_stderr": 0.01633288239343138 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 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"acc_norm": 0.6454545454545455, "acc_norm_stderr": 0.045820048415054174 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7346938775510204, "acc_stderr": 0.0282638899437846, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.0282638899437846 }, "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": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-virology|5": { "acc": 0.5481927710843374, "acc_stderr": 0.03874371556587953, "acc_norm": 0.5481927710843374, "acc_norm_stderr": 0.03874371556587953 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8128654970760234, "acc_stderr": 0.029913127232368036, "acc_norm": 0.8128654970760234, "acc_norm_stderr": 0.029913127232368036 }, "harness|truthfulqa:mc|0": { "mc1": 0.2839657282741738, "mc1_stderr": 0.015785370858396725, "mc2": 0.4302819836285525, "mc2_stderr": 0.01426088687933726 }, "harness|winogrande|5": { "acc": 0.7932123125493291, "acc_stderr": 0.011382566829235802 }, "harness|gsm8k|5": { "acc": 0.5382865807429871, "acc_stderr": 0.013732048227016682 } } ``` ## 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]

gglab-ku/cogeval-human-SNLI-lalor

--- license: apache-2.0 ---

liuyanchen1015/MULTI_VALUE_mrpc_drop_aux_be_gonna

--- 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: 774 num_examples: 4 - name: train num_bytes: 3388 num_examples: 14 - name: validation num_bytes: 1008 num_examples: 4 download_size: 13603 dataset_size: 5170 --- # Dataset Card for "MULTI_VALUE_mrpc_drop_aux_be_gonna" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

bloyal/deeploc

--- license: cc-by-4.0 --- # DeepLoc-2.0 Training Data Dataset from https://services.healthtech.dtu.dk/services/DeepLoc-2.0/ used to train the DeepLoc-2.0 model. ## Data preparation Data downloaded and processed using the following Python script: ```python import pandas as pd df = pd.read_csv('https://services.healthtech.dtu.dk/services/DeepLoc-2.0/data/Swissprot_Train_Validation_dataset.csv').drop(['Unnamed: 0', 'Partition'], axis=1) df['labels'] = df[['Cell membrane', 'Cytoplasm','Endoplasmic reticulum', 'Extracellular', 'Golgi apparatus', 'Lysosome/Vacuole', 'Mitochondrion', 'Nucleus', 'Peroxisome', 'Plastid']].astype('float32').values.tolist() df['Membrane'] = df['Membrane'].astype('float32') df = df[['Kingdom', 'ACC', 'Sequence','Membrane','labels']] train = df.sample(frac=0.8) df = df.drop(train.index) val = df.sample(frac=0.5) test = df.drop(val.index) train = train.reset_index(drop=True) val = val.reset_index(drop=True) test = test.reset_index(drop=True) train.to_parquet('deeploc-train.parquet', index=False) val.to_parquet('deploc-val.parquet', index=False) test.to_parquet('deeploc-test.parquet', index=False) ``` ## Labels {'Cell membrane': 0, 'Cytoplasm': 1, 'Endoplasmic reticulum': 2, 'Extracellular': 3, 'Golgi apparatus': 4, 'Lysosome/Vacuole': 5, 'Mitochondrion': 6, 'Nucleus': 7, 'Peroxisome': 8, 'Plastid': 9} ## Citation **DeepLoc-2.0:** ``` Vineet Thumuluri and others, DeepLoc 2.0: multi-label subcellular localization prediction using protein language models, Nucleic Acids Research, Volume 50, Issue W1, 5 July 2022, Pages W228–W234, https://doi.org/10.1093/nar/gkac278 ``` The DeepLoc data is a derivative of the UniProt dataset: **UniProt** ``` The UniProt Consortium UniProt: the Universal Protein Knowledgebase in 2023 Nucleic Acids Res. 51:D523–D531 (2023) ```

Cognitive-Lab/Indic-MMLU

--- configs: - config_name: kn data_files: - split: test path: kn/test.json - split: validation path: kn/validation.json - split: dev path: kn/dev.json - config_name: hi data_files: - split: test path: hi/test.json - split: validation path: hi/validation.json - split: dev path: hi/dev.json - config_name: ta data_files: - split: test path: ta/test.json - split: validation path: ta/validation.json - split: dev path: ta/dev.json - config_name: te data_files: - split: test path: te/test.json - split: validation path: te/validation.json - split: dev path: te/dev.json - config_name: ml data_files: - split: test path: ml/test.json - split: validation path: ml/validation.json - split: dev path: ml/dev.json - config_name: gu data_files: - split: test path: gu/test.json - split: validation path: gu/validation.json - split: dev path: gu/dev.json - config_name: mr data_files: - split: test path: mr/test.json - split: validation path: mr/validation.json - split: dev path: mr/dev.json --- # MMLU Translated Citations: ``` @article{hendryckstest2021, title={Measuring Massive Multitask Language Understanding}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } @article{hendrycks2021ethics, title={Aligning AI With Shared Human Values}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } ``` Contributions:\ Thanks to [@Srinidhi9113](https://huggingface.co/Srinidhi9113) for adding the dataset.

TVRRaviteja/Mental-Health-Data

--- language: - en --- # Mental Health Queries and Personality Dataset ## Overview This dataset encompasses a collection of mental health queries paired with personality scores and responses generated by a Large Language Model (LLM). It aims to provide insights into the interplay between personality traits and mental health inquiries, facilitating research in personalized conversational agents and mental health support systems. ## Dataset Description Each record in the dataset contains: - A query from a Mental Health user. - A personality score across five types: Agreeableness, Extraversion, Openness, Conscientiousness, and Neuroticism. - A context interpretation based on the user's personality. - A tailored response from the Assistant. ## Potential Uses The dataset is particularly useful for researchers and developers working on: - Personalized conversational AI in mental health. - The impact of personality traits on mental health support. - Enhancing natural language understanding and response generation in the context of mental health. ## Access and Use This dataset is hosted on Hugging Face Datasets, available for academic and research purposes. Users are encouraged to cite the dataset when used in their research or projects. --- license: mit ---

TalTechNLP/dialogsum_ee

--- license: cc-by-4.0 dataset_info: features: - name: id dtype: string - name: dialogue dtype: string - name: summary dtype: string - name: topic dtype: string - name: en_dialogue dtype: string - name: en_summary dtype: string splits: - name: train num_bytes: 22666234 num_examples: 12460 - name: validation num_bytes: 881912 num_examples: 500 - name: test num_bytes: 2703111 num_examples: 1500 download_size: 14384437 dataset_size: 26251257 ---

subAxiom/central-bank-digital-currencies

--- license: cc task_categories: - text-generation language: - en tags: - finance pretty_name: Central Bank Digital Currencies size_categories: - n<1K --- # Dataset Card for Dataset Name ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [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]

chiragtubakad/flan-test-final

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: test num_bytes: 1196001.0504610357 num_examples: 1000 download_size: 552002 dataset_size: 1196001.0504610357 --- # Dataset Card for "flan-test-final" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

zhangshuoming/c_x86_exebench_json_cleaned

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 749238025.3045925 num_examples: 701744 download_size: 209658460 dataset_size: 749238025.3045925 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "c_x86_exebench_json_cleaned" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

pankajmathur/alpaca_orca

--- license: cc-by-nc-sa-4.0 task_categories: - text-generation language: - en size_categories: - 10K<n<100K --- Explain tuned Alpaca dataset ~52K created using approaches from Orca Research Paper. We leverage all of the 15 system instructions provided in Orca Research Paper. to generate custom datasets, in contrast to vanilla instruction tuning approaches used by original datasets. This helps student models like [orca_mini_13b](https://huggingface.co/psmathur/orca_mini_13b) to learn thought process from teacher model, which is ChatGPT (gpt-3.5-turbo-0301 version). Please see how the **System** prompt is added before each **instruction**.

thercyl/NVDA

--- dataset_info: features: - name: 'Unnamed: 0' dtype: float64 - name: Ticker dtype: string - name: Year dtype: string - name: Text dtype: string - name: Embedding dtype: string splits: - name: train num_bytes: 68921754 num_examples: 1979 download_size: 40675215 dataset_size: 68921754 --- # Dataset Card for "NVDA" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

joey234/mmlu-computer_security-neg-answer

--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: neg_answer dtype: string splits: - name: test num_bytes: 31239 num_examples: 100 download_size: 22397 dataset_size: 31239 --- # Dataset Card for "mmlu-computer_security-neg-answer" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

lowo/ncep-TestData1

--- license: mit ---

Moatazz/First

--- task_categories: - text-classification language: - en pretty_name: Trial size_categories: - n<1K ---

tner/bc5cdr

--- language: - en license: - other multilinguality: - monolingual size_categories: - 10K<n<100K task_categories: - token-classification task_ids: - named-entity-recognition pretty_name: BioCreative V CDR --- # Dataset Card for "tner/bc5cdr" ## Dataset Description - **Repository:** [T-NER](https://github.com/asahi417/tner) - **Paper:** [https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true](https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true) - **Dataset:** BioCreative V CDR - **Domain:** Biomedical - **Number of Entity:** 2 ### Dataset Summary BioCreative V CDR NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. The original dataset consists of long documents which cannot be fed on LM because of the length, so we split them into sentences to reduce their size. - Entity Types: `Chemical`, `Disease` ## Dataset Structure ### Data Instances An example of `train` looks as follows. ``` { 'tags': [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0], 'tokens': ['Fasciculations', 'in', 'six', 'areas', 'of', 'the', 'body', 'were', 'scored', 'from', '0', 'to', '3', 'and', 'summated', 'as', 'a', 'total', 'fasciculation', 'score', '.'] } ``` ### Label ID The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/bc5cdr/raw/main/dataset/label.json). ```python { "O": 0, "B-Chemical": 1, "B-Disease": 2, "I-Disease": 3, "I-Chemical": 4 } ``` ### Data Splits | name |train|validation|test| |---------|----:|---------:|---:| |bc5cdr|5228| 5330|5865| ### Citation Information ``` @article{wei2016assessing, title={Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task}, author={Wei, Chih-Hsuan and Peng, Yifan and Leaman, Robert and Davis, Allan Peter and Mattingly, Carolyn J and Li, Jiao and Wiegers, Thomas C and Lu, Zhiyong}, journal={Database}, volume={2016}, year={2016}, publisher={Oxford Academic} } ```

davanstrien/on_the_books

--- license: cc-by-3.0 language: - en tags: - lam pretty_name: On the Books --- # Dataset Card for Dataset Name ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [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]

andrewrreed/fewnerd-person-names-augmented

--- dataset_info: features: - name: tokens sequence: string - name: ner_tags sequence: class_label: names: '0': O '1': B-PER '2': I-PER splits: - name: train num_bytes: 42959061.57005247 num_examples: 122254 - name: validation num_bytes: 4086233.0513204616 num_examples: 20417 - name: test num_bytes: 8454146.29895592 num_examples: 32293 download_size: 14382598 dataset_size: 55499440.92032885 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

shidowake/oasst2_answers_from_g-ronimo_subset_split_0

--- dataset_info: features: - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 7084599.121609153 num_examples: 2710 download_size: 3550248 dataset_size: 7084599.121609153 configs: - config_name: default data_files: - split: train path: data/train-* ---

niizam/fgo-story

--- license: cc-by-2.0 task_categories: - translation language: - en - ja - id tags: - story - conversation size_categories: - 1M<n<10M ---

lim4349/origin_added_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: 83769368 num_examples: 57923 - name: validation num_bytes: 9244735 num_examples: 6436 download_size: 57373216 dataset_size: 93014103 --- # Dataset Card for "origin_added_korquad" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Nexdata/Russian_Speech_Data_by_Mobile_Phone

--- YAML tags: - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging --- # Dataset Card for Nexdata/Russian_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://www.nexdata.ai/datasets/976?source=Huggingface - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary 1960 Russian native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, in-vehicle and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/976?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Russian ## 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 Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions

harshgulati/guanaco-llama2-1k

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1654448 num_examples: 1000 download_size: 966692 dataset_size: 1654448 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA

--- pretty_name: Evaluation run of quantumaikr/QuantumLM-llama2-70B-Korean-LoRA dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [quantumaikr/QuantumLM-llama2-70B-Korean-LoRA](https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA)\ \ 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_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-30T07:53:24.183560](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA/blob/main/results_2023-08-30T07%3A53%3A24.183560.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\": 0.6934168799483462,\n\ \ \"acc_stderr\": 0.03115919348812645,\n \"acc_norm\": 0.6971494359890498,\n\ \ \"acc_norm_stderr\": 0.031131669600877022,\n \"mc1\": 0.401468788249694,\n\ \ \"mc1_stderr\": 0.017160273901693654,\n \"mc2\": 0.5608488880093394,\n\ \ \"mc2_stderr\": 0.014874770245335572\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6749146757679181,\n \"acc_stderr\": 0.013688147309729119,\n\ \ \"acc_norm\": 0.7056313993174061,\n \"acc_norm_stderr\": 0.013318528460539422\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6743676558454491,\n\ \ \"acc_stderr\": 0.004676529200753001,\n \"acc_norm\": 0.8638717386974706,\n\ \ \"acc_norm_stderr\": 0.0034222387022263645\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5925925925925926,\n\ \ \"acc_stderr\": 0.04244633238353228,\n \"acc_norm\": 0.5925925925925926,\n\ \ \"acc_norm_stderr\": 0.04244633238353228\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.8289473684210527,\n \"acc_stderr\": 0.03064360707167709,\n\ \ \"acc_norm\": 0.8289473684210527,\n \"acc_norm_stderr\": 0.03064360707167709\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7245283018867924,\n \"acc_stderr\": 0.027495663683724057,\n\ \ \"acc_norm\": 0.7245283018867924,\n \"acc_norm_stderr\": 0.027495663683724057\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.031164899666948617,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.031164899666948617\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n\ \ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.04810840148082635,\n\ \ \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.04810840148082635\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.73,\n \"acc_stderr\": 0.04461960433384739,\n \"acc_norm\": 0.73,\n\ \ \"acc_norm_stderr\": 0.04461960433384739\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6808510638297872,\n \"acc_stderr\": 0.030472973363380045,\n\ \ \"acc_norm\": 0.6808510638297872,\n \"acc_norm_stderr\": 0.030472973363380045\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4473684210526316,\n\ \ \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.4473684210526316,\n\ \ \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5862068965517241,\n \"acc_stderr\": 0.04104269211806232,\n\ \ \"acc_norm\": 0.5862068965517241,\n \"acc_norm_stderr\": 0.04104269211806232\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.43915343915343913,\n \"acc_stderr\": 0.02555992055053101,\n \"\ acc_norm\": 0.43915343915343913,\n \"acc_norm_stderr\": 0.02555992055053101\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\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8451612903225807,\n\ \ \"acc_stderr\": 0.020579287326583227,\n \"acc_norm\": 0.8451612903225807,\n\ \ \"acc_norm_stderr\": 0.020579287326583227\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5320197044334976,\n \"acc_stderr\": 0.03510766597959217,\n\ \ \"acc_norm\": 0.5320197044334976,\n \"acc_norm_stderr\": 0.03510766597959217\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\"\ : 0.73,\n \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8242424242424242,\n \"acc_stderr\": 0.02972094300622445,\n\ \ \"acc_norm\": 0.8242424242424242,\n \"acc_norm_stderr\": 0.02972094300622445\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8636363636363636,\n \"acc_stderr\": 0.024450155973189835,\n \"\ acc_norm\": 0.8636363636363636,\n \"acc_norm_stderr\": 0.024450155973189835\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9430051813471503,\n \"acc_stderr\": 0.01673108529360756,\n\ \ \"acc_norm\": 0.9430051813471503,\n \"acc_norm_stderr\": 0.01673108529360756\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.7256410256410256,\n \"acc_stderr\": 0.022622765767493225,\n\ \ \"acc_norm\": 0.7256410256410256,\n \"acc_norm_stderr\": 0.022622765767493225\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.35185185185185186,\n \"acc_stderr\": 0.029116617606083015,\n \ \ \"acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.029116617606083015\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.7857142857142857,\n \"acc_stderr\": 0.026653531596715484,\n\ \ \"acc_norm\": 0.7857142857142857,\n \"acc_norm_stderr\": 0.026653531596715484\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.45695364238410596,\n \"acc_stderr\": 0.04067325174247443,\n \"\ acc_norm\": 0.45695364238410596,\n \"acc_norm_stderr\": 0.04067325174247443\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8844036697247707,\n \"acc_stderr\": 0.013708749534172636,\n \"\ acc_norm\": 0.8844036697247707,\n \"acc_norm_stderr\": 0.013708749534172636\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5879629629629629,\n \"acc_stderr\": 0.03356787758160831,\n \"\ acc_norm\": 0.5879629629629629,\n \"acc_norm_stderr\": 0.03356787758160831\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9068627450980392,\n \"acc_stderr\": 0.020397853969427,\n \"acc_norm\"\ : 0.9068627450980392,\n \"acc_norm_stderr\": 0.020397853969427\n },\n\ \ \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\":\ \ 0.8734177215189873,\n \"acc_stderr\": 0.02164419572795517,\n \"\ acc_norm\": 0.8734177215189873,\n \"acc_norm_stderr\": 0.02164419572795517\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7757847533632287,\n\ \ \"acc_stderr\": 0.027991534258519517,\n \"acc_norm\": 0.7757847533632287,\n\ \ \"acc_norm_stderr\": 0.027991534258519517\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8320610687022901,\n \"acc_stderr\": 0.032785485373431386,\n\ \ \"acc_norm\": 0.8320610687022901,\n \"acc_norm_stderr\": 0.032785485373431386\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8842975206611571,\n \"acc_stderr\": 0.029199802455622814,\n \"\ acc_norm\": 0.8842975206611571,\n \"acc_norm_stderr\": 0.029199802455622814\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8518518518518519,\n\ \ \"acc_stderr\": 0.03434300243631,\n \"acc_norm\": 0.8518518518518519,\n\ \ \"acc_norm_stderr\": 0.03434300243631\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\": 0.5267857142857143,\n\ \ \"acc_stderr\": 0.047389751192741546,\n \"acc_norm\": 0.5267857142857143,\n\ \ \"acc_norm_stderr\": 0.047389751192741546\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.0398913985953177,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.0398913985953177\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n\ \ \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n\ \ \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8531289910600255,\n\ \ \"acc_stderr\": 0.012658201736147278,\n \"acc_norm\": 0.8531289910600255,\n\ \ \"acc_norm_stderr\": 0.012658201736147278\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7687861271676301,\n \"acc_stderr\": 0.022698657167855713,\n\ \ \"acc_norm\": 0.7687861271676301,\n \"acc_norm_stderr\": 0.022698657167855713\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.5094972067039106,\n\ \ \"acc_stderr\": 0.01671948464334877,\n \"acc_norm\": 0.5094972067039106,\n\ \ \"acc_norm_stderr\": 0.01671948464334877\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7679738562091504,\n \"acc_stderr\": 0.024170840879340873,\n\ \ \"acc_norm\": 0.7679738562091504,\n \"acc_norm_stderr\": 0.024170840879340873\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7588424437299035,\n\ \ \"acc_stderr\": 0.024296594034763426,\n \"acc_norm\": 0.7588424437299035,\n\ \ \"acc_norm_stderr\": 0.024296594034763426\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8055555555555556,\n \"acc_stderr\": 0.022021366100220194,\n\ \ \"acc_norm\": 0.8055555555555556,\n \"acc_norm_stderr\": 0.022021366100220194\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5567375886524822,\n \"acc_stderr\": 0.02963483847376601,\n \ \ \"acc_norm\": 0.5567375886524822,\n \"acc_norm_stderr\": 0.02963483847376601\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5560625814863103,\n\ \ \"acc_stderr\": 0.012689708167787677,\n \"acc_norm\": 0.5560625814863103,\n\ \ \"acc_norm_stderr\": 0.012689708167787677\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7536764705882353,\n \"acc_stderr\": 0.02617343857052,\n\ \ \"acc_norm\": 0.7536764705882353,\n \"acc_norm_stderr\": 0.02617343857052\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7630718954248366,\n \"acc_stderr\": 0.01720166216978977,\n \ \ \"acc_norm\": 0.7630718954248366,\n \"acc_norm_stderr\": 0.01720166216978977\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7181818181818181,\n\ \ \"acc_stderr\": 0.04309118709946458,\n \"acc_norm\": 0.7181818181818181,\n\ \ \"acc_norm_stderr\": 0.04309118709946458\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7755102040816326,\n \"acc_stderr\": 0.0267114305555384,\n\ \ \"acc_norm\": 0.7755102040816326,\n \"acc_norm_stderr\": 0.0267114305555384\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8955223880597015,\n\ \ \"acc_stderr\": 0.021628920516700643,\n \"acc_norm\": 0.8955223880597015,\n\ \ \"acc_norm_stderr\": 0.021628920516700643\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.93,\n \"acc_stderr\": 0.0256432399976243,\n \ \ \"acc_norm\": 0.93,\n \"acc_norm_stderr\": 0.0256432399976243\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.536144578313253,\n\ \ \"acc_stderr\": 0.038823108508905954,\n \"acc_norm\": 0.536144578313253,\n\ \ \"acc_norm_stderr\": 0.038823108508905954\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.02709729011807082,\n\ \ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.02709729011807082\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.401468788249694,\n\ \ \"mc1_stderr\": 0.017160273901693654,\n \"mc2\": 0.5608488880093394,\n\ \ \"mc2_stderr\": 0.014874770245335572\n }\n}\n```" repo_url: https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA 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_30T07_53_24.183560 path: - '**/details_harness|arc:challenge|25_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hellaswag|10_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-30T07:53:24.183560.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-management|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T07:53:24.183560.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_30T07_53_24.183560 path: - '**/details_harness|truthfulqa:mc|0_2023-08-30T07:53:24.183560.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-30T07:53:24.183560.parquet' - config_name: results data_files: - split: 2023_08_30T07_53_24.183560 path: - results_2023-08-30T07:53:24.183560.parquet - split: latest path: - results_2023-08-30T07:53:24.183560.parquet --- # Dataset Card for Evaluation run of quantumaikr/QuantumLM-llama2-70B-Korean-LoRA ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA - **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 [quantumaikr/QuantumLM-llama2-70B-Korean-LoRA](https://huggingface.co/quantumaikr/QuantumLM-llama2-70B-Korean-LoRA) 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_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-30T07:53:24.183560](https://huggingface.co/datasets/open-llm-leaderboard/details_quantumaikr__QuantumLM-llama2-70B-Korean-LoRA/blob/main/results_2023-08-30T07%3A53%3A24.183560.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": 0.6934168799483462, "acc_stderr": 0.03115919348812645, "acc_norm": 0.6971494359890498, "acc_norm_stderr": 0.031131669600877022, "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5608488880093394, "mc2_stderr": 0.014874770245335572 }, "harness|arc:challenge|25": { "acc": 0.6749146757679181, "acc_stderr": 0.013688147309729119, "acc_norm": 0.7056313993174061, "acc_norm_stderr": 0.013318528460539422 }, "harness|hellaswag|10": { "acc": 0.6743676558454491, "acc_stderr": 0.004676529200753001, "acc_norm": 0.8638717386974706, "acc_norm_stderr": 0.0034222387022263645 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5925925925925926, "acc_stderr": 0.04244633238353228, "acc_norm": 0.5925925925925926, "acc_norm_stderr": 0.04244633238353228 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8289473684210527, "acc_stderr": 0.03064360707167709, "acc_norm": 0.8289473684210527, "acc_norm_stderr": 0.03064360707167709 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7245283018867924, "acc_stderr": 0.027495663683724057, "acc_norm": 0.7245283018867924, "acc_norm_stderr": 0.027495663683724057 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8333333333333334, "acc_stderr": 0.031164899666948617, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.031164899666948617 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082635, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082635 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.73, "acc_stderr": 0.04461960433384739, "acc_norm": 0.73, "acc_norm_stderr": 0.04461960433384739 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6808510638297872, "acc_stderr": 0.030472973363380045, "acc_norm": 0.6808510638297872, "acc_norm_stderr": 0.030472973363380045 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4473684210526316, "acc_stderr": 0.04677473004491199, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.04677473004491199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5862068965517241, "acc_stderr": 0.04104269211806232, "acc_norm": 0.5862068965517241, "acc_norm_stderr": 0.04104269211806232 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.43915343915343913, "acc_stderr": 0.02555992055053101, "acc_norm": 0.43915343915343913, "acc_norm_stderr": 0.02555992055053101 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8451612903225807, "acc_stderr": 0.020579287326583227, "acc_norm": 0.8451612903225807, "acc_norm_stderr": 0.020579287326583227 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5320197044334976, "acc_stderr": 0.03510766597959217, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.03510766597959217 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8242424242424242, "acc_stderr": 0.02972094300622445, "acc_norm": 0.8242424242424242, "acc_norm_stderr": 0.02972094300622445 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9430051813471503, "acc_stderr": 0.01673108529360756, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.01673108529360756 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7256410256410256, "acc_stderr": 0.022622765767493225, "acc_norm": 0.7256410256410256, "acc_norm_stderr": 0.022622765767493225 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.029116617606083015, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.029116617606083015 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7857142857142857, "acc_stderr": 0.026653531596715484, "acc_norm": 0.7857142857142857, "acc_norm_stderr": 0.026653531596715484 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.45695364238410596, "acc_stderr": 0.04067325174247443, "acc_norm": 0.45695364238410596, "acc_norm_stderr": 0.04067325174247443 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8844036697247707, "acc_stderr": 0.013708749534172636, "acc_norm": 0.8844036697247707, "acc_norm_stderr": 0.013708749534172636 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5879629629629629, "acc_stderr": 0.03356787758160831, "acc_norm": 0.5879629629629629, "acc_norm_stderr": 0.03356787758160831 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9068627450980392, "acc_stderr": 0.020397853969427, "acc_norm": 0.9068627450980392, "acc_norm_stderr": 0.020397853969427 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8734177215189873, "acc_stderr": 0.02164419572795517, "acc_norm": 0.8734177215189873, "acc_norm_stderr": 0.02164419572795517 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7757847533632287, "acc_stderr": 0.027991534258519517, "acc_norm": 0.7757847533632287, "acc_norm_stderr": 0.027991534258519517 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8320610687022901, "acc_stderr": 0.032785485373431386, "acc_norm": 0.8320610687022901, "acc_norm_stderr": 0.032785485373431386 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8842975206611571, "acc_stderr": 0.029199802455622814, "acc_norm": 0.8842975206611571, "acc_norm_stderr": 0.029199802455622814 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8518518518518519, "acc_stderr": 0.03434300243631, "acc_norm": 0.8518518518518519, "acc_norm_stderr": 0.03434300243631 }, "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": 0.5267857142857143, "acc_stderr": 0.047389751192741546, "acc_norm": 0.5267857142857143, "acc_norm_stderr": 0.047389751192741546 }, "harness|hendrycksTest-management|5": { "acc": 0.7961165048543689, "acc_stderr": 0.0398913985953177, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.0398913985953177 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8717948717948718, "acc_stderr": 0.02190190511507333, "acc_norm": 0.8717948717948718, "acc_norm_stderr": 0.02190190511507333 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8531289910600255, "acc_stderr": 0.012658201736147278, "acc_norm": 0.8531289910600255, "acc_norm_stderr": 0.012658201736147278 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7687861271676301, "acc_stderr": 0.022698657167855713, "acc_norm": 0.7687861271676301, "acc_norm_stderr": 0.022698657167855713 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.5094972067039106, "acc_stderr": 0.01671948464334877, "acc_norm": 0.5094972067039106, "acc_norm_stderr": 0.01671948464334877 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7679738562091504, "acc_stderr": 0.024170840879340873, "acc_norm": 0.7679738562091504, "acc_norm_stderr": 0.024170840879340873 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7588424437299035, "acc_stderr": 0.024296594034763426, "acc_norm": 0.7588424437299035, "acc_norm_stderr": 0.024296594034763426 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8055555555555556, "acc_stderr": 0.022021366100220194, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.022021366100220194 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5567375886524822, "acc_stderr": 0.02963483847376601, "acc_norm": 0.5567375886524822, "acc_norm_stderr": 0.02963483847376601 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5560625814863103, "acc_stderr": 0.012689708167787677, "acc_norm": 0.5560625814863103, "acc_norm_stderr": 0.012689708167787677 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7536764705882353, "acc_stderr": 0.02617343857052, "acc_norm": 0.7536764705882353, "acc_norm_stderr": 0.02617343857052 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7630718954248366, "acc_stderr": 0.01720166216978977, "acc_norm": 0.7630718954248366, "acc_norm_stderr": 0.01720166216978977 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7181818181818181, "acc_stderr": 0.04309118709946458, "acc_norm": 0.7181818181818181, "acc_norm_stderr": 0.04309118709946458 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7755102040816326, "acc_stderr": 0.0267114305555384, "acc_norm": 0.7755102040816326, "acc_norm_stderr": 0.0267114305555384 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8955223880597015, "acc_stderr": 0.021628920516700643, "acc_norm": 0.8955223880597015, "acc_norm_stderr": 0.021628920516700643 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.93, "acc_stderr": 0.0256432399976243, "acc_norm": 0.93, "acc_norm_stderr": 0.0256432399976243 }, "harness|hendrycksTest-virology|5": { "acc": 0.536144578313253, "acc_stderr": 0.038823108508905954, "acc_norm": 0.536144578313253, "acc_norm_stderr": 0.038823108508905954 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8538011695906432, "acc_stderr": 0.02709729011807082, "acc_norm": 0.8538011695906432, "acc_norm_stderr": 0.02709729011807082 }, "harness|truthfulqa:mc|0": { "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5608488880093394, "mc2_stderr": 0.014874770245335572 } } ``` ### 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]

bigscience-data/roots_zh_ted_talks_iwslt

--- language: zh license: cc-by-nc-nd-4.0 extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience Ethical Charter. The charter can be found at: https://hf.co/spaces/bigscience/ethical-charter' extra_gated_fields: I have read and agree to abide by the BigScience Ethical Charter: checkbox --- ROOTS Subset: roots_zh_ted_talks_iwslt # WIT Ted Talks - Dataset uid: `ted_talks_iwslt` ### Description The Web Inventory Talk is a collection of the original Ted talks and their translated version. The translations are available in more than 109+ languages, though the distribution is not uniform. ### Homepage https://github.com/huggingface/datasets/blob/master/datasets/ted_talks_iwslt/README.md ### Licensing - open license - cc-by-nc-4.0: Creative Commons Attribution Non Commercial 4.0 International TED makes its collection of video recordings and transcripts of talks available under the Creative Commons BY-NC-ND license (look here). WIT3 acknowledges the authorship of TED talks (BY condition) and does not redistribute transcripts for commercial purposes (NC). As regards the integrity of the work (ND), WIT3 only changes the format of the container, while preserving the original contents. WIT3 aims to support research on human language processing as well as the diffusion of TED Talks! ### Speaker Locations - Southern Europe - Italy ### Sizes - 0.0305 % of total - 0.0736 % of ar - 0.2002 % of pt - 0.0128 % of zh - 0.2236 % of vi - 0.0330 % of fr - 0.0545 % of es - 0.0122 % of en - 0.3704 % of id - 0.0373 % of indic-hi - 0.0330 % of indic-ta - 0.1393 % of indic-mr - 0.0305 % of ca - 0.1179 % of indic-ur - 0.0147 % of indic-bn - 0.0240 % of indic-ml - 0.0244 % of indic-te - 0.0503 % of indic-gu - 0.0211 % of indic-kn - 0.0274 % of eu - 0.0023 % of indic-as - 0.0001 % of indic-pa ### BigScience processing steps #### Filters applied to: ar - dedup_document - dedup_template_soft - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: pt - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: zh - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: vi - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: fr - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: es - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: en - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: id - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-hi - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-ta - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-mr - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: ca - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_1024 #### Filters applied to: indic-ur - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-bn - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-ml - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-te - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-gu - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: indic-kn - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300 #### Filters applied to: eu - dedup_document - filter_remove_empty_docs #### Filters applied to: indic-as - dedup_document - filter_remove_empty_docs #### Filters applied to: indic-pa - dedup_document - filter_remove_empty_docs - filter_small_docs_bytes_300

japanese-asr/whisper_transcriptions.reazonspeech.all_12

--- 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: 30338653855.0 num_examples: 266555 download_size: 30101931897 dataset_size: 30338653855.0 configs: - config_name: all data_files: - split: train path: all/train-* ---

open-llm-leaderboard/details_NoIdeaLand__test-4k-fn

--- pretty_name: Evaluation run of NoIdeaLand/test-4k-fn dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NoIdeaLand/test-4k-fn](https://huggingface.co/NoIdeaLand/test-4k-fn) 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_NoIdeaLand__test-4k-fn\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-10-01T16:31:47.992543](https://huggingface.co/datasets/open-llm-leaderboard/details_NoIdeaLand__test-4k-fn/blob/main/results_2023-10-01T16-31-47.992543.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\": 0.2795859427889157,\n\ \ \"acc_stderr\": 0.03244654146727709,\n \"acc_norm\": 0.283431508310814,\n\ \ \"acc_norm_stderr\": 0.032446107426975616,\n \"mc1\": 0.23255813953488372,\n\ \ \"mc1_stderr\": 0.014789157531080512,\n \"mc2\": 0.38860179255046867,\n\ \ \"mc2_stderr\": 0.014093255696402213\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.35665529010238906,\n \"acc_stderr\": 0.01399805690262019,\n\ \ \"acc_norm\": 0.3993174061433447,\n \"acc_norm_stderr\": 0.014312094557946704\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4971121290579566,\n\ \ \"acc_stderr\": 0.004989698183207823,\n \"acc_norm\": 0.6813383788090022,\n\ \ \"acc_norm_stderr\": 0.004650052150094427\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816508,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816508\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.23703703703703705,\n\ \ \"acc_stderr\": 0.03673731683969506,\n \"acc_norm\": 0.23703703703703705,\n\ \ \"acc_norm_stderr\": 0.03673731683969506\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.18421052631578946,\n \"acc_stderr\": 0.0315469804508223,\n\ \ \"acc_norm\": 0.18421052631578946,\n \"acc_norm_stderr\": 0.0315469804508223\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.34,\n\ \ \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n \ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.29056603773584905,\n \"acc_stderr\": 0.027943219989337145,\n\ \ \"acc_norm\": 0.29056603773584905,\n \"acc_norm_stderr\": 0.027943219989337145\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.037455547914624555,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.037455547914624555\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"acc\"\ : 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.21,\n\ \ \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-college_mathematics|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_medicine|5\": {\n \"acc\": 0.2543352601156069,\n\ \ \"acc_stderr\": 0.0332055644308557,\n \"acc_norm\": 0.2543352601156069,\n\ \ \"acc_norm_stderr\": 0.0332055644308557\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617746,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617746\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.3021276595744681,\n \"acc_stderr\": 0.030017554471880557,\n\ \ \"acc_norm\": 0.3021276595744681,\n \"acc_norm_stderr\": 0.030017554471880557\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.21929824561403508,\n\ \ \"acc_stderr\": 0.03892431106518754,\n \"acc_norm\": 0.21929824561403508,\n\ \ \"acc_norm_stderr\": 0.03892431106518754\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.3103448275862069,\n \"acc_stderr\": 0.038552896163789485,\n\ \ \"acc_norm\": 0.3103448275862069,\n \"acc_norm_stderr\": 0.038552896163789485\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.24603174603174602,\n \"acc_stderr\": 0.022182037202948365,\n \"\ acc_norm\": 0.24603174603174602,\n \"acc_norm_stderr\": 0.022182037202948365\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.03670066451047182,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.03670066451047182\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.24838709677419354,\n\ \ \"acc_stderr\": 0.024580028921481003,\n \"acc_norm\": 0.24838709677419354,\n\ \ \"acc_norm_stderr\": 0.024580028921481003\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.2019704433497537,\n \"acc_stderr\": 0.02824735012218027,\n\ \ \"acc_norm\": 0.2019704433497537,\n \"acc_norm_stderr\": 0.02824735012218027\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.2727272727272727,\n \"acc_stderr\": 0.0347769116216366,\n\ \ \"acc_norm\": 0.2727272727272727,\n \"acc_norm_stderr\": 0.0347769116216366\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.23232323232323232,\n \"acc_stderr\": 0.030088629490217487,\n \"\ acc_norm\": 0.23232323232323232,\n \"acc_norm_stderr\": 0.030088629490217487\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.3471502590673575,\n \"acc_stderr\": 0.03435696168361355,\n\ \ \"acc_norm\": 0.3471502590673575,\n \"acc_norm_stderr\": 0.03435696168361355\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.31025641025641026,\n \"acc_stderr\": 0.023454674889404288,\n\ \ \"acc_norm\": 0.31025641025641026,\n \"acc_norm_stderr\": 0.023454674889404288\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\": 0.25630252100840334,\n \"acc_stderr\": 0.02835962087053395,\n\ \ \"acc_norm\": 0.25630252100840334,\n \"acc_norm_stderr\": 0.02835962087053395\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.036313298039696525,\n \"\ acc_norm\": 0.271523178807947,\n \"acc_norm_stderr\": 0.036313298039696525\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.24036697247706423,\n \"acc_stderr\": 0.01832060732096407,\n \"\ acc_norm\": 0.24036697247706423,\n \"acc_norm_stderr\": 0.01832060732096407\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.26851851851851855,\n \"acc_stderr\": 0.030225226160012397,\n \"\ acc_norm\": 0.26851851851851855,\n \"acc_norm_stderr\": 0.030225226160012397\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.24509803921568626,\n \"acc_stderr\": 0.03019028245350194,\n \"\ acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.03019028245350194\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.3037974683544304,\n \"acc_stderr\": 0.029936696387138605,\n \ \ \"acc_norm\": 0.3037974683544304,\n \"acc_norm_stderr\": 0.029936696387138605\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3542600896860987,\n\ \ \"acc_stderr\": 0.03210062154134987,\n \"acc_norm\": 0.3542600896860987,\n\ \ \"acc_norm_stderr\": 0.03210062154134987\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.2900763358778626,\n \"acc_stderr\": 0.03980066246467765,\n\ \ \"acc_norm\": 0.2900763358778626,\n \"acc_norm_stderr\": 0.03980066246467765\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.35537190082644626,\n \"acc_stderr\": 0.04369236326573981,\n \"\ acc_norm\": 0.35537190082644626,\n \"acc_norm_stderr\": 0.04369236326573981\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.26851851851851855,\n\ \ \"acc_stderr\": 0.04284467968052192,\n \"acc_norm\": 0.26851851851851855,\n\ \ \"acc_norm_stderr\": 0.04284467968052192\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.27607361963190186,\n \"acc_stderr\": 0.0351238528370505,\n\ \ \"acc_norm\": 0.27607361963190186,\n \"acc_norm_stderr\": 0.0351238528370505\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.35714285714285715,\n\ \ \"acc_stderr\": 0.04547960999764376,\n \"acc_norm\": 0.35714285714285715,\n\ \ \"acc_norm_stderr\": 0.04547960999764376\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.22330097087378642,\n \"acc_stderr\": 0.04123553189891431,\n\ \ \"acc_norm\": 0.22330097087378642,\n \"acc_norm_stderr\": 0.04123553189891431\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.3803418803418803,\n\ \ \"acc_stderr\": 0.03180425204384099,\n \"acc_norm\": 0.3803418803418803,\n\ \ \"acc_norm_stderr\": 0.03180425204384099\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.24521072796934865,\n\ \ \"acc_stderr\": 0.015384352284543936,\n \"acc_norm\": 0.24521072796934865,\n\ \ \"acc_norm_stderr\": 0.015384352284543936\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.2543352601156069,\n \"acc_stderr\": 0.02344582627654555,\n\ \ \"acc_norm\": 0.2543352601156069,\n \"acc_norm_stderr\": 0.02344582627654555\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\ \ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\ \ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.3235294117647059,\n \"acc_stderr\": 0.02678745311190654,\n\ \ \"acc_norm\": 0.3235294117647059,\n \"acc_norm_stderr\": 0.02678745311190654\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.2508038585209003,\n\ \ \"acc_stderr\": 0.024619771956697165,\n \"acc_norm\": 0.2508038585209003,\n\ \ \"acc_norm_stderr\": 0.024619771956697165\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.22530864197530864,\n \"acc_stderr\": 0.02324620264781975,\n\ \ \"acc_norm\": 0.22530864197530864,\n \"acc_norm_stderr\": 0.02324620264781975\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.2553191489361702,\n \"acc_stderr\": 0.026011992930902013,\n \ \ \"acc_norm\": 0.2553191489361702,\n \"acc_norm_stderr\": 0.026011992930902013\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2777053455019557,\n\ \ \"acc_stderr\": 0.011438741422769575,\n \"acc_norm\": 0.2777053455019557,\n\ \ \"acc_norm_stderr\": 0.011438741422769575\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.1948529411764706,\n \"acc_stderr\": 0.024060599423487428,\n\ \ \"acc_norm\": 0.1948529411764706,\n \"acc_norm_stderr\": 0.024060599423487428\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.28104575163398693,\n \"acc_stderr\": 0.018185218954318075,\n \ \ \"acc_norm\": 0.28104575163398693,\n \"acc_norm_stderr\": 0.018185218954318075\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.3181818181818182,\n\ \ \"acc_stderr\": 0.044612721759105085,\n \"acc_norm\": 0.3181818181818182,\n\ \ \"acc_norm_stderr\": 0.044612721759105085\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.2530612244897959,\n \"acc_stderr\": 0.027833023871399677,\n\ \ \"acc_norm\": 0.2530612244897959,\n \"acc_norm_stderr\": 0.027833023871399677\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.27860696517412936,\n\ \ \"acc_stderr\": 0.031700561834973086,\n \"acc_norm\": 0.27860696517412936,\n\ \ \"acc_norm_stderr\": 0.031700561834973086\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.2891566265060241,\n\ \ \"acc_stderr\": 0.03529486801511114,\n \"acc_norm\": 0.2891566265060241,\n\ \ \"acc_norm_stderr\": 0.03529486801511114\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.3216374269005848,\n \"acc_stderr\": 0.03582529442573122,\n\ \ \"acc_norm\": 0.3216374269005848,\n \"acc_norm_stderr\": 0.03582529442573122\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.23255813953488372,\n\ \ \"mc1_stderr\": 0.014789157531080512,\n \"mc2\": 0.38860179255046867,\n\ \ \"mc2_stderr\": 0.014093255696402213\n }\n}\n```" repo_url: https://huggingface.co/NoIdeaLand/test-4k-fn 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_10_01T16_31_47.992543 path: - '**/details_harness|arc:challenge|25_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hellaswag|10_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-01T16-31-47.992543.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-management|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-virology|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-01T16-31-47.992543.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_01T16_31_47.992543 path: - '**/details_harness|truthfulqa:mc|0_2023-10-01T16-31-47.992543.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-10-01T16-31-47.992543.parquet' - config_name: results data_files: - split: 2023_10_01T16_31_47.992543 path: - results_2023-10-01T16-31-47.992543.parquet - split: latest path: - results_2023-10-01T16-31-47.992543.parquet --- # Dataset Card for Evaluation run of NoIdeaLand/test-4k-fn ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/NoIdeaLand/test-4k-fn - **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 [NoIdeaLand/test-4k-fn](https://huggingface.co/NoIdeaLand/test-4k-fn) 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_NoIdeaLand__test-4k-fn", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-10-01T16:31:47.992543](https://huggingface.co/datasets/open-llm-leaderboard/details_NoIdeaLand__test-4k-fn/blob/main/results_2023-10-01T16-31-47.992543.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": 0.2795859427889157, "acc_stderr": 0.03244654146727709, "acc_norm": 0.283431508310814, "acc_norm_stderr": 0.032446107426975616, "mc1": 0.23255813953488372, "mc1_stderr": 0.014789157531080512, "mc2": 0.38860179255046867, "mc2_stderr": 0.014093255696402213 }, "harness|arc:challenge|25": { "acc": 0.35665529010238906, "acc_stderr": 0.01399805690262019, "acc_norm": 0.3993174061433447, "acc_norm_stderr": 0.014312094557946704 }, "harness|hellaswag|10": { "acc": 0.4971121290579566, "acc_stderr": 0.004989698183207823, "acc_norm": 0.6813383788090022, "acc_norm_stderr": 0.004650052150094427 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.23, "acc_stderr": 0.04229525846816508, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816508 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.23703703703703705, "acc_stderr": 0.03673731683969506, "acc_norm": 0.23703703703703705, "acc_norm_stderr": 0.03673731683969506 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.18421052631578946, "acc_stderr": 0.0315469804508223, "acc_norm": 0.18421052631578946, "acc_norm_stderr": 0.0315469804508223 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.29056603773584905, "acc_stderr": 0.027943219989337145, "acc_norm": 0.29056603773584905, "acc_norm_stderr": 0.027943219989337145 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2777777777777778, "acc_stderr": 0.037455547914624555, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.037455547914624555 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2543352601156069, "acc_stderr": 0.0332055644308557, "acc_norm": 0.2543352601156069, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617746, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617746 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3021276595744681, "acc_stderr": 0.030017554471880557, "acc_norm": 0.3021276595744681, "acc_norm_stderr": 0.030017554471880557 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21929824561403508, "acc_stderr": 0.03892431106518754, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.03892431106518754 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.3103448275862069, "acc_stderr": 0.038552896163789485, "acc_norm": 0.3103448275862069, "acc_norm_stderr": 0.038552896163789485 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24603174603174602, "acc_stderr": 0.022182037202948365, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.022182037202948365 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.21428571428571427, "acc_stderr": 0.03670066451047182, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.03670066451047182 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.24838709677419354, "acc_stderr": 0.024580028921481003, "acc_norm": 0.24838709677419354, "acc_norm_stderr": 0.024580028921481003 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2019704433497537, "acc_stderr": 0.02824735012218027, "acc_norm": 0.2019704433497537, "acc_norm_stderr": 0.02824735012218027 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.2727272727272727, "acc_stderr": 0.0347769116216366, "acc_norm": 0.2727272727272727, "acc_norm_stderr": 0.0347769116216366 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.23232323232323232, "acc_stderr": 0.030088629490217487, "acc_norm": 0.23232323232323232, "acc_norm_stderr": 0.030088629490217487 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.3471502590673575, "acc_stderr": 0.03435696168361355, "acc_norm": 0.3471502590673575, "acc_norm_stderr": 0.03435696168361355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.31025641025641026, "acc_stderr": 0.023454674889404288, "acc_norm": 0.31025641025641026, "acc_norm_stderr": 0.023454674889404288 }, "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": 0.25630252100840334, "acc_stderr": 0.02835962087053395, "acc_norm": 0.25630252100840334, "acc_norm_stderr": 0.02835962087053395 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.271523178807947, "acc_stderr": 0.036313298039696525, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.036313298039696525 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.24036697247706423, "acc_stderr": 0.01832060732096407, "acc_norm": 0.24036697247706423, "acc_norm_stderr": 0.01832060732096407 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.26851851851851855, "acc_stderr": 0.030225226160012397, "acc_norm": 0.26851851851851855, "acc_norm_stderr": 0.030225226160012397 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.24509803921568626, "acc_stderr": 0.03019028245350194, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.03019028245350194 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.3037974683544304, "acc_stderr": 0.029936696387138605, "acc_norm": 0.3037974683544304, "acc_norm_stderr": 0.029936696387138605 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.3542600896860987, "acc_stderr": 0.03210062154134987, "acc_norm": 0.3542600896860987, "acc_norm_stderr": 0.03210062154134987 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.2900763358778626, "acc_stderr": 0.03980066246467765, "acc_norm": 0.2900763358778626, "acc_norm_stderr": 0.03980066246467765 }, "harness|hendrycksTest-international_law|5": { "acc": 0.35537190082644626, "acc_stderr": 0.04369236326573981, "acc_norm": 0.35537190082644626, "acc_norm_stderr": 0.04369236326573981 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.26851851851851855, "acc_stderr": 0.04284467968052192, "acc_norm": 0.26851851851851855, "acc_norm_stderr": 0.04284467968052192 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.27607361963190186, "acc_stderr": 0.0351238528370505, "acc_norm": 0.27607361963190186, "acc_norm_stderr": 0.0351238528370505 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.35714285714285715, "acc_stderr": 0.04547960999764376, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.04547960999764376 }, "harness|hendrycksTest-management|5": { "acc": 0.22330097087378642, "acc_stderr": 0.04123553189891431, "acc_norm": 0.22330097087378642, "acc_norm_stderr": 0.04123553189891431 }, "harness|hendrycksTest-marketing|5": { "acc": 0.3803418803418803, "acc_stderr": 0.03180425204384099, "acc_norm": 0.3803418803418803, "acc_norm_stderr": 0.03180425204384099 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.24521072796934865, "acc_stderr": 0.015384352284543936, "acc_norm": 0.24521072796934865, "acc_norm_stderr": 0.015384352284543936 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.2543352601156069, "acc_stderr": 0.02344582627654555, "acc_norm": 0.2543352601156069, "acc_norm_stderr": 0.02344582627654555 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2424581005586592, "acc_stderr": 0.014333522059217889, "acc_norm": 0.2424581005586592, "acc_norm_stderr": 0.014333522059217889 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.3235294117647059, "acc_stderr": 0.02678745311190654, "acc_norm": 0.3235294117647059, "acc_norm_stderr": 0.02678745311190654 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.2508038585209003, "acc_stderr": 0.024619771956697165, "acc_norm": 0.2508038585209003, "acc_norm_stderr": 0.024619771956697165 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.22530864197530864, "acc_stderr": 0.02324620264781975, "acc_norm": 0.22530864197530864, "acc_norm_stderr": 0.02324620264781975 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.2553191489361702, "acc_stderr": 0.026011992930902013, "acc_norm": 0.2553191489361702, "acc_norm_stderr": 0.026011992930902013 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.2777053455019557, "acc_stderr": 0.011438741422769575, "acc_norm": 0.2777053455019557, "acc_norm_stderr": 0.011438741422769575 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.1948529411764706, "acc_stderr": 0.024060599423487428, "acc_norm": 0.1948529411764706, "acc_norm_stderr": 0.024060599423487428 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.28104575163398693, "acc_stderr": 0.018185218954318075, "acc_norm": 0.28104575163398693, "acc_norm_stderr": 0.018185218954318075 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.3181818181818182, "acc_stderr": 0.044612721759105085, "acc_norm": 0.3181818181818182, "acc_norm_stderr": 0.044612721759105085 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.2530612244897959, "acc_stderr": 0.027833023871399677, "acc_norm": 0.2530612244897959, "acc_norm_stderr": 0.027833023871399677 }, "harness|hendrycksTest-sociology|5": { "acc": 0.27860696517412936, "acc_stderr": 0.031700561834973086, "acc_norm": 0.27860696517412936, "acc_norm_stderr": 0.031700561834973086 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-virology|5": { "acc": 0.2891566265060241, "acc_stderr": 0.03529486801511114, "acc_norm": 0.2891566265060241, "acc_norm_stderr": 0.03529486801511114 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.3216374269005848, "acc_stderr": 0.03582529442573122, "acc_norm": 0.3216374269005848, "acc_norm_stderr": 0.03582529442573122 }, "harness|truthfulqa:mc|0": { "mc1": 0.23255813953488372, "mc1_stderr": 0.014789157531080512, "mc2": 0.38860179255046867, "mc2_stderr": 0.014093255696402213 } } ``` ### 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]

umarigan/turkish_corpus

--- license: mit task_categories: - feature-extraction language: - tr pretty_name: Corpus size_categories: - 10M<n<100M ---

huggingface-course/documentation-images

--- license: apache-2.0 ---

RoryCochrane/pokemon-and-fakemon

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 480609633.745 num_examples: 4763 download_size: 391516344 dataset_size: 480609633.745 --- # Dataset Card for "pokemon-and-fakemon" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/hassan_of_the_serenity_fgo

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hassan_of_the_serenity/静謐のハサン/静谧哈桑 (Fate/Grand Order) This is the dataset of hassan_of_the_serenity/静謐のハサン/静谧哈桑 (Fate/Grand Order), containing 500 images and their tags. The core tags of this character are `purple_hair, dark_skin, dark-skinned_female, purple_eyes, short_hair, breasts, hair_between_eyes, hairband, medium_breasts, black_hairband, very_dark_skin`, 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 | 578.80 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 500 | 497.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1186 | 977.63 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hassan_of_the_serenity_fgo/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/hassan_of_the_serenity_fgo', 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 | 23 | ![](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, bare_shoulders, black_gloves, looking_at_viewer, center_opening, black_leotard, navel, white_background, simple_background, fingerless_gloves, holding, weapon, parted_lips | | 1 | 6 | ![](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, black_gloves, center_opening, fingerless_gloves, navel, solo, black_leotard, blush, cleavage, looking_at_viewer, open_mouth | | 2 | 14 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, ass, backless_outfit, bare_back, bare_shoulders, black_gloves, fingerless_gloves, from_behind, solo, looking_at_viewer, looking_back, holding_weapon, leotard, sideboob, kunai, between_fingers, butt_crack, knife, simple_background, white_background, leggings, night, sky, toeless_legwear | | 3 | 15 | ![](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, sleeveless_dress, solo, white_dress, collarbone, white_background, looking_at_viewer, blush, sidelocks, simple_background, bare_arms, upper_body, closed_mouth, parted_lips, sundress | | 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, black_shirt, blush, closed_mouth, solo, white_background, looking_at_viewer, collarbone, long_sleeves, sidelocks, simple_background, sleeves_past_wrists, smile, hand_up, upper_body | | 5 | 12 | ![](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, puffy_long_sleeves, solo, hood_down, sleeves_past_wrists, smile, white_background, drawstring, simple_background, black_hoodie, closed_mouth, :>, v-shaped_eyebrows, hand_up | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | 1girl, collared_shirt, long_sleeves, looking_at_viewer, pleated_skirt, school_uniform, solo, white_background, white_shirt, blush, plaid_skirt, sleeves_past_wrists, smile, alternate_costume, blazer, closed_mouth, open_jacket, sidelocks, simple_background, black_jacket, black_skirt, bowtie, sweater | | 7 | 42 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | 1girl, bare_shoulders, solo, detached_sleeves, official_alternate_costume, looking_at_viewer, detached_collar, hair_flower, long_sleeves, white_dress, ribbon, strapless_dress, blush, bow, red_apple, smile, ahoge, holding_fruit, closed_mouth, pink_dress | | 8 | 10 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | 1girl, bare_shoulders, bell, looking_at_viewer, solo, blush, christmas, smile, white_thighhighs, white_panties, navel, ribbon-trimmed_legwear, red_bow, sheep_horns, underboob, closed_mouth, gift_box, sitting, stomach, bare_arms, colored_skin, fireplace, fur_collar, indoors, sidelocks | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | bare_shoulders | black_gloves | looking_at_viewer | center_opening | black_leotard | navel | white_background | simple_background | fingerless_gloves | holding | weapon | parted_lips | blush | cleavage | open_mouth | ass | backless_outfit | bare_back | from_behind | looking_back | holding_weapon | leotard | sideboob | kunai | between_fingers | butt_crack | knife | leggings | night | sky | toeless_legwear | sleeveless_dress | white_dress | collarbone | sidelocks | bare_arms | upper_body | closed_mouth | sundress | black_shirt | long_sleeves | sleeves_past_wrists | smile | hand_up | puffy_long_sleeves | hood_down | drawstring | black_hoodie | :> | v-shaped_eyebrows | collared_shirt | pleated_skirt | school_uniform | white_shirt | plaid_skirt | alternate_costume | blazer | open_jacket | black_jacket | black_skirt | bowtie | sweater | detached_sleeves | official_alternate_costume | detached_collar | hair_flower | ribbon | strapless_dress | bow | red_apple | ahoge | holding_fruit | pink_dress | bell | christmas | white_thighhighs | white_panties | ribbon-trimmed_legwear | red_bow | sheep_horns | underboob | gift_box | sitting | stomach | colored_skin | fireplace | fur_collar | indoors | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:-----------------|:---------------|:--------------------|:-----------------|:----------------|:--------|:-------------------|:--------------------|:--------------------|:----------|:---------|:--------------|:--------|:-----------|:-------------|:------|:------------------|:------------|:--------------|:---------------|:-----------------|:----------|:-----------|:--------|:------------------|:-------------|:--------|:-----------|:--------|:------|:------------------|:-------------------|:--------------|:-------------|:------------|:------------|:-------------|:---------------|:-----------|:--------------|:---------------|:----------------------|:--------|:----------|:---------------------|:------------|:-------------|:---------------|:-----|:--------------------|:-----------------|:----------------|:-----------------|:--------------|:--------------|:--------------------|:---------|:--------------|:---------------|:--------------|:---------|:----------|:-------------------|:-----------------------------|:------------------|:--------------|:---------|:------------------|:------|:------------|:--------|:----------------|:-------------|:-------|:------------|:-------------------|:----------------|:-------------------------|:----------|:--------------|:------------|:-----------|:----------|:----------|:---------------|:------------|:-------------|:----------| | 0 | 23 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 6 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | X | X | X | X | X | | | X | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 14 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | X | X | | | | X | X | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 15 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 12 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | X | X | | | X | | | | X | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | | X | | | X | X | X | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | 7 | 42 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | X | X | X | | X | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | X | | | | | X | | | X | | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | 8 | 10 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | X | X | X | | X | | | X | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | X | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

cgulse/alpaca-cleaned-tr

--- license: cc-by-4.0 language: - tr tags: - alpaca - instruction-finetuning pretty_name: Turkish Alpaca-cleaned size_categories: - 10K<n<100K --- Alpaca Cleaned Dataset. Machine Translated facebook/nllb-200-3.3B Languages Turkish

open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2

--- pretty_name: Evaluation run of g-ronimo/phi-2-OpenHermes-2.5-v2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [g-ronimo/phi-2-OpenHermes-2.5-v2](https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2)\ \ 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_g-ronimo__phi-2-OpenHermes-2.5-v2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-10T00:49:09.888984](https://huggingface.co/datasets/open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2/blob/main/results_2024-03-10T00-49-09.888984.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\": 0.564734458241999,\n\ \ \"acc_stderr\": 0.03391431521091429,\n \"acc_norm\": 0.5676857564160381,\n\ \ \"acc_norm_stderr\": 0.03461774832252384,\n \"mc1\": 0.3011015911872705,\n\ \ \"mc1_stderr\": 0.01605899902610061,\n \"mc2\": 0.44887128521126124,\n\ \ \"mc2_stderr\": 0.015342799330160783\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5699658703071673,\n \"acc_stderr\": 0.01446763155913799,\n\ \ \"acc_norm\": 0.5844709897610921,\n \"acc_norm_stderr\": 0.014401366641216388\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5592511451902011,\n\ \ \"acc_stderr\": 0.004954622308738996,\n \"acc_norm\": 0.7456681935869349,\n\ \ \"acc_norm_stderr\": 0.004345949382382379\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.48148148148148145,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.48148148148148145,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5657894736842105,\n \"acc_stderr\": 0.0403356566784832,\n\ \ \"acc_norm\": 0.5657894736842105,\n \"acc_norm_stderr\": 0.0403356566784832\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.5735849056603773,\n \"acc_stderr\": 0.03043779434298305,\n\ \ \"acc_norm\": 0.5735849056603773,\n \"acc_norm_stderr\": 0.03043779434298305\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\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness|hendrycksTest-college_computer_science|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-college_mathematics|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5491329479768786,\n\ \ \"acc_stderr\": 0.03794012674697031,\n \"acc_norm\": 0.5491329479768786,\n\ \ \"acc_norm_stderr\": 0.03794012674697031\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3137254901960784,\n \"acc_stderr\": 0.04617034827006717,\n\ \ \"acc_norm\": 0.3137254901960784,\n \"acc_norm_stderr\": 0.04617034827006717\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5276595744680851,\n \"acc_stderr\": 0.03263597118409769,\n\ \ \"acc_norm\": 0.5276595744680851,\n \"acc_norm_stderr\": 0.03263597118409769\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.39473684210526316,\n\ \ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.39473684210526316,\n\ \ \"acc_norm_stderr\": 0.045981880578165414\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5103448275862069,\n \"acc_stderr\": 0.04165774775728763,\n\ \ \"acc_norm\": 0.5103448275862069,\n \"acc_norm_stderr\": 0.04165774775728763\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.40476190476190477,\n \"acc_stderr\": 0.025279850397404907,\n \"\ acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.025279850397404907\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.373015873015873,\n\ \ \"acc_stderr\": 0.04325506042017086,\n \"acc_norm\": 0.373015873015873,\n\ \ \"acc_norm_stderr\": 0.04325506042017086\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.6645161290322581,\n \"acc_stderr\": 0.026860206444724352,\n \"\ acc_norm\": 0.6645161290322581,\n \"acc_norm_stderr\": 0.026860206444724352\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.4630541871921182,\n \"acc_stderr\": 0.035083705204426656,\n \"\ acc_norm\": 0.4630541871921182,\n \"acc_norm_stderr\": 0.035083705204426656\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6606060606060606,\n \"acc_stderr\": 0.036974422050315967,\n\ \ \"acc_norm\": 0.6606060606060606,\n \"acc_norm_stderr\": 0.036974422050315967\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7373737373737373,\n \"acc_stderr\": 0.03135305009533086,\n \"\ acc_norm\": 0.7373737373737373,\n \"acc_norm_stderr\": 0.03135305009533086\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.7564766839378239,\n \"acc_stderr\": 0.030975436386845436,\n\ \ \"acc_norm\": 0.7564766839378239,\n \"acc_norm_stderr\": 0.030975436386845436\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5615384615384615,\n \"acc_stderr\": 0.025158266016868578,\n\ \ \"acc_norm\": 0.5615384615384615,\n \"acc_norm_stderr\": 0.025158266016868578\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2962962962962963,\n \"acc_stderr\": 0.027840811495871916,\n \ \ \"acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.027840811495871916\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5882352941176471,\n \"acc_stderr\": 0.03196876989195778,\n \ \ \"acc_norm\": 0.5882352941176471,\n \"acc_norm_stderr\": 0.03196876989195778\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.32450331125827814,\n \"acc_stderr\": 0.03822746937658753,\n \"\ acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.03822746937658753\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7834862385321101,\n \"acc_stderr\": 0.017658710594443128,\n \"\ acc_norm\": 0.7834862385321101,\n \"acc_norm_stderr\": 0.017658710594443128\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.4537037037037037,\n \"acc_stderr\": 0.033953227263757976,\n \"\ acc_norm\": 0.4537037037037037,\n \"acc_norm_stderr\": 0.033953227263757976\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.6617647058823529,\n \"acc_stderr\": 0.03320574612945431,\n \"\ acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.03320574612945431\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7341772151898734,\n \"acc_stderr\": 0.028756799629658342,\n \ \ \"acc_norm\": 0.7341772151898734,\n \"acc_norm_stderr\": 0.028756799629658342\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6502242152466368,\n\ \ \"acc_stderr\": 0.03200736719484503,\n \"acc_norm\": 0.6502242152466368,\n\ \ \"acc_norm_stderr\": 0.03200736719484503\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6335877862595419,\n \"acc_stderr\": 0.04225875451969638,\n\ \ \"acc_norm\": 0.6335877862595419,\n \"acc_norm_stderr\": 0.04225875451969638\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302871,\n \"acc_norm\"\ : 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302871\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7222222222222222,\n\ \ \"acc_stderr\": 0.043300437496507416,\n \"acc_norm\": 0.7222222222222222,\n\ \ \"acc_norm_stderr\": 0.043300437496507416\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7361963190184049,\n \"acc_stderr\": 0.03462419931615623,\n\ \ \"acc_norm\": 0.7361963190184049,\n \"acc_norm_stderr\": 0.03462419931615623\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6990291262135923,\n \"acc_stderr\": 0.04541609446503948,\n\ \ \"acc_norm\": 0.6990291262135923,\n \"acc_norm_stderr\": 0.04541609446503948\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8205128205128205,\n\ \ \"acc_stderr\": 0.025140935950335428,\n \"acc_norm\": 0.8205128205128205,\n\ \ \"acc_norm_stderr\": 0.025140935950335428\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.63,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.63,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6756066411238825,\n\ \ \"acc_stderr\": 0.016740929047162696,\n \"acc_norm\": 0.6756066411238825,\n\ \ \"acc_norm_stderr\": 0.016740929047162696\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.661849710982659,\n \"acc_stderr\": 0.02546977014940017,\n\ \ \"acc_norm\": 0.661849710982659,\n \"acc_norm_stderr\": 0.02546977014940017\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2212290502793296,\n\ \ \"acc_stderr\": 0.01388216459888727,\n \"acc_norm\": 0.2212290502793296,\n\ \ \"acc_norm_stderr\": 0.01388216459888727\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6013071895424836,\n \"acc_stderr\": 0.02803609227389177,\n\ \ \"acc_norm\": 0.6013071895424836,\n \"acc_norm_stderr\": 0.02803609227389177\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6237942122186495,\n\ \ \"acc_stderr\": 0.02751392568354943,\n \"acc_norm\": 0.6237942122186495,\n\ \ \"acc_norm_stderr\": 0.02751392568354943\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6203703703703703,\n \"acc_stderr\": 0.027002521034516468,\n\ \ \"acc_norm\": 0.6203703703703703,\n \"acc_norm_stderr\": 0.027002521034516468\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4078014184397163,\n \"acc_stderr\": 0.02931601177634356,\n \ \ \"acc_norm\": 0.4078014184397163,\n \"acc_norm_stderr\": 0.02931601177634356\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.40808344198174706,\n\ \ \"acc_stderr\": 0.012552598958563662,\n \"acc_norm\": 0.40808344198174706,\n\ \ \"acc_norm_stderr\": 0.012552598958563662\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.44485294117647056,\n \"acc_stderr\": 0.03018753206032939,\n\ \ \"acc_norm\": 0.44485294117647056,\n \"acc_norm_stderr\": 0.03018753206032939\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.5718954248366013,\n \"acc_stderr\": 0.0200176292142131,\n \ \ \"acc_norm\": 0.5718954248366013,\n \"acc_norm_stderr\": 0.0200176292142131\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6938775510204082,\n \"acc_stderr\": 0.02950489645459595,\n\ \ \"acc_norm\": 0.6938775510204082,\n \"acc_norm_stderr\": 0.02950489645459595\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7412935323383084,\n\ \ \"acc_stderr\": 0.03096590312357303,\n \"acc_norm\": 0.7412935323383084,\n\ \ \"acc_norm_stderr\": 0.03096590312357303\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-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\": 0.6842105263157895,\n \"acc_stderr\": 0.035650796707083106,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.035650796707083106\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3011015911872705,\n\ \ \"mc1_stderr\": 0.01605899902610061,\n \"mc2\": 0.44887128521126124,\n\ \ \"mc2_stderr\": 0.015342799330160783\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7521704814522494,\n \"acc_stderr\": 0.012134386019865353\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.4040940106141016,\n \ \ \"acc_stderr\": 0.013516752972721717\n }\n}\n```" repo_url: https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|arc:challenge|25_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-10T00-49-09.888984.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|gsm8k|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hellaswag|10_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-10T00-49-09.888984.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-management|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-10T00-49-09.888984.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|truthfulqa:mc|0_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-10T00-49-09.888984.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_10T00_49_09.888984 path: - '**/details_harness|winogrande|5_2024-03-10T00-49-09.888984.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-10T00-49-09.888984.parquet' - config_name: results data_files: - split: 2024_03_10T00_49_09.888984 path: - results_2024-03-10T00-49-09.888984.parquet - split: latest path: - results_2024-03-10T00-49-09.888984.parquet --- # Dataset Card for Evaluation run of g-ronimo/phi-2-OpenHermes-2.5-v2  Dataset automatically created during the evaluation run of model [g-ronimo/phi-2-OpenHermes-2.5-v2](https://huggingface.co/g-ronimo/phi-2-OpenHermes-2.5-v2) 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_g-ronimo__phi-2-OpenHermes-2.5-v2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-10T00:49:09.888984](https://huggingface.co/datasets/open-llm-leaderboard/details_g-ronimo__phi-2-OpenHermes-2.5-v2/blob/main/results_2024-03-10T00-49-09.888984.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": 0.564734458241999, "acc_stderr": 0.03391431521091429, "acc_norm": 0.5676857564160381, "acc_norm_stderr": 0.03461774832252384, "mc1": 0.3011015911872705, "mc1_stderr": 0.01605899902610061, "mc2": 0.44887128521126124, "mc2_stderr": 0.015342799330160783 }, "harness|arc:challenge|25": { "acc": 0.5699658703071673, "acc_stderr": 0.01446763155913799, "acc_norm": 0.5844709897610921, "acc_norm_stderr": 0.014401366641216388 }, "harness|hellaswag|10": { "acc": 0.5592511451902011, "acc_stderr": 0.004954622308738996, "acc_norm": 0.7456681935869349, "acc_norm_stderr": 0.004345949382382379 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.48148148148148145, "acc_stderr": 0.043163785995113245, "acc_norm": 0.48148148148148145, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5657894736842105, "acc_stderr": 0.0403356566784832, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.0403356566784832 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5735849056603773, "acc_stderr": 0.03043779434298305, "acc_norm": 0.5735849056603773, "acc_norm_stderr": 0.03043779434298305 }, "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": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5491329479768786, "acc_stderr": 0.03794012674697031, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.03794012674697031 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006717, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006717 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5276595744680851, "acc_stderr": 0.03263597118409769, "acc_norm": 0.5276595744680851, "acc_norm_stderr": 0.03263597118409769 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.39473684210526316, "acc_stderr": 0.045981880578165414, "acc_norm": 0.39473684210526316, "acc_norm_stderr": 0.045981880578165414 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5103448275862069, "acc_stderr": 0.04165774775728763, "acc_norm": 0.5103448275862069, "acc_norm_stderr": 0.04165774775728763 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.40476190476190477, "acc_stderr": 0.025279850397404907, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.025279850397404907 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.373015873015873, "acc_stderr": 0.04325506042017086, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.04325506042017086 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6645161290322581, "acc_stderr": 0.026860206444724352, "acc_norm": 0.6645161290322581, "acc_norm_stderr": 0.026860206444724352 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4630541871921182, "acc_stderr": 0.035083705204426656, "acc_norm": 0.4630541871921182, "acc_norm_stderr": 0.035083705204426656 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6606060606060606, "acc_stderr": 0.036974422050315967, "acc_norm": 0.6606060606060606, "acc_norm_stderr": 0.036974422050315967 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7373737373737373, "acc_stderr": 0.03135305009533086, "acc_norm": 0.7373737373737373, "acc_norm_stderr": 0.03135305009533086 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7564766839378239, "acc_stderr": 0.030975436386845436, "acc_norm": 0.7564766839378239, "acc_norm_stderr": 0.030975436386845436 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5615384615384615, "acc_stderr": 0.025158266016868578, "acc_norm": 0.5615384615384615, "acc_norm_stderr": 0.025158266016868578 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2962962962962963, "acc_stderr": 0.027840811495871916, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.027840811495871916 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.5882352941176471, "acc_stderr": 0.03196876989195778, "acc_norm": 0.5882352941176471, "acc_norm_stderr": 0.03196876989195778 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.32450331125827814, "acc_stderr": 0.03822746937658753, "acc_norm": 0.32450331125827814, "acc_norm_stderr": 0.03822746937658753 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.7834862385321101, "acc_stderr": 0.017658710594443128, "acc_norm": 0.7834862385321101, "acc_norm_stderr": 0.017658710594443128 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4537037037037037, "acc_stderr": 0.033953227263757976, "acc_norm": 0.4537037037037037, "acc_norm_stderr": 0.033953227263757976 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.6617647058823529, "acc_stderr": 0.03320574612945431, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.03320574612945431 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7341772151898734, "acc_stderr": 0.028756799629658342, "acc_norm": 0.7341772151898734, "acc_norm_stderr": 0.028756799629658342 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6502242152466368, "acc_stderr": 0.03200736719484503, "acc_norm": 0.6502242152466368, "acc_norm_stderr": 0.03200736719484503 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.6335877862595419, "acc_stderr": 0.04225875451969638, "acc_norm": 0.6335877862595419, "acc_norm_stderr": 0.04225875451969638 }, "harness|hendrycksTest-international_law|5": { "acc": 0.743801652892562, "acc_stderr": 0.03984979653302871, "acc_norm": 0.743801652892562, "acc_norm_stderr": 0.03984979653302871 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7222222222222222, "acc_stderr": 0.043300437496507416, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.043300437496507416 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7361963190184049, "acc_stderr": 0.03462419931615623, "acc_norm": 0.7361963190184049, "acc_norm_stderr": 0.03462419931615623 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness|hendrycksTest-management|5": { "acc": 0.6990291262135923, "acc_stderr": 0.04541609446503948, "acc_norm": 0.6990291262135923, "acc_norm_stderr": 0.04541609446503948 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8205128205128205, "acc_stderr": 0.025140935950335428, "acc_norm": 0.8205128205128205, "acc_norm_stderr": 0.025140935950335428 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.6756066411238825, "acc_stderr": 0.016740929047162696, "acc_norm": 0.6756066411238825, "acc_norm_stderr": 0.016740929047162696 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.661849710982659, "acc_stderr": 0.02546977014940017, "acc_norm": 0.661849710982659, "acc_norm_stderr": 0.02546977014940017 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2212290502793296, "acc_stderr": 0.01388216459888727, "acc_norm": 0.2212290502793296, "acc_norm_stderr": 0.01388216459888727 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6013071895424836, "acc_stderr": 0.02803609227389177, "acc_norm": 0.6013071895424836, "acc_norm_stderr": 0.02803609227389177 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6237942122186495, "acc_stderr": 0.02751392568354943, "acc_norm": 0.6237942122186495, "acc_norm_stderr": 0.02751392568354943 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6203703703703703, "acc_stderr": 0.027002521034516468, "acc_norm": 0.6203703703703703, "acc_norm_stderr": 0.027002521034516468 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4078014184397163, "acc_stderr": 0.02931601177634356, "acc_norm": 0.4078014184397163, "acc_norm_stderr": 0.02931601177634356 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.40808344198174706, "acc_stderr": 0.012552598958563662, "acc_norm": 0.40808344198174706, "acc_norm_stderr": 0.012552598958563662 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.44485294117647056, "acc_stderr": 0.03018753206032939, "acc_norm": 0.44485294117647056, "acc_norm_stderr": 0.03018753206032939 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.5718954248366013, "acc_stderr": 0.0200176292142131, "acc_norm": 0.5718954248366013, "acc_norm_stderr": 0.0200176292142131 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6938775510204082, "acc_stderr": 0.02950489645459595, "acc_norm": 0.6938775510204082, "acc_norm_stderr": 0.02950489645459595 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7412935323383084, "acc_stderr": 0.03096590312357303, "acc_norm": 0.7412935323383084, "acc_norm_stderr": 0.03096590312357303 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "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": 0.6842105263157895, "acc_stderr": 0.035650796707083106, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.035650796707083106 }, "harness|truthfulqa:mc|0": { "mc1": 0.3011015911872705, "mc1_stderr": 0.01605899902610061, "mc2": 0.44887128521126124, "mc2_stderr": 0.015342799330160783 }, "harness|winogrande|5": { "acc": 0.7521704814522494, "acc_stderr": 0.012134386019865353 }, "harness|gsm8k|5": { "acc": 0.4040940106141016, "acc_stderr": 0.013516752972721717 } } ``` ## 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 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open-llm-leaderboard/details_Technoculture__MT7Bi-sft

--- pretty_name: Evaluation run of Technoculture/MT7Bi-sft dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Technoculture/MT7Bi-sft](https://huggingface.co/Technoculture/MT7Bi-sft) 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_Technoculture__MT7Bi-sft\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-01T14:25:40.116952](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MT7Bi-sft/blob/main/results_2024-02-01T14-25-40.116952.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\": 0.4105658357592459,\n\ \ \"acc_stderr\": 0.03434113134801399,\n \"acc_norm\": 0.416672739687421,\n\ \ \"acc_norm_stderr\": 0.03527569703844115,\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608767,\n \"mc2\": 0.4460516469060258,\n\ \ \"mc2_stderr\": 0.01603355318388596\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.3796928327645051,\n \"acc_stderr\": 0.014182119866974874,\n\ \ \"acc_norm\": 0.4180887372013652,\n \"acc_norm_stderr\": 0.014413988396996074\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4629555865365465,\n\ \ \"acc_stderr\": 0.004976067726432563,\n \"acc_norm\": 0.5683130850428202,\n\ \ \"acc_norm_stderr\": 0.004942990623131126\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.5185185185185185,\n\ \ \"acc_stderr\": 0.043163785995113245,\n \"acc_norm\": 0.5185185185185185,\n\ \ \"acc_norm_stderr\": 0.043163785995113245\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.40131578947368424,\n \"acc_stderr\": 0.039889037033362836,\n\ \ \"acc_norm\": 0.40131578947368424,\n \"acc_norm_stderr\": 0.039889037033362836\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.5018867924528302,\n \"acc_stderr\": 0.03077265364207565,\n\ \ \"acc_norm\": 0.5018867924528302,\n \"acc_norm_stderr\": 0.03077265364207565\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4236111111111111,\n\ \ \"acc_stderr\": 0.04132125019723369,\n \"acc_norm\": 0.4236111111111111,\n\ \ \"acc_norm_stderr\": 0.04132125019723369\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.41040462427745666,\n\ \ \"acc_stderr\": 0.03750757044895537,\n \"acc_norm\": 0.41040462427745666,\n\ \ \"acc_norm_stderr\": 0.03750757044895537\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.29411764705882354,\n \"acc_stderr\": 0.04533838195929774,\n\ \ \"acc_norm\": 0.29411764705882354,\n \"acc_norm_stderr\": 0.04533838195929774\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.3276595744680851,\n \"acc_stderr\": 0.030683020843231004,\n\ \ \"acc_norm\": 0.3276595744680851,\n \"acc_norm_stderr\": 0.030683020843231004\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.043036840335373146,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.043036840335373146\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.45517241379310347,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.45517241379310347,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2751322751322751,\n \"acc_stderr\": 0.02300008685906864,\n \"\ acc_norm\": 0.2751322751322751,\n \"acc_norm_stderr\": 0.02300008685906864\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.25396825396825395,\n\ \ \"acc_stderr\": 0.03893259610604674,\n \"acc_norm\": 0.25396825396825395,\n\ \ \"acc_norm_stderr\": 0.03893259610604674\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.4935483870967742,\n \"acc_stderr\": 0.02844163823354051,\n \"\ acc_norm\": 0.4935483870967742,\n \"acc_norm_stderr\": 0.02844163823354051\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.26108374384236455,\n \"acc_stderr\": 0.0309037969521145,\n \"\ acc_norm\": 0.26108374384236455,\n \"acc_norm_stderr\": 0.0309037969521145\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001974,\n \"acc_norm\"\ : 0.39,\n \"acc_norm_stderr\": 0.04902071300001974\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.47878787878787876,\n \"acc_stderr\": 0.039008289137373,\n\ \ \"acc_norm\": 0.47878787878787876,\n \"acc_norm_stderr\": 0.039008289137373\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.4797979797979798,\n \"acc_stderr\": 0.03559443565563921,\n \"\ acc_norm\": 0.4797979797979798,\n \"acc_norm_stderr\": 0.03559443565563921\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.47668393782383417,\n \"acc_stderr\": 0.03604513672442206,\n\ \ \"acc_norm\": 0.47668393782383417,\n \"acc_norm_stderr\": 0.03604513672442206\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.3435897435897436,\n \"acc_stderr\": 0.024078696580635484,\n\ \ \"acc_norm\": 0.3435897435897436,\n \"acc_norm_stderr\": 0.024078696580635484\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340496,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340496\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.3697478991596639,\n \"acc_stderr\": 0.031357095996135904,\n\ \ \"acc_norm\": 0.3697478991596639,\n \"acc_norm_stderr\": 0.031357095996135904\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.037579499229433426,\n \"\ acc_norm\": 0.304635761589404,\n \"acc_norm_stderr\": 0.037579499229433426\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.5522935779816514,\n \"acc_stderr\": 0.021319754962425462,\n \"\ acc_norm\": 0.5522935779816514,\n \"acc_norm_stderr\": 0.021319754962425462\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.35648148148148145,\n \"acc_stderr\": 0.032664783315272714,\n \"\ acc_norm\": 0.35648148148148145,\n \"acc_norm_stderr\": 0.032664783315272714\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.37745098039215685,\n \"acc_stderr\": 0.03402272044340703,\n \"\ acc_norm\": 0.37745098039215685,\n \"acc_norm_stderr\": 0.03402272044340703\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.5780590717299579,\n \"acc_stderr\": 0.032148146302403695,\n \ \ \"acc_norm\": 0.5780590717299579,\n \"acc_norm_stderr\": 0.032148146302403695\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.47533632286995514,\n\ \ \"acc_stderr\": 0.033516951676526276,\n \"acc_norm\": 0.47533632286995514,\n\ \ \"acc_norm_stderr\": 0.033516951676526276\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5343511450381679,\n \"acc_stderr\": 0.043749285605997376,\n\ \ \"acc_norm\": 0.5343511450381679,\n \"acc_norm_stderr\": 0.043749285605997376\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5867768595041323,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.5867768595041323,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5370370370370371,\n\ \ \"acc_stderr\": 0.04820403072760628,\n \"acc_norm\": 0.5370370370370371,\n\ \ \"acc_norm_stderr\": 0.04820403072760628\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.4294478527607362,\n \"acc_stderr\": 0.038890666191127216,\n\ \ \"acc_norm\": 0.4294478527607362,\n \"acc_norm_stderr\": 0.038890666191127216\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.21428571428571427,\n\ \ \"acc_stderr\": 0.038946411200447915,\n \"acc_norm\": 0.21428571428571427,\n\ \ \"acc_norm_stderr\": 0.038946411200447915\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5048543689320388,\n \"acc_stderr\": 0.04950504382128921,\n\ \ \"acc_norm\": 0.5048543689320388,\n \"acc_norm_stderr\": 0.04950504382128921\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6025641025641025,\n\ \ \"acc_stderr\": 0.03205953453789293,\n \"acc_norm\": 0.6025641025641025,\n\ \ \"acc_norm_stderr\": 0.03205953453789293\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.4661558109833972,\n\ \ \"acc_stderr\": 0.017838956009136805,\n \"acc_norm\": 0.4661558109833972,\n\ \ \"acc_norm_stderr\": 0.017838956009136805\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.44508670520231214,\n \"acc_stderr\": 0.02675625512966377,\n\ \ \"acc_norm\": 0.44508670520231214,\n \"acc_norm_stderr\": 0.02675625512966377\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2335195530726257,\n\ \ \"acc_stderr\": 0.014149575348976259,\n \"acc_norm\": 0.2335195530726257,\n\ \ \"acc_norm_stderr\": 0.014149575348976259\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.4869281045751634,\n \"acc_stderr\": 0.028620130800700246,\n\ \ \"acc_norm\": 0.4869281045751634,\n \"acc_norm_stderr\": 0.028620130800700246\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.4437299035369775,\n\ \ \"acc_stderr\": 0.028217683556652308,\n \"acc_norm\": 0.4437299035369775,\n\ \ \"acc_norm_stderr\": 0.028217683556652308\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.42901234567901236,\n \"acc_stderr\": 0.027538925613470863,\n\ \ \"acc_norm\": 0.42901234567901236,\n \"acc_norm_stderr\": 0.027538925613470863\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.33687943262411346,\n \"acc_stderr\": 0.028195534873966734,\n \ \ \"acc_norm\": 0.33687943262411346,\n \"acc_norm_stderr\": 0.028195534873966734\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3057366362451108,\n\ \ \"acc_stderr\": 0.011766973847072914,\n \"acc_norm\": 0.3057366362451108,\n\ \ \"acc_norm_stderr\": 0.011766973847072914\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.4227941176470588,\n \"acc_stderr\": 0.030008562845003486,\n\ \ \"acc_norm\": 0.4227941176470588,\n \"acc_norm_stderr\": 0.030008562845003486\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.39705882352941174,\n \"acc_stderr\": 0.01979448890002411,\n \ \ \"acc_norm\": 0.39705882352941174,\n \"acc_norm_stderr\": 0.01979448890002411\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.43636363636363634,\n\ \ \"acc_stderr\": 0.04750185058907297,\n \"acc_norm\": 0.43636363636363634,\n\ \ \"acc_norm_stderr\": 0.04750185058907297\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.49795918367346936,\n \"acc_stderr\": 0.0320089533497105,\n\ \ \"acc_norm\": 0.49795918367346936,\n \"acc_norm_stderr\": 0.0320089533497105\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.5472636815920398,\n\ \ \"acc_stderr\": 0.03519702717576915,\n \"acc_norm\": 0.5472636815920398,\n\ \ \"acc_norm_stderr\": 0.03519702717576915\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562427,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562427\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.3855421686746988,\n\ \ \"acc_stderr\": 0.037891344246115496,\n \"acc_norm\": 0.3855421686746988,\n\ \ \"acc_norm_stderr\": 0.037891344246115496\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.49122807017543857,\n \"acc_stderr\": 0.03834234744164993,\n\ \ \"acc_norm\": 0.49122807017543857,\n \"acc_norm_stderr\": 0.03834234744164993\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608767,\n \"mc2\": 0.4460516469060258,\n\ \ \"mc2_stderr\": 0.01603355318388596\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6045777426992897,\n \"acc_stderr\": 0.013741678387545352\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/Technoculture/MT7Bi-sft 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_01T14_25_40.116952 path: - '**/details_harness|arc:challenge|25_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-01T14-25-40.116952.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|gsm8k|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hellaswag|10_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-01T14-25-40.116952.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-management|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-01T14-25-40.116952.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|truthfulqa:mc|0_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-01T14-25-40.116952.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_01T14_25_40.116952 path: - '**/details_harness|winogrande|5_2024-02-01T14-25-40.116952.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-01T14-25-40.116952.parquet' - config_name: results data_files: - split: 2024_02_01T14_25_40.116952 path: - results_2024-02-01T14-25-40.116952.parquet - split: latest path: - results_2024-02-01T14-25-40.116952.parquet --- # Dataset Card for Evaluation run of Technoculture/MT7Bi-sft  Dataset automatically created during the evaluation run of model [Technoculture/MT7Bi-sft](https://huggingface.co/Technoculture/MT7Bi-sft) 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_Technoculture__MT7Bi-sft", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-01T14:25:40.116952](https://huggingface.co/datasets/open-llm-leaderboard/details_Technoculture__MT7Bi-sft/blob/main/results_2024-02-01T14-25-40.116952.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": 0.4105658357592459, "acc_stderr": 0.03434113134801399, "acc_norm": 0.416672739687421, "acc_norm_stderr": 0.03527569703844115, "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608767, "mc2": 0.4460516469060258, "mc2_stderr": 0.01603355318388596 }, "harness|arc:challenge|25": { "acc": 0.3796928327645051, "acc_stderr": 0.014182119866974874, "acc_norm": 0.4180887372013652, "acc_norm_stderr": 0.014413988396996074 }, "harness|hellaswag|10": { "acc": 0.4629555865365465, "acc_stderr": 0.004976067726432563, "acc_norm": 0.5683130850428202, "acc_norm_stderr": 0.004942990623131126 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5185185185185185, "acc_stderr": 0.043163785995113245, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.40131578947368424, "acc_stderr": 0.039889037033362836, "acc_norm": 0.40131578947368424, "acc_norm_stderr": 0.039889037033362836 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5018867924528302, "acc_stderr": 0.03077265364207565, "acc_norm": 0.5018867924528302, "acc_norm_stderr": 0.03077265364207565 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4236111111111111, "acc_stderr": 0.04132125019723369, "acc_norm": 0.4236111111111111, "acc_norm_stderr": 0.04132125019723369 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.41040462427745666, "acc_stderr": 0.03750757044895537, "acc_norm": 0.41040462427745666, "acc_norm_stderr": 0.03750757044895537 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929774, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929774 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3276595744680851, "acc_stderr": 0.030683020843231004, "acc_norm": 0.3276595744680851, "acc_norm_stderr": 0.030683020843231004 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2982456140350877, "acc_stderr": 0.043036840335373146, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.043036840335373146 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2751322751322751, "acc_stderr": 0.02300008685906864, "acc_norm": 0.2751322751322751, "acc_norm_stderr": 0.02300008685906864 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4935483870967742, "acc_stderr": 0.02844163823354051, "acc_norm": 0.4935483870967742, "acc_norm_stderr": 0.02844163823354051 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.26108374384236455, "acc_stderr": 0.0309037969521145, "acc_norm": 0.26108374384236455, "acc_norm_stderr": 0.0309037969521145 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.47878787878787876, "acc_stderr": 0.039008289137373, "acc_norm": 0.47878787878787876, "acc_norm_stderr": 0.039008289137373 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4797979797979798, "acc_stderr": 0.03559443565563921, "acc_norm": 0.4797979797979798, "acc_norm_stderr": 0.03559443565563921 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.47668393782383417, "acc_stderr": 0.03604513672442206, "acc_norm": 0.47668393782383417, "acc_norm_stderr": 0.03604513672442206 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3435897435897436, "acc_stderr": 0.024078696580635484, "acc_norm": 0.3435897435897436, "acc_norm_stderr": 0.024078696580635484 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340496, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340496 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.3697478991596639, "acc_stderr": 0.031357095996135904, "acc_norm": 0.3697478991596639, "acc_norm_stderr": 0.031357095996135904 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.304635761589404, "acc_stderr": 0.037579499229433426, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.037579499229433426 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.5522935779816514, "acc_stderr": 0.021319754962425462, "acc_norm": 0.5522935779816514, "acc_norm_stderr": 0.021319754962425462 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.35648148148148145, "acc_stderr": 0.032664783315272714, "acc_norm": 0.35648148148148145, "acc_norm_stderr": 0.032664783315272714 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.37745098039215685, "acc_stderr": 0.03402272044340703, "acc_norm": 0.37745098039215685, "acc_norm_stderr": 0.03402272044340703 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.5780590717299579, "acc_stderr": 0.032148146302403695, "acc_norm": 0.5780590717299579, "acc_norm_stderr": 0.032148146302403695 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.47533632286995514, "acc_stderr": 0.033516951676526276, "acc_norm": 0.47533632286995514, "acc_norm_stderr": 0.033516951676526276 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5343511450381679, "acc_stderr": 0.043749285605997376, "acc_norm": 0.5343511450381679, "acc_norm_stderr": 0.043749285605997376 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5867768595041323, "acc_stderr": 0.04495087843548408, "acc_norm": 0.5867768595041323, "acc_norm_stderr": 0.04495087843548408 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.5370370370370371, "acc_stderr": 0.04820403072760628, "acc_norm": 0.5370370370370371, "acc_norm_stderr": 0.04820403072760628 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.4294478527607362, "acc_stderr": 0.038890666191127216, "acc_norm": 0.4294478527607362, "acc_norm_stderr": 0.038890666191127216 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.21428571428571427, "acc_stderr": 0.038946411200447915, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.038946411200447915 }, "harness|hendrycksTest-management|5": { "acc": 0.5048543689320388, "acc_stderr": 0.04950504382128921, "acc_norm": 0.5048543689320388, "acc_norm_stderr": 0.04950504382128921 }, "harness|hendrycksTest-marketing|5": { "acc": 0.6025641025641025, "acc_stderr": 0.03205953453789293, "acc_norm": 0.6025641025641025, "acc_norm_stderr": 0.03205953453789293 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.4661558109833972, "acc_stderr": 0.017838956009136805, "acc_norm": 0.4661558109833972, "acc_norm_stderr": 0.017838956009136805 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.44508670520231214, "acc_stderr": 0.02675625512966377, "acc_norm": 0.44508670520231214, "acc_norm_stderr": 0.02675625512966377 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2335195530726257, "acc_stderr": 0.014149575348976259, "acc_norm": 0.2335195530726257, "acc_norm_stderr": 0.014149575348976259 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.4869281045751634, "acc_stderr": 0.028620130800700246, "acc_norm": 0.4869281045751634, "acc_norm_stderr": 0.028620130800700246 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.4437299035369775, "acc_stderr": 0.028217683556652308, "acc_norm": 0.4437299035369775, "acc_norm_stderr": 0.028217683556652308 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.42901234567901236, "acc_stderr": 0.027538925613470863, "acc_norm": 0.42901234567901236, "acc_norm_stderr": 0.027538925613470863 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.33687943262411346, "acc_stderr": 0.028195534873966734, "acc_norm": 0.33687943262411346, "acc_norm_stderr": 0.028195534873966734 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3057366362451108, "acc_stderr": 0.011766973847072914, "acc_norm": 0.3057366362451108, "acc_norm_stderr": 0.011766973847072914 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.4227941176470588, "acc_stderr": 0.030008562845003486, "acc_norm": 0.4227941176470588, "acc_norm_stderr": 0.030008562845003486 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.39705882352941174, "acc_stderr": 0.01979448890002411, "acc_norm": 0.39705882352941174, "acc_norm_stderr": 0.01979448890002411 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.43636363636363634, "acc_stderr": 0.04750185058907297, "acc_norm": 0.43636363636363634, "acc_norm_stderr": 0.04750185058907297 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.49795918367346936, "acc_stderr": 0.0320089533497105, "acc_norm": 0.49795918367346936, "acc_norm_stderr": 0.0320089533497105 }, "harness|hendrycksTest-sociology|5": { "acc": 0.5472636815920398, "acc_stderr": 0.03519702717576915, "acc_norm": 0.5472636815920398, "acc_norm_stderr": 0.03519702717576915 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.57, "acc_stderr": 0.04975698519562427, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562427 }, "harness|hendrycksTest-virology|5": { "acc": 0.3855421686746988, "acc_stderr": 0.037891344246115496, "acc_norm": 0.3855421686746988, "acc_norm_stderr": 0.037891344246115496 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.49122807017543857, "acc_stderr": 0.03834234744164993, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.03834234744164993 }, "harness|truthfulqa:mc|0": { "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608767, "mc2": 0.4460516469060258, "mc2_stderr": 0.01603355318388596 }, "harness|winogrande|5": { "acc": 0.6045777426992897, "acc_stderr": 0.013741678387545352 }, "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?  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