metadata
pretty_name: Evaluation run of euclaise/Ferret-7B
dataset_summary: "Dataset automatically created during the evaluation run of model [euclaise/Ferret-7B](https://huggingface.co/euclaise/Ferret-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 4 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\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_euclaise__Ferret-7B_public\",\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-11-25T03:02:51.561913](https://huggingface.co/datasets/open-llm-leaderboard/details_euclaise__Ferret-7B_public/blob/main/results_2023-11-25T03-02-51.561913.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\": 0.5959498298780265,\n \"acc_stderr\": 0.033140542039800984,\n \"acc_norm\": 0.6066121431850051,\n \"acc_norm_stderr\": 0.03397883209596383,\n \"mc1\": 0.2778457772337821,\n \"mc1_stderr\": 0.015680929364024647,\n \"mc2\": 0.4001041496199733,\n \"mc2_stderr\": 0.014571617835253216,\n \"em\": 0.001572986577181208,\n \"em_stderr\": 0.00040584511324177344,\n \"f1\": 0.06579802852349013,\n \"f1_stderr\": 0.0014930152947085352\n },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.5767918088737202,\n \"acc_stderr\": 0.014438036220848029,\n \"acc_norm\": 0.6228668941979523,\n \"acc_norm_stderr\": 0.014163366896192596\n },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6248755228042223,\n \"acc_stderr\": 0.004831655648489736,\n \"acc_norm\": 0.8130850428201554,\n \"acc_norm_stderr\": 0.00389046515827181\n },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252606,\n \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252606\n },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6,\n \"acc_stderr\": 0.042320736951515885,\n \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.042320736951515885\n },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.6644736842105263,\n \"acc_stderr\": 0.03842498559395269,\n \"acc_norm\": 0.6644736842105263,\n \"acc_norm_stderr\": 0.03842498559395269\n },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.05\n },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.6679245283018868,\n \"acc_stderr\": 0.02898545565233439,\n \"acc_norm\": 0.6679245283018868,\n \"acc_norm_stderr\": 0.02898545565233439\n },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6944444444444444,\n \"acc_stderr\": 0.03852084696008534,\n \"acc_norm\": 0.6944444444444444,\n \"acc_norm_stderr\": 0.03852084696008534\n },\n \"harness|hendrycksTest-college_chemistry|5\": {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-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\": 0.5780346820809249,\n \"acc_stderr\": 0.0376574669386515,\n \"acc_norm\": 0.5780346820809249,\n \"acc_norm_stderr\": 0.0376574669386515\n },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.37254901960784315,\n \"acc_stderr\": 0.048108401480826346,\n \"acc_norm\": 0.37254901960784315,\n \"acc_norm_stderr\": 0.048108401480826346\n },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\": 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.04560480215720684\n },\n \"harness|hendrycksTest-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\": 0.5,\n \"acc_stderr\": 0.047036043419179864,\n \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.047036043419179864\n },\n \"harness|hendrycksTest-electrical_engineering|5\": {\n \"acc\": 0.6137931034482759,\n \"acc_stderr\": 0.04057324734419035,\n \"acc_norm\": 0.6137931034482759,\n \"acc_norm_stderr\": 0.04057324734419035\n },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.3915343915343915,\n \"acc_stderr\": 0.025138091388851088,\n \"acc_norm\": 0.3915343915343915,\n \"acc_norm_stderr\": 0.025138091388851088\n },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3888888888888889,\n \"acc_stderr\": 0.0436031486007746,\n \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.0436031486007746\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\": 0.6709677419354839,\n \"acc_stderr\": 0.026729499068349954,\n \"acc_norm\": 0.6709677419354839,\n \"acc_norm_stderr\": 0.026729499068349954\n },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\": 0.4729064039408867,\n \"acc_stderr\": 0.03512819077876106,\n \"acc_norm\": 0.4729064039408867,\n \"acc_norm_stderr\": 0.03512819077876106\n },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\": 0.61,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-high_school_european_history|5\": {\n \"acc\": 0.7393939393939394,\n \"acc_stderr\": 0.034277431758165236,\n \"acc_norm\": 0.7393939393939394,\n \"acc_norm_stderr\": 0.034277431758165236\n },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\": 0.7424242424242424,\n \"acc_stderr\": 0.03115626951964683,\n \"acc_norm\": 0.7424242424242424,\n \"acc_norm_stderr\": 0.03115626951964683\n },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \"acc\": 0.8341968911917098,\n \"acc_stderr\": 0.026839845022314415,\n \"acc_norm\": 0.8341968911917098,\n \"acc_norm_stderr\": 0.026839845022314415\n },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \"acc\": 0.5897435897435898,\n \"acc_stderr\": 0.024939313906940798,\n \"acc_norm\": 0.5897435897435898,\n \"acc_norm_stderr\": 0.024939313906940798\n },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"acc\": 0.29259259259259257,\n \"acc_stderr\": 0.027738969632176088,\n \"acc_norm\": 0.29259259259259257,\n \"acc_norm_stderr\": 0.027738969632176088\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\": 0.0386155754625517,\n \"acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.0386155754625517\n },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.7908256880733945,\n \"acc_stderr\": 0.017437937173343233,\n \"acc_norm\": 0.7908256880733945,\n \"acc_norm_stderr\": 0.017437937173343233\n },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\": 0.4166666666666667,\n \"acc_stderr\": 0.03362277436608043,\n \"acc_norm\": 0.4166666666666667,\n \"acc_norm_stderr\": 0.03362277436608043\n },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.7696078431372549,\n \"acc_stderr\": 0.02955429260569506,\n \"acc_norm\": 0.7696078431372549,\n \"acc_norm_stderr\": 0.02955429260569506\n },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\": 0.7637130801687764,\n \"acc_stderr\": 0.02765215314415926,\n \"acc_norm\": 0.7637130801687764,\n \"acc_norm_stderr\": 0.02765215314415926\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\": 0.732824427480916,\n \"acc_stderr\": 0.038808483010823944,\n \"acc_norm\": 0.732824427480916,\n \"acc_norm_stderr\": 0.038808483010823944\n },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\": 0.7272727272727273,\n \"acc_stderr\": 0.04065578140908705,\n \"acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.04065578140908705\n },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7685185185185185,\n \"acc_stderr\": 0.04077494709252626,\n \"acc_norm\": 0.7685185185185185,\n \"acc_norm_stderr\": 0.04077494709252626\n },\n \"harness|hendrycksTest-logical_fallacies|5\": {\n \"acc\": 0.7239263803680982,\n \"acc_stderr\": 0.035123852837050475,\n \"acc_norm\": 0.7239263803680982,\n \"acc_norm_stderr\": 0.035123852837050475\n },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.41964285714285715,\n \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.41964285714285715,\n \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness|hendrycksTest-management|5\": {\n \"acc\": 0.8058252427184466,\n \"acc_stderr\": 0.03916667762822585,\n \"acc_norm\": 0.8058252427184466,\n \"acc_norm_stderr\": 0.03916667762822585\n },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8034188034188035,\n \"acc_stderr\": 0.026035386098951292,\n \"acc_norm\": 0.8034188034188035,\n \"acc_norm_stderr\": 0.026035386098951292\n },\n \"harness|hendrycksTest-medical_genetics|5\": {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.789272030651341,\n \"acc_stderr\": 0.014583812465862543,\n \"acc_norm\": 0.789272030651341,\n \"acc_norm_stderr\": 0.014583812465862543\n },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.630057803468208,\n \"acc_stderr\": 0.025992472029306376,\n \"acc_norm\": 0.630057803468208,\n \"acc_norm_stderr\": 0.025992472029306376\n },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.38212290502793295,\n \"acc_stderr\": 0.016251139711570762,\n \"acc_norm\": 0.38212290502793295,\n \"acc_norm_stderr\": 0.016251139711570762\n },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.6601307189542484,\n \"acc_stderr\": 0.02712195607138886,\n \"acc_norm\": 0.6601307189542484,\n \"acc_norm_stderr\": 0.02712195607138886\n },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6527331189710611,\n \"acc_stderr\": 0.027040745502307336,\n \"acc_norm\": 0.6527331189710611,\n \"acc_norm_stderr\": 0.027040745502307336\n },\n \"harness|hendrycksTest-prehistory|5\": {\n \"acc\": 0.6790123456790124,\n \"acc_stderr\": 0.025976566010862737,\n \"acc_norm\": 0.6790123456790124,\n \"acc_norm_stderr\": 0.025976566010862737\n },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\": 0.450354609929078,\n \"acc_stderr\": 0.02968010556502904,\n \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.02968010556502904\n },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3924380704041721,\n \"acc_stderr\": 0.012471243669229106,\n \"acc_norm\": 0.3924380704041721,\n \"acc_norm_stderr\": 0.012471243669229106\n },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\": 0.6066176470588235,\n \"acc_stderr\": 0.029674288281311155,\n \"acc_norm\": 0.6066176470588235,\n \"acc_norm_stderr\": 0.029674288281311155\n },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\": 0.6160130718954249,\n \"acc_stderr\": 0.01967580813528151,\n \"acc_norm\": 0.6160130718954249,\n \"acc_norm_stderr\": 0.01967580813528151\n },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6272727272727273,\n \"acc_stderr\": 0.046313813194254656,\n \"acc_norm\": 0.6272727272727273,\n \"acc_norm_stderr\": 0.046313813194254656\n },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.636734693877551,\n \"acc_stderr\": 0.03078905113903081,\n \"acc_norm\": 0.636734693877551,\n \"acc_norm_stderr\": 0.03078905113903081\n },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7761194029850746,\n \"acc_stderr\": 0.029475250236017204,\n \"acc_norm\": 0.7761194029850746,\n \"acc_norm_stderr\": 0.029475250236017204\n },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\": 0.83,\n \"acc_stderr\": 0.0377525168068637,\n \"acc_norm\": 0.83,\n \"acc_norm_stderr\": 0.0377525168068637\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\": 0.783625730994152,\n \"acc_stderr\": 0.031581495393387324,\n \"acc_norm\": 0.783625730994152,\n \"acc_norm_stderr\": 0.031581495393387324\n },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2778457772337821,\n \"mc1_stderr\": 0.015680929364024647,\n \"mc2\": 0.4001041496199733,\n \"mc2_stderr\": 0.014571617835253216\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.77663772691397,\n \"acc_stderr\": 0.011705697565205198\n },\n \"harness|drop|3\": {\n \"em\": 0.001572986577181208,\n \"em_stderr\": 0.00040584511324177344,\n \"f1\": 0.06579802852349013,\n \"f1_stderr\": 0.0014930152947085352\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.02047005307050796,\n \"acc_stderr\": 0.003900413385915721\n }\n}\n```"
repo_url: https://huggingface.co/euclaise/Ferret-7B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- >-
**/details_harness|arc:challenge|25_2023-11-19T15-52-54.018947.parquet
- split: 2023_11_25T02_44_41.580934
path:
- >-
**/details_harness|arc:challenge|25_2023-11-25T02-44-41.580934.parquet
- split: 2023_11_25T02_50_24.454188
path:
- >-
**/details_harness|arc:challenge|25_2023-11-25T02-50-24.454188.parquet
- split: 2023_11_25T03_02_51.561913
path:
- >-
**/details_harness|arc:challenge|25_2023-11-25T03-02-51.561913.parquet
- split: latest
path:
- >-
**/details_harness|arc:challenge|25_2023-11-25T03-02-51.561913.parquet
- config_name: harness_drop_3
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- '**/details_harness|drop|3_2023-11-19T15-52-54.018947.parquet'
- split: 2023_11_25T02_44_41.580934
path:
- '**/details_harness|drop|3_2023-11-25T02-44-41.580934.parquet'
- split: 2023_11_25T02_50_24.454188
path:
- '**/details_harness|drop|3_2023-11-25T02-50-24.454188.parquet'
- split: 2023_11_25T03_02_51.561913
path:
- '**/details_harness|drop|3_2023-11-25T03-02-51.561913.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-11-25T03-02-51.561913.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- '**/details_harness|gsm8k|5_2023-11-19T15-52-54.018947.parquet'
- split: 2023_11_25T02_44_41.580934
path:
- '**/details_harness|gsm8k|5_2023-11-25T02-44-41.580934.parquet'
- split: 2023_11_25T02_50_24.454188
path:
- '**/details_harness|gsm8k|5_2023-11-25T02-50-24.454188.parquet'
- split: 2023_11_25T03_02_51.561913
path:
- '**/details_harness|gsm8k|5_2023-11-25T03-02-51.561913.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-11-25T03-02-51.561913.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- '**/details_harness|hellaswag|10_2023-11-19T15-52-54.018947.parquet'
- split: 2023_11_25T02_44_41.580934
path:
- '**/details_harness|hellaswag|10_2023-11-25T02-44-41.580934.parquet'
- split: 2023_11_25T02_50_24.454188
path:
- '**/details_harness|hellaswag|10_2023-11-25T02-50-24.454188.parquet'
- split: 2023_11_25T03_02_51.561913
path:
- '**/details_harness|hellaswag|10_2023-11-25T03-02-51.561913.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-11-25T03-02-51.561913.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- >-
**/details_harness|hendrycksTest-abstract_algebra|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-anatomy|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-astronomy|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-business_ethics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-clinical_knowledge|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_biology|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_chemistry|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_computer_science|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_mathematics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_medicine|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-college_physics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-computer_security|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-conceptual_physics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-econometrics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-electrical_engineering|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-elementary_mathematics|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-formal_logic|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-global_facts|5_2023-11-19T15-52-54.018947.parquet
- >-
**/details_harness|hendrycksTest-high_school_biology|5_2023-11-19T15-52-54.018947.parquet
- >-
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- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
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- config_name: harness_hendrycksTest_anatomy_5
data_files:
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- config_name: harness_hendrycksTest_astronomy_5
data_files:
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- config_name: harness_hendrycksTest_business_ethics_5
data_files:
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- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
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- config_name: harness_hendrycksTest_college_biology_5
data_files:
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- config_name: harness_hendrycksTest_college_chemistry_5
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- config_name: harness_hendrycksTest_college_computer_science_5
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- config_name: harness_hendrycksTest_college_mathematics_5
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- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
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**/details_harness|hendrycksTest-world_religions|5_2023-11-25T02-50-24.454188.parquet
- split: 2023_11_25T03_02_51.561913
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-11-25T03-02-51.561913.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-11-25T03-02-51.561913.parquet
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- >-
**/details_harness|truthfulqa:mc|0_2023-11-19T15-52-54.018947.parquet
- split: 2023_11_25T02_44_41.580934
path:
- >-
**/details_harness|truthfulqa:mc|0_2023-11-25T02-44-41.580934.parquet
- split: 2023_11_25T02_50_24.454188
path:
- >-
**/details_harness|truthfulqa:mc|0_2023-11-25T02-50-24.454188.parquet
- split: 2023_11_25T03_02_51.561913
path:
- >-
**/details_harness|truthfulqa:mc|0_2023-11-25T03-02-51.561913.parquet
- split: latest
path:
- >-
**/details_harness|truthfulqa:mc|0_2023-11-25T03-02-51.561913.parquet
- config_name: harness_winogrande_5
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- '**/details_harness|winogrande|5_2023-11-19T15-52-54.018947.parquet'
- split: 2023_11_25T02_44_41.580934
path:
- '**/details_harness|winogrande|5_2023-11-25T02-44-41.580934.parquet'
- split: 2023_11_25T02_50_24.454188
path:
- '**/details_harness|winogrande|5_2023-11-25T02-50-24.454188.parquet'
- split: 2023_11_25T03_02_51.561913
path:
- '**/details_harness|winogrande|5_2023-11-25T03-02-51.561913.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-11-25T03-02-51.561913.parquet'
- config_name: results
data_files:
- split: 2023_11_19T15_52_54.018947
path:
- results_2023-11-19T15-52-54.018947.parquet
- split: 2023_11_25T02_44_41.580934
path:
- results_2023-11-25T02-44-41.580934.parquet
- split: 2023_11_25T02_50_24.454188
path:
- results_2023-11-25T02-50-24.454188.parquet
- split: 2023_11_25T03_02_51.561913
path:
- results_2023-11-25T03-02-51.561913.parquet
- split: latest
path:
- results_2023-11-25T03-02-51.561913.parquet
Dataset Card for Evaluation run of euclaise/Ferret-7B
Dataset Description
- Homepage:
- Repository: https://huggingface.co/euclaise/Ferret-7B
- Paper:
- Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- Point of Contact: clementine@hf.co
Dataset Summary
Dataset automatically created during the evaluation run of model euclaise/Ferret-7B on the 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 4 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).
To load the details from a run, you can for instance do the following:
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_euclaise__Ferret-7B_public",
"harness_winogrande_5",
split="train")
Latest results
These are the latest results from run 2023-11-25T03:02:51.561913(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):
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"harness|hendrycksTest-logical_fallacies|5": {
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"harness|hendrycksTest-management|5": {
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"harness|hendrycksTest-marketing|5": {
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"harness|gsm8k|5": {
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}
}
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
[More Information Needed]