datasetId
stringlengths 2
117
| author
stringlengths 2
42
⌀ | last_modified
timestamp[us, tz=UTC] | downloads
int64 0
9.36M
| likes
int64 0
3.89k
| tags
sequence | task_categories
sequence | createdAt
timestamp[us, tz=UTC] | card
stringlengths 19
1.01M
| embedding
sequence |
|---|---|---|---|---|---|---|---|---|---|
reza-alipour/con-eng-seg-4 | reza-alipour | 2023-12-11T11:44:01Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T11:43:54Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 20218499.0
num_examples: 50
download_size: 20219748
dataset_size: 20218499.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/con-eng-seg-5 | reza-alipour | 2023-12-11T12:08:39Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T11:54:33Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 40501119.0
num_examples: 100
download_size: 40500091
dataset_size: 40501119.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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DIAS123/AMARILSON | DIAS123 | 2023-12-11T11:56:31Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T11:55:31Z | ---
license: openrail
---
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567-labs/wikipedia-embedding-sample | 567-labs | 2023-12-11T12:05:46Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T12:04:24Z | ---
dataset_info:
features:
- name: text
dtype: string
- name: embedding
sequence: float64
splits:
- name: train
num_bytes: 2316774622
num_examples: 353730
download_size: 2351371774
dataset_size: 2316774622
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/con-eng-seg-6 | reza-alipour | 2023-12-11T12:17:34Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T12:17:24Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 40437887.0
num_examples: 100
download_size: 40437035
dataset_size: 40437887.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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] |
Predict9731/voxpopuli_windows_cs | Predict9731 | 2023-12-11T12:28:22Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T12:19:28Z | ---
dataset_info:
features:
- name: audio_id
dtype: string
- name: language
dtype:
class_label:
names:
'0': en
'1': de
'2': fr
'3': es
'4': pl
'5': it
'6': ro
'7': hu
'8': cs
'9': nl
'10': fi
'11': hr
'12': sk
'13': sl
'14': et
'15': lt
'16': en_accented
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: raw_text
dtype: string
- name: normalized_text
dtype: string
- name: gender
dtype: string
- name: speaker_id
dtype: string
- name: is_gold_transcript
dtype: bool
- name: accent
dtype: string
splits:
- name: train
num_bytes: 6549063392.628
num_examples: 18902
download_size: 10449462424
dataset_size: 6549063392.628
---
# Dataset Card for "voxpopuli_windows_cs"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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SasnayaLetovka/rep_name | SasnayaLetovka | 2023-12-11T12:24:43Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T12:24:41Z | ---
dataset_info:
features:
- name: image
dtype: int64
- name: input_ids
sequence: int64
- name: attention_mask
sequence: int64
- name: token_type_ids
sequence: int64
- name: bbox
dtype: int64
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 49248
num_examples: 3
- name: test
num_bytes: 49248
num_examples: 3
- name: val
num_bytes: 49248
num_examples: 3
download_size: 18994
dataset_size: 147744
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: val
path: data/val-*
---
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MatsuoDochiai/Samuel | MatsuoDochiai | 2023-12-11T12:36:13Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T12:35:25Z | ---
license: openrail
---
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reza-alipour/con-eng-seg-7 | reza-alipour | 2023-12-11T12:59:17Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T12:58:40Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 202297183.0
num_examples: 498
download_size: 202286341
dataset_size: 202297183.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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open-llm-leaderboard/details_Deci__DeciLM-7B | open-llm-leaderboard | 2023-12-12T13:55:39Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T13:08:44Z | ---
pretty_name: Evaluation run of Deci/DeciLM-7B
dataset_summary: "Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B](https://huggingface.co/Deci/DeciLM-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\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Deci-early-access__DeciLM-7B-early_private\",\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-12-11T13:05:55.242370](https://huggingface.co/datasets/open-llm-leaderboard/details_Deci-early-access__DeciLM-7B-early_private/blob/main/results_2023-12-11T13-05-55.242370.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\": 0.5986461662246719,\n \"acc_stderr\": 0.03322810922254394,\n \"acc_norm\": 0.6014214623320648,\n \"acc_norm_stderr\": 0.03391006890945986,\n \"mc1\": 0.2692778457772338,\n \"mc1_stderr\": 0.015528566637087295,\n \"mc2\": 0.4032625331106103,\n \"mc2_stderr\": 0.01398363920569579\n },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.552901023890785,\n \"acc_stderr\": 0.014529380160526843,\n \"acc_norm\": 0.5938566552901023,\n \"acc_norm_stderr\": 0.014351656690097862\n },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6262696673969329,\n \"acc_stderr\": 0.004828045774734898,\n \"acc_norm\": 0.8251344353714399,\n \"acc_norm_stderr\": 0.0037907576465758953\n },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5407407407407407,\n \"acc_stderr\": 0.04304979692464242,\n \"acc_norm\": 0.5407407407407407,\n \"acc_norm_stderr\": 0.04304979692464242\n },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.6644736842105263,\n \"acc_stderr\": 0.03842498559395268,\n \"acc_norm\": 0.6644736842105263,\n \"acc_norm_stderr\": 0.03842498559395268\n },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.56,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.56,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.6792452830188679,\n \"acc_stderr\": 0.028727502957880267,\n \"acc_norm\": 0.6792452830188679,\n \"acc_norm_stderr\": 0.028727502957880267\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\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_computer_science|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-college_mathematics|5\": {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.630057803468208,\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\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287533,\n \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287533\n },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\": {\n \"acc\": 0.5106382978723404,\n \"acc_stderr\": 0.03267862331014063,\n \"acc_norm\": 0.5106382978723404,\n \"acc_norm_stderr\": 0.03267862331014063\n },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.40350877192982454,\n \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness|hendrycksTest-electrical_engineering|5\": {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.38095238095238093,\n \"acc_stderr\": 0.025010749116137595,\n \"acc_norm\": 0.38095238095238093,\n \"acc_norm_stderr\": 0.025010749116137595\n },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.3412698412698413,\n \"acc_stderr\": 0.04240799327574924,\n \"acc_norm\": 0.3412698412698413,\n \"acc_norm_stderr\": 0.04240799327574924\n },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7225806451612903,\n \"acc_stderr\": 0.025470196835900055,\n \"acc_norm\": 0.7225806451612903,\n \"acc_norm_stderr\": 0.025470196835900055\n },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\": 0.46798029556650245,\n \"acc_stderr\": 0.035107665979592154,\n \"acc_norm\": 0.46798029556650245,\n \"acc_norm_stderr\": 0.035107665979592154\n },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\": 0.62,\n \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-high_school_european_history|5\": {\n \"acc\": 0.7272727272727273,\n \"acc_stderr\": 0.0347769116216366,\n \"acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.0347769116216366\n },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\": 0.7474747474747475,\n \"acc_stderr\": 0.030954055470365897,\n \"acc_norm\": 0.7474747474747475,\n \"acc_norm_stderr\": 0.030954055470365897\n },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \"acc\": 0.8393782383419689,\n \"acc_stderr\": 0.02649905770139746,\n \"acc_norm\": 0.8393782383419689,\n \"acc_norm_stderr\": 0.02649905770139746\n },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \"acc\": 0.5794871794871795,\n \"acc_stderr\": 0.025028610276710855,\n \"acc_norm\": 0.5794871794871795,\n \"acc_norm_stderr\": 0.025028610276710855\n },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"acc\": 0.3888888888888889,\n \"acc_stderr\": 0.029723278961476668,\n \"acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.029723278961476668\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \"acc\": 0.6260504201680672,\n \"acc_stderr\": 0.03142946637883708,\n \"acc_norm\": 0.6260504201680672,\n \"acc_norm_stderr\": 0.03142946637883708\n },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\": 0.3841059602649007,\n \"acc_stderr\": 0.03971301814719197,\n \"acc_norm\": 0.3841059602649007,\n \"acc_norm_stderr\": 0.03971301814719197\n },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.7871559633027523,\n \"acc_stderr\": 0.017549376389313694,\n \"acc_norm\": 0.7871559633027523,\n \"acc_norm_stderr\": 0.017549376389313694\n },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\": 0.47685185185185186,\n \"acc_stderr\": 0.03406315360711507,\n \"acc_norm\": 0.47685185185185186,\n \"acc_norm_stderr\": 0.03406315360711507\n },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.7598039215686274,\n \"acc_stderr\": 0.02998373305591362,\n \"acc_norm\": 0.7598039215686274,\n \"acc_norm_stderr\": 0.02998373305591362\n },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\": 0.7805907172995781,\n \"acc_stderr\": 0.026939106581553945,\n \"acc_norm\": 0.7805907172995781,\n \"acc_norm_stderr\": 0.026939106581553945\n },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6681614349775785,\n \"acc_stderr\": 0.03160295143776679,\n \"acc_norm\": 0.6681614349775785,\n \"acc_norm_stderr\": 0.03160295143776679\n },\n \"harness|hendrycksTest-human_sexuality|5\": {\n \"acc\": 0.6946564885496184,\n \"acc_stderr\": 0.040393149787245605,\n \"acc_norm\": 0.6946564885496184,\n \"acc_norm_stderr\": 0.040393149787245605\n },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\": 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\": 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\": {\n \"acc\": 0.6871165644171779,\n \"acc_stderr\": 0.036429145782924055,\n \"acc_norm\": 0.6871165644171779,\n \"acc_norm_stderr\": 0.036429145782924055\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\": 0.7475728155339806,\n \"acc_stderr\": 0.04301250399690878,\n \"acc_norm\": 0.7475728155339806,\n \"acc_norm_stderr\": 0.04301250399690878\n },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8461538461538461,\n \"acc_stderr\": 0.02363687331748927,\n \"acc_norm\": 0.8461538461538461,\n \"acc_norm_stderr\": 0.02363687331748927\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\": 0.7879948914431673,\n \"acc_stderr\": 0.01461609938583368,\n \"acc_norm\": 0.7879948914431673,\n \"acc_norm_stderr\": 0.01461609938583368\n },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.6705202312138728,\n \"acc_stderr\": 0.025305258131879695,\n \"acc_norm\": 0.6705202312138728,\n \"acc_norm_stderr\": 0.025305258131879695\n },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n \"acc_stderr\": 0.01433352205921789,\n \"acc_norm\": 0.2424581005586592,\n \"acc_norm_stderr\": 0.01433352205921789\n },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.696078431372549,\n \"acc_stderr\": 0.02633661346904663,\n \"acc_norm\": 0.696078431372549,\n \"acc_norm_stderr\": 0.02633661346904663\n },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6688102893890675,\n \"acc_stderr\": 0.02673062072800491,\n \"acc_norm\": 0.6688102893890675,\n \"acc_norm_stderr\": 0.02673062072800491\n },\n \"harness|hendrycksTest-prehistory|5\": {\n \"acc\": 0.6728395061728395,\n \"acc_stderr\": 0.026105673861409825,\n \"acc_norm\": 0.6728395061728395,\n \"acc_norm_stderr\": 0.026105673861409825\n },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\": 0.4645390070921986,\n \"acc_stderr\": 0.029752389657427047,\n \"acc_norm\": 0.4645390070921986,\n \"acc_norm_stderr\": 0.029752389657427047\n },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4276401564537158,\n \"acc_stderr\": 0.012635799922765846,\n \"acc_norm\": 0.4276401564537158,\n \"acc_norm_stderr\": 0.012635799922765846\n },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\": 0.6139705882352942,\n \"acc_stderr\": 0.029573269134411124,\n \"acc_norm\": 0.6139705882352942,\n \"acc_norm_stderr\": 0.029573269134411124\n },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\": 0.5915032679738562,\n \"acc_stderr\": 0.01988622103750187,\n \"acc_norm\": 0.5915032679738562,\n \"acc_norm_stderr\": 0.01988622103750187\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\": 0.7183673469387755,\n \"acc_stderr\": 0.02879518557429129,\n \"acc_norm\": 0.7183673469387755,\n \"acc_norm_stderr\": 0.02879518557429129\n },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8208955223880597,\n \"acc_stderr\": 0.027113286753111837,\n \"acc_norm\": 0.8208955223880597,\n \"acc_norm_stderr\": 0.027113286753111837\n },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\": 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\": 0.77,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4939759036144578,\n \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.4939759036144578,\n \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.8011695906432749,\n \"acc_stderr\": 0.030611116557432528,\n \"acc_norm\": 0.8011695906432749,\n \"acc_norm_stderr\": 0.030611116557432528\n },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2692778457772338,\n \"mc1_stderr\": 0.015528566637087295,\n \"mc2\": 0.4032625331106103,\n \"mc2_stderr\": 0.01398363920569579\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.7995264404104183,\n \"acc_stderr\": 0.011251958281205083\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.47384382107657314,\n \"acc_stderr\": 0.013753627037255045\n }\n}\n```"
repo_url: https://huggingface.co/Deci/DeciLM-7B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- '**/details_harness|arc:challenge|25_2023-12-11T13-05-55.242370.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-11T13-05-55.242370.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- '**/details_harness|gsm8k|5_2023-12-11T13-05-55.242370.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-11T13-05-55.242370.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- '**/details_harness|hellaswag|10_2023-12-11T13-05-55.242370.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-11T13-05-55.242370.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-anatomy|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-astronomy|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_biology|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-college_physics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-computer_security|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-econometrics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-global_facts|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-human_aging|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-international_law|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-management|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-marketing|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-nutrition|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-philosophy|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-prehistory|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-professional_law|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T13-05-55.242370.parquet
- >-
**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T13-05-55.242370.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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**/details_harness|hendrycksTest-college_biology|5_2023-12-11T13-05-55.242370.parquet
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**/details_harness|hendrycksTest-college_biology|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
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- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
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- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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- config_name: harness_hendrycksTest_college_physics_5
data_files:
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- config_name: harness_hendrycksTest_computer_security_5
data_files:
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- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
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- config_name: harness_hendrycksTest_econometrics_5
data_files:
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- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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- config_name: harness_hendrycksTest_global_facts_5
data_files:
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- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
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- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
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**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T13-05-55.242370.parquet
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**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T13-05-55.242370.parquet
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**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
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- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
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- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
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- config_name: harness_hendrycksTest_human_aging_5
data_files:
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- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
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**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-international_law|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-international_law|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-management|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-management|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-marketing|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-marketing|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-nutrition|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-nutrition|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-philosophy|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-philosophy|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-prehistory|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-prehistory|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-professional_law|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-professional_law|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-public_relations|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-public_relations|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-security_studies|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-security_studies|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-sociology|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-sociology|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-virology|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-virology|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-12-11T13-05-55.242370.parquet
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T13-05-55.242370.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T13-05-55.242370.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- '**/details_harness|winogrande|5_2023-12-11T13-05-55.242370.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-11T13-05-55.242370.parquet'
- config_name: results
data_files:
- split: 2023_12_11T13_05_55.242370
path:
- results_2023-12-11T13-05-55.242370.parquet
- split: latest
path:
- results_2023-12-11T13-05-55.242370.parquet
---
# Dataset Card for Evaluation run of Deci/DeciLM-7B
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Deci/DeciLM-7B
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B](https://huggingface.co/Deci/DeciLM-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_Deci/DeciLM-7B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-11T13:05:55.242370](https://huggingface.co/datasets/open-llm-leaderboard/details_Deci__DeciLM-7B/blob/main/results_2023-12-11T13-05-55.242370.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": 0.5986461662246719,
"acc_stderr": 0.03322810922254394,
"acc_norm": 0.6014214623320648,
"acc_norm_stderr": 0.03391006890945986,
"mc1": 0.2692778457772338,
"mc1_stderr": 0.015528566637087295,
"mc2": 0.4032625331106103,
"mc2_stderr": 0.01398363920569579
},
"harness|arc:challenge|25": {
"acc": 0.552901023890785,
"acc_stderr": 0.014529380160526843,
"acc_norm": 0.5938566552901023,
"acc_norm_stderr": 0.014351656690097862
},
"harness|hellaswag|10": {
"acc": 0.6262696673969329,
"acc_stderr": 0.004828045774734898,
"acc_norm": 0.8251344353714399,
"acc_norm_stderr": 0.0037907576465758953
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.24,
"acc_stderr": 0.04292346959909283,
"acc_norm": 0.24,
"acc_norm_stderr": 0.04292346959909283
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.5407407407407407,
"acc_stderr": 0.04304979692464242,
"acc_norm": 0.5407407407407407,
"acc_norm_stderr": 0.04304979692464242
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6644736842105263,
"acc_stderr": 0.03842498559395268,
"acc_norm": 0.6644736842105263,
"acc_norm_stderr": 0.03842498559395268
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.56,
"acc_stderr": 0.04988876515698589,
"acc_norm": 0.56,
"acc_norm_stderr": 0.04988876515698589
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6792452830188679,
"acc_stderr": 0.028727502957880267,
"acc_norm": 0.6792452830188679,
"acc_norm_stderr": 0.028727502957880267
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.6944444444444444,
"acc_stderr": 0.03852084696008534,
"acc_norm": 0.6944444444444444,
"acc_norm_stderr": 0.03852084696008534
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.42,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.42,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.42,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.42,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.35,
"acc_stderr": 0.0479372485441102,
"acc_norm": 0.35,
"acc_norm_stderr": 0.0479372485441102
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.630057803468208,
"acc_stderr": 0.0368122963339432,
"acc_norm": 0.630057803468208,
"acc_norm_stderr": 0.0368122963339432
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.43137254901960786,
"acc_stderr": 0.04928099597287533,
"acc_norm": 0.43137254901960786,
"acc_norm_stderr": 0.04928099597287533
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.72,
"acc_stderr": 0.045126085985421276,
"acc_norm": 0.72,
"acc_norm_stderr": 0.045126085985421276
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5106382978723404,
"acc_stderr": 0.03267862331014063,
"acc_norm": 0.5106382978723404,
"acc_norm_stderr": 0.03267862331014063
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.40350877192982454,
"acc_stderr": 0.046151869625837026,
"acc_norm": 0.40350877192982454,
"acc_norm_stderr": 0.046151869625837026
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5448275862068965,
"acc_stderr": 0.04149886942192117,
"acc_norm": 0.5448275862068965,
"acc_norm_stderr": 0.04149886942192117
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.38095238095238093,
"acc_stderr": 0.025010749116137595,
"acc_norm": 0.38095238095238093,
"acc_norm_stderr": 0.025010749116137595
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.3412698412698413,
"acc_stderr": 0.04240799327574924,
"acc_norm": 0.3412698412698413,
"acc_norm_stderr": 0.04240799327574924
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7225806451612903,
"acc_stderr": 0.025470196835900055,
"acc_norm": 0.7225806451612903,
"acc_norm_stderr": 0.025470196835900055
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.46798029556650245,
"acc_stderr": 0.035107665979592154,
"acc_norm": 0.46798029556650245,
"acc_norm_stderr": 0.035107665979592154
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.62,
"acc_stderr": 0.048783173121456316,
"acc_norm": 0.62,
"acc_norm_stderr": 0.048783173121456316
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7272727272727273,
"acc_stderr": 0.0347769116216366,
"acc_norm": 0.7272727272727273,
"acc_norm_stderr": 0.0347769116216366
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7474747474747475,
"acc_stderr": 0.030954055470365897,
"acc_norm": 0.7474747474747475,
"acc_norm_stderr": 0.030954055470365897
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8393782383419689,
"acc_stderr": 0.02649905770139746,
"acc_norm": 0.8393782383419689,
"acc_norm_stderr": 0.02649905770139746
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.5794871794871795,
"acc_stderr": 0.025028610276710855,
"acc_norm": 0.5794871794871795,
"acc_norm_stderr": 0.025028610276710855
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.3888888888888889,
"acc_stderr": 0.029723278961476668,
"acc_norm": 0.3888888888888889,
"acc_norm_stderr": 0.029723278961476668
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6260504201680672,
"acc_stderr": 0.03142946637883708,
"acc_norm": 0.6260504201680672,
"acc_norm_stderr": 0.03142946637883708
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.3841059602649007,
"acc_stderr": 0.03971301814719197,
"acc_norm": 0.3841059602649007,
"acc_norm_stderr": 0.03971301814719197
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.7871559633027523,
"acc_stderr": 0.017549376389313694,
"acc_norm": 0.7871559633027523,
"acc_norm_stderr": 0.017549376389313694
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.47685185185185186,
"acc_stderr": 0.03406315360711507,
"acc_norm": 0.47685185185185186,
"acc_norm_stderr": 0.03406315360711507
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.7598039215686274,
"acc_stderr": 0.02998373305591362,
"acc_norm": 0.7598039215686274,
"acc_norm_stderr": 0.02998373305591362
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7805907172995781,
"acc_stderr": 0.026939106581553945,
"acc_norm": 0.7805907172995781,
"acc_norm_stderr": 0.026939106581553945
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6681614349775785,
"acc_stderr": 0.03160295143776679,
"acc_norm": 0.6681614349775785,
"acc_norm_stderr": 0.03160295143776679
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.6946564885496184,
"acc_stderr": 0.040393149787245605,
"acc_norm": 0.6946564885496184,
"acc_norm_stderr": 0.040393149787245605
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.768595041322314,
"acc_stderr": 0.03849856098794088,
"acc_norm": 0.768595041322314,
"acc_norm_stderr": 0.03849856098794088
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7129629629629629,
"acc_stderr": 0.043733130409147614,
"acc_norm": 0.7129629629629629,
"acc_norm_stderr": 0.043733130409147614
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.6871165644171779,
"acc_stderr": 0.036429145782924055,
"acc_norm": 0.6871165644171779,
"acc_norm_stderr": 0.036429145782924055
},
"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": 0.7475728155339806,
"acc_stderr": 0.04301250399690878,
"acc_norm": 0.7475728155339806,
"acc_norm_stderr": 0.04301250399690878
},
"harness|hendrycksTest-marketing|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] | [
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MaxYuki/Nini | MaxYuki | 2023-12-11T13:34:32Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T13:27:16Z | ---
license: apache-2.0
---
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filipeaugustogxp/gekko | filipeaugustogxp | 2023-12-11T17:36:03Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T13:39:38Z | ---
license: openrail
---
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MSheng-Lee/M3DBench | MSheng-Lee | 2023-12-11T13:44:14Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-11T13:41:32Z | ---
license: mit
---
The Dataset of M3DBench | [
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peterholdsworth/vangogh | peterholdsworth | 2023-12-11T13:49:05Z | 0 | 0 | [
"license:unknown",
"region:us"
] | null | 2023-12-11T13:45:21Z | ---
license: unknown
---
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MaxYuki/Ryo | MaxYuki | 2023-12-11T13:57:15Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T13:53:28Z | ---
license: apache-2.0
---
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Flavinhouaua2022/JL | Flavinhouaua2022 | 2023-12-11T13:57:12Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T13:56:49Z | ---
license: openrail
---
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lili98/tarja1 | lili98 | 2023-12-11T14:38:37Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T14:10:38Z | ---
license: openrail
---
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anthony-wss/librispeech_asr-audiodec_44k | anthony-wss | 2023-12-13T04:31:36Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T14:11:39Z | ---
configs:
- config_name: default
data_files:
- split: train.clean.360
path: data/train.clean.360-*
- split: train.other.500
path: data/train.other.500-*
dataset_info:
features:
- name: text
dtype: string
- name: id
dtype: string
- name: unit
sequence:
sequence: int64
splits:
- name: train.clean.360
num_bytes: 10788010668
num_examples: 104014
- name: train.other.500
num_bytes: 14756337873
num_examples: 148688
download_size: 3925792960
dataset_size: 25544348541
---
# Dataset Card for "librispeech_asr-audiodec_44k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Renatanimareli/Renatasantosaudios | Renatanimareli | 2023-12-11T14:31:30Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T14:31:30Z | ---
license: openrail
---
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Renatanimareli/renatanimareli | Renatanimareli | 2023-12-11T14:34:48Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T14:34:48Z | ---
license: openrail
---
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Renatanimareli/renatanimarelii | Renatanimareli | 2023-12-11T14:41:23Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T14:39:19Z | ---
license: openrail
---
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projecte-aina/openslr-slr69-ca-trimmed-denoised | projecte-aina | 2023-12-17T10:27:01Z | 0 | 0 | [
"task_categories:text-to-speech",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:openslr",
"language:ca",
"license:cc-by-sa-4.0",
"arxiv:2202.07790",
"region:us"
] | [
"text-to-speech"
] | 2023-12-11T14:43:28Z | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets: openslr
task_categories:
- text-to-speech
task_ids: []
pretty_name: openslr-slr69-ca-reviewed
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 811311975.4
num_examples: 4240
download_size: 721217811
dataset_size: 811311975.4
---
# Dataset Card for openslr-slr69-ca-denoised
## Dataset Details
This is a post-processed version of the Catalan subset belonging to the [Open Speech and Language Resources (OpenSLR)](https://www.openslr.org/index.html) speech dataset.
Specifically the subset [OpenSLR-69](https://www.openslr.org/69).
The original HF🤗 SLR-69 dataset is located [here](https://huggingface.co/datasets/openslr/viewer/SLR69)
### Dataset Description
We processed the data of the Catalan OpenSLR with the following recipe:
- **Trimming:** Long silences from the start and the end of clips have been removed.
- [py-webrtcvad](https://pypi.org/project/webrtcvad/) -> Python interface to the Voice Activity Detector (VAD) developed by Google for the WebRTC.
- **Resampling:** From 48000 Hz to 22050 Hz, which is the most common sampling rate for training TTS models
- Resampler from [CoquiTTS](https://github.com/coqui-ai/TTS/tree/dev) framework
- **Denoising:** Although base quality of the audios is high, we could remove some background noise and small artifcats thanks to the CleanUNet denoiser developed by NVIDIA.
- [CleanUNet](https://github.com/NVIDIA/CleanUNet) - [arXiv](https://arxiv.org/abs/2202.07790)
We kept the same number of wave files, also the original anonymized file names and transcriptions.
Same license is maintained: [Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by/4.0/)
## Uses
The purpose of this dataset is mainly for training text-to-speech and automatic speech recognition models in Catalan.
## 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. -->
The dataset consists of a single split, providing audios and transcriptions:
```
DatasetDict({
train: Dataset({
features: ['audio', 'transcription'],
num_rows: 4240
})
})
```
Each data point is structured as:
```
>> data['train'][0]['audio']
{'path': 'caf_09901_01619988267.wav',
'array': array([-3.05175781e-05, -3.05175781e-05, -3.05175781e-05, ..., -6.10351562e-05, -6.10351562e-05, -6.10351562e-05])
'sampling_rate': 22050}
>> data['train'][0]['transcription']
"L'òpera de Sydney es troba a l'entrada de la badia"
```
### Dataset Splits
- ```audio (dict)```: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: ```dataset[0]["audio"]``` the audio file is automatically decoded and resampled to ```dataset.features["audio"].sampling_rate```. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus, it is important to first query the sample index before the "audio" column, i.e. ```dataset[0]["audio"]``` should always be preferred over ```dataset["audio"][0]```.
* ```path (str)```: The path to the audio file.
* ```array (array)```: Decoded audio array.
* ```sampling_rate (int)```: Audio sampling rate.
- ```transcription (str)```: The sentence the user was prompted to speak.
## Dataset Creation
#### SLR69: Crowdsourced high-quality Catalan multi-speaker speech data set
This data set contains transcribed high-quality audio of Catalan sentences recorded by volunteers. The recordings
were prepared with the help of Direcció General de Política Lingüística del Departament de Cultura, Generalitat de
Catalunya. The data set consists of wave files, and a TSV file (line_index.tsv). The file line_index.tsv contains
an anonymized FileID and the transcription of audio in the file.
The data set has been manually quality checked, but there might still be errors.
Please report any issues in the following issue tracker on GitHub. https://github.com/googlei18n/language-resources/issues
The original dataset is distributed under Creative Commons Attribution-ShareAlike 4.0 International Public License.
See [LICENSE](https://www.openslr.org/resources/69/LICENSE) file and
https://github.com/google/language-resources#license for license information.
#### 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. -->
#### Who are the source data producers?
Copyright 2018, 2019 Google, Inc.
### Annotations
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### 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. -->
The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset.
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
### 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
The original paper where authors detail how OpenSLR-69 was generated:
```
@inproceedings{kjartansson-etal-2020-open,
title = {{Open-Source High Quality Speech Datasets for Basque, Catalan and Galician}},
author = {Kjartansson, Oddur and Gutkin, Alexander and Butryna, Alena and Demirsahin, Isin and Rivera, Clara},
booktitle = {Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)},
year = {2020},
pages = {21--27},
month = may,
address = {Marseille, France},
publisher = {European Language Resources association (ELRA)},
url = {https://www.aclweb.org/anthology/2020.sltu-1.3},
ISBN = {979-10-95546-35-1},
}
```
**APA:**
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
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] |
el2e10/aya-paraphrase | el2e10 | 2023-12-15T09:10:18Z | 0 | 0 | [
"task_categories:text-generation",
"size_categories:n<1K",
"source_datasets:extended|ai4bharat/IndicXParaphrase",
"language:ml",
"language:pa",
"language:mr",
"language:gu",
"language:hi",
"language:bn",
"license:cc",
"region:us"
] | [
"text-generation"
] | 2023-12-11T14:48:09Z | ---
license: cc
task_categories:
- text-generation
language:
- ml
- pa
- mr
- gu
- hi
- bn
size_categories:
- n<1K
pretty_name: Aya Paraphrase
source_datasets:
- extended|ai4bharat/IndicXParaphrase
configs:
- config_name: marathi
data_files: mr.csv
- config_name: gujarati
data_files: gu.csv
- config_name: malayalam
data_files: ml.csv
- config_name: panjabi
data_files: pa.csv
- config_name: bengali
data_files: bn.csv
- config_name: hindi
data_files: hi.csv
---
### Description
This dataset is derived from the already existing dataset made by AI4Bharat. We have used the [IndicXParaphrase](https://huggingface.co/datasets/ai4bharat/IndicXParaphrase) dataset of AI4Bharat to create this instruction style dataset.
We have used the malayalam split of the above mentioned dataset to create this one. This was created as part of [Aya Open Science Initiative](https://sites.google.com/cohere.com/aya-en/home) from Cohere For AI.
IndicXParaphrase is multilingual, and n-way parallel dataset for paraphrase detection in 10 Indic languages. The original dataset(IndicXParaphrase) was made available under the cc-0 license.
### Template
The following templates(Malayalam) where used for converting the original dataset:
```
prompt:
ഇനിപ്പറയുന്ന വാചകം വ്യത്യസ്ത വാക്കുകളിൽ എഴുതുക: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
ഇനിപ്പറയുന്ന വാചകം മറ്റൊരു രീതിയിൽ എഴുതുക: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
താഴെപ്പറയുന്ന വാചകം പരാവർത്തനം ചെയ്യുക: "{original_sentence}"
completion:
{paraphrased_sentence}
```
The following templates(Gujarati) where used for converting the original dataset:
```
prompt:
નીચેના વાક્યને અલગ શબ્દોનો ઉપયોગ કરીને લખો: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
નીચેના વાક્યને અલગ રીતે ફરીથી લખો: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
નીચેના વાક્યને બીજા સ્વરૂપમાં ફરીથી લખો: "{original_sentence}"
completion:
{paraphrased_sentence}
```
The following templates(Punjabi) where used for converting the original dataset:
```
prompt:
ਵੱਖ-ਵੱਖ ਸ਼ਬਦਾਂ ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਹੇਠਾਂ ਦਿੱਤੇ ਵਾਕ ਨੂੰ ਲਿਖੋ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
ਨਿਮਨਲਿਖਤ ਵਾਕ ਨੂੰ ਵੱਖਰੇ ਤਰੀਕੇ ਨਾਲ ਦੁਬਾਰਾ ਲਿਖੋ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
ਹੇਠਾਂ ਦਿੱਤੇ ਵਾਕ ਨੂੰ ਸਮਝਾਓ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
The following templates(Marathi) where used for converting the original dataset:
```
prompt:
खालील वाक्य दुसरे-भिन्न शब्द वापरून लिहा: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
खालील वाक्य वेगळ्या प्रकारे पुन्हा लिहा: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
खालील वाक्य दुसरे शब्द वापरून रूपांतरित-अनुवादित करा: "{original_sentence}"
completion:
{paraphrased_sentence}
```
The following templates(Bengali) where used for converting the original dataset:
```
prompt:
ভিন্ন শব্দগুচ্ছ ব্যবহার করে নিচের বাক্যটি লেখ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
নিচের বাক্যটি ভিন্নভাবে লেখ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
অর্থের পরিবর্তন না করে নিচের বাক্যটি নতুনভাবে লেখ: "{original_sentence}"
completion:
{paraphrased_sentence}
```
The following templates(Hindi) where used for converting the original dataset:
```
prompt:
दुसरे शब्दों का प्रयोग करके इस वाक्य को लिखिए: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
इस वाक्य को अन्य तरीके से फिर से लिखिए: "{original_sentence}"
completion:
{paraphrased_sentence}
```
```
prompt:
निम्नलिखित वाक्य का अर्थ बदले बिना उसे दोबारा लिखिए: "{original_sentence}"
completion:
{paraphrased_sentence}
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Lemone-io/lpf | Lemone-io | 2023-12-11T14:50:55Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"tax",
"llm",
"fiscal",
"lpf",
"Livre des procédures fiscales",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-11T14:50:04Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- tax
- llm
- fiscal
- lpf
- Livre des procédures fiscales
source_datasets:
- original
pretty_name: Livre des procédures fiscales (LPF)
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- n<1K
---
# Livre des procédures fiscales, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `version`: `string`, denoting the version associated with the element.
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
- `complexity`: `int`, reflecting the degree of abstraction requested from the LLM (Legal Language Model). A value of 1 represents an instruction grounded in authoritative text, while 2 introduces added complexity or abstraction.
- `created_at`: `date`, capturing the date and time of the document's creation.
- `updated_at`: `date`, detailing the most recent update's date and time.
- `expiration`: `date`, delineating the expiration date of the legal information.
- `status`: `string`, specifying the application status of the law.
- `coming_into_force`: `date`, signifying the date when the legal information becomes enforceable.
- `language`: `string`, describing the language in which the legal information is presented.
- `length`: `int`, offering information regarding the length of the legal content.
- `source`: `string`, representing the source from which the legal information originated.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Livre des procédures fiscales, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/lpf}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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Lemone-io/cgi | Lemone-io | 2023-12-11T14:55:57Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"tax",
"llm",
"fiscal",
"cgi",
"Code Général des Impôts",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-11T14:55:01Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- tax
- llm
- fiscal
- cgi
- Code Général des Impôts
source_datasets:
- original
pretty_name: Code Général des Impôts (CGI)
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- 1K<n<10K
---
# Code Général des Impôts, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `version`: `string`, denoting the version associated with the element.
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
- `complexity`: `int`, reflecting the degree of abstraction requested from the LLM (Legal Language Model). A value of 1 represents an instruction grounded in authoritative text, while 2 introduces added complexity or abstraction.
- `created_at`: `date`, capturing the date and time of the document's creation.
- `updated_at`: `date`, detailing the most recent update's date and time.
- `expiration`: `date`, delineating the expiration date of the legal information.
- `status`: `string`, specifying the application status of the law.
- `coming_into_force`: `date`, signifying the date when the legal information becomes enforceable.
- `language`: `string`, describing the language in which the legal information is presented.
- `length`: `int`, offering information regarding the length of the legal content.
- `source`: `string`, representing the source from which the legal information originated.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Code Général des Impôts, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/cgi}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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code2life/operation-ts-model | code2life | 2023-12-11T15:03:34Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-11T15:03:34Z | ---
license: mit
---
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louisbrulenaudet/lpf | louisbrulenaudet | 2023-12-11T15:12:01Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"tax",
"llm",
"fiscal",
"lpf",
"Livre des procédures fiscales",
"doi:10.57967/hf/1439",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-11T15:11:08Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- tax
- llm
- fiscal
- lpf
- Livre des procédures fiscales
source_datasets:
- original
pretty_name: Livre des procédures fiscales (LPF)
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- n<1K
---
# Livre des procédures fiscales, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Livre des procédures fiscales, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/lpf}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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MaxYuki/Neil-Bowman-Dub | MaxYuki | 2023-12-11T15:23:10Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T15:21:01Z | ---
license: apache-2.0
---
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Renatanimareli/renatasantosss | Renatanimareli | 2023-12-11T15:32:16Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T15:31:43Z | ---
license: openrail
---
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kardosdrur/dfm_domain_classification | kardosdrur | 2023-12-11T16:06:33Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T15:42:57Z | ---
dataset_info:
features:
- name: content
dtype: string
- name: domain
dtype: string
splits:
- name: train
num_bytes: 40202954.4
num_examples: 80000
- name: test
num_bytes: 10050738.6
num_examples: 20000
download_size: 33465068
dataset_size: 50253693.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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open-llm-leaderboard/details_Deci__DeciLM-7B-instruct | open-llm-leaderboard | 2023-12-12T13:57:39Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T16:07:38Z | ---
pretty_name: Evaluation run of Deci/DeciLM-7B-instruct
dataset_summary: "Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B-instruct](https://huggingface.co/Deci/DeciLM-7B-instruct) 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\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Deci-early-access__DeciLM-7B-instruct-early_private\",\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-12-11T16:04:45.894054](https://huggingface.co/datasets/open-llm-leaderboard/details_Deci-early-access__DeciLM-7B-instruct-early_private/blob/main/results_2023-12-11T16-04-45.894054.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\": 0.6031249566837412,\n \"acc_stderr\": 0.033116595870832835,\n \"acc_norm\": 0.6063162588110805,\n \"acc_norm_stderr\": 0.03379377067263216,\n \"mc1\": 0.34761321909424725,\n \"mc1_stderr\": 0.016670769188897303,\n \"mc2\": 0.49753650846026637,\n \"mc2_stderr\": 0.015257351147769172\n },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.5665529010238908,\n \"acc_stderr\": 0.014481376224558902,\n \"acc_norm\": 0.6100682593856656,\n \"acc_norm_stderr\": 0.014252959848892896\n },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6278629755028878,\n \"acc_stderr\": 0.004823867761332466,\n \"acc_norm\": 0.8237402907787293,\n \"acc_norm_stderr\": 0.0038026223415290146\n },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.22,\n \"acc_stderr\": 0.0416333199893227,\n \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.0416333199893227\n },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5777777777777777,\n \"acc_stderr\": 0.042667634040995814,\n \"acc_norm\": 0.5777777777777777,\n \"acc_norm_stderr\": 0.042667634040995814\n },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.7039473684210527,\n \"acc_stderr\": 0.037150621549989056,\n \"acc_norm\": 0.7039473684210527,\n \"acc_norm_stderr\": 0.037150621549989056\n },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.6377358490566037,\n \"acc_stderr\": 0.0295822451283843,\n \"acc_norm\": 0.6377358490566037,\n \"acc_norm_stderr\": 0.0295822451283843\n },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.6875,\n \"acc_stderr\": 0.038760854559127644,\n \"acc_norm\": 0.6875,\n \"acc_norm_stderr\": 0.038760854559127644\n },\n \"harness|hendrycksTest-college_chemistry|5\": {\n \"acc\": 0.45,\n \"acc_stderr\": 0.04999999999999999,\n \"acc_norm\": 0.45,\n \"acc_norm_stderr\": 0.04999999999999999\n },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-college_mathematics|5\": {\n \"acc\": 0.39,\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\": 0.6127167630057804,\n \"acc_stderr\": 0.03714325906302065,\n \"acc_norm\": 0.6127167630057804,\n \"acc_norm_stderr\": 0.03714325906302065\n },\n \"harness|hendrycksTest-college_physics|5\": {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.048580835742663454,\n \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.048580835742663454\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\": 0.548936170212766,\n \"acc_stderr\": 0.032529096196131965,\n \"acc_norm\": 0.548936170212766,\n \"acc_norm_stderr\": 0.032529096196131965\n },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4473684210526316,\n \"acc_stderr\": 0.046774730044911984,\n \"acc_norm\": 0.4473684210526316,\n \"acc_norm_stderr\": 0.046774730044911984\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\": 0.4074074074074074,\n \"acc_stderr\": 0.025305906241590632,\n \"acc_norm\": 0.4074074074074074,\n \"acc_norm_stderr\": 0.025305906241590632\n },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.36507936507936506,\n \"acc_stderr\": 0.04306241259127153,\n \"acc_norm\": 0.36507936507936506,\n \"acc_norm_stderr\": 0.04306241259127153\n },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7290322580645161,\n \"acc_stderr\": 0.025284416114900156,\n \"acc_norm\": 0.7290322580645161,\n \"acc_norm_stderr\": 0.025284416114900156\n },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\": 0.4433497536945813,\n \"acc_stderr\": 0.03495334582162934,\n \"acc_norm\": 0.4433497536945813,\n \"acc_norm_stderr\": 0.03495334582162934\n },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252607,\n \"acc_norm\": 0.67,\n \"acc_norm_stderr\": 0.04725815626252607\n },\n \"harness|hendrycksTest-high_school_european_history|5\": {\n \"acc\": 0.7454545454545455,\n \"acc_stderr\": 0.03401506715249039,\n \"acc_norm\": 0.7454545454545455,\n \"acc_norm_stderr\": 0.03401506715249039\n },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\": 0.7121212121212122,\n \"acc_stderr\": 0.03225883512300992,\n \"acc_norm\": 0.7121212121212122,\n \"acc_norm_stderr\": 0.03225883512300992\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\": 0.6076923076923076,\n \"acc_stderr\": 0.02475600038213095,\n \"acc_norm\": 0.6076923076923076,\n \"acc_norm_stderr\": 0.02475600038213095\n },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"acc\": 0.37407407407407406,\n \"acc_stderr\": 0.02950286112895529,\n \"acc_norm\": 0.37407407407407406,\n \"acc_norm_stderr\": 0.02950286112895529\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \"acc\": 0.6260504201680672,\n \"acc_stderr\": 0.03142946637883708,\n \"acc_norm\": 0.6260504201680672,\n \"acc_norm_stderr\": 0.03142946637883708\n },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\": 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\n },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.7926605504587156,\n \"acc_stderr\": 0.01738141556360868,\n \"acc_norm\": 0.7926605504587156,\n \"acc_norm_stderr\": 0.01738141556360868\n },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\": 0.48148148148148145,\n \"acc_stderr\": 0.034076320938540516,\n \"acc_norm\": 0.48148148148148145,\n \"acc_norm_stderr\": 0.034076320938540516\n },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.7843137254901961,\n \"acc_stderr\": 0.028867431449849313,\n \"acc_norm\": 0.7843137254901961,\n \"acc_norm_stderr\": 0.028867431449849313\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\": 0.6816143497757847,\n \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness|hendrycksTest-human_sexuality|5\": {\n \"acc\": 0.6946564885496184,\n \"acc_stderr\": 0.040393149787245605,\n \"acc_norm\": 0.6946564885496184,\n \"acc_norm_stderr\": 0.040393149787245605\n },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\": 0.8016528925619835,\n \"acc_stderr\": 0.03640118271990946,\n \"acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.03640118271990946\n },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7129629629629629,\n \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.7129629629629629,\n \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\": {\n \"acc\": 0.7055214723926381,\n \"acc_stderr\": 0.03581165790474082,\n \"acc_norm\": 0.7055214723926381,\n \"acc_norm_stderr\": 0.03581165790474082\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\": 0.7281553398058253,\n \"acc_stderr\": 0.044052680241409216,\n \"acc_norm\": 0.7281553398058253,\n \"acc_norm_stderr\": 0.044052680241409216\n },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n \"acc_stderr\": 0.02190190511507333,\n \"acc_norm\": 0.8717948717948718,\n \"acc_norm_stderr\": 0.02190190511507333\n },\n \"harness|hendrycksTest-medical_genetics|5\": {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7931034482758621,\n \"acc_stderr\": 0.014485656041669176,\n \"acc_norm\": 0.7931034482758621,\n \"acc_norm_stderr\": 0.014485656041669176\n },\n \"harness|hendrycksTest-moral_disputes|5\": {\n \"acc\": 0.6705202312138728,\n \"acc_stderr\": 0.025305258131879713,\n \"acc_norm\": 0.6705202312138728,\n \"acc_norm_stderr\": 0.025305258131879713\n },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.33631284916201115,\n \"acc_stderr\": 0.015801003729145887,\n \"acc_norm\": 0.33631284916201115,\n \"acc_norm_stderr\": 0.015801003729145887\n },\n \"harness|hendrycksTest-nutrition|5\": {\n \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.02699254433929724,\n \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.02699254433929724\n },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6334405144694534,\n \"acc_stderr\": 0.027368078243971625,\n \"acc_norm\": 0.6334405144694534,\n \"acc_norm_stderr\": 0.027368078243971625\n },\n \"harness|hendrycksTest-prehistory|5\": {\n \"acc\": 0.6851851851851852,\n \"acc_stderr\": 0.02584224870090217,\n \"acc_norm\": 0.6851851851851852,\n \"acc_norm_stderr\": 0.02584224870090217\n },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\": 0.46099290780141844,\n \"acc_stderr\": 0.02973659252642444,\n \"acc_norm\": 0.46099290780141844,\n \"acc_norm_stderr\": 0.02973659252642444\n },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4335071707953064,\n \"acc_stderr\": 0.012656810383983969,\n \"acc_norm\": 0.4335071707953064,\n \"acc_norm_stderr\": 0.012656810383983969\n },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\": 0.5625,\n \"acc_stderr\": 0.030134614954403924,\n \"acc_norm\": 0.5625,\n \"acc_norm_stderr\": 0.030134614954403924\n },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\": 0.6127450980392157,\n \"acc_stderr\": 0.019706875804085627,\n \"acc_norm\": 0.6127450980392157,\n \"acc_norm_stderr\": 0.019706875804085627\n },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5909090909090909,\n \"acc_stderr\": 0.04709306978661895,\n \"acc_norm\": 0.5909090909090909,\n \"acc_norm_stderr\": 0.04709306978661895\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\": 0.8159203980099502,\n \"acc_stderr\": 0.027403859410786838,\n \"acc_norm\": 0.8159203980099502,\n \"acc_norm_stderr\": 0.027403859410786838\n },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\": 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.463855421686747,\n \"acc_stderr\": 0.03882310850890594,\n \"acc_norm\": 0.463855421686747,\n \"acc_norm_stderr\": 0.03882310850890594\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\": 0.34761321909424725,\n \"mc1_stderr\": 0.016670769188897303,\n \"mc2\": 0.49753650846026637,\n \"mc2_stderr\": 0.015257351147769172\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.7971586424625099,\n \"acc_stderr\": 0.011301439925936643\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.46019711902956784,\n \"acc_stderr\": 0.013728776714099363\n }\n}\n```"
repo_url: https://huggingface.co/Deci/DeciLM-7B-instruct
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- '**/details_harness|arc:challenge|25_2023-12-11T16-04-45.894054.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-11T16-04-45.894054.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- '**/details_harness|gsm8k|5_2023-12-11T16-04-45.894054.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-11T16-04-45.894054.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- '**/details_harness|hellaswag|10_2023-12-11T16-04-45.894054.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-11T16-04-45.894054.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
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**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-anatomy|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-astronomy|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-nutrition|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-philosophy|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-prehistory|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_law|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-public_relations|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-security_studies|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-sociology|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-virology|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-anatomy|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-astronomy|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_biology|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-college_physics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-computer_security|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-econometrics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-global_facts|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-international_law|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-management|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-marketing|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-nutrition|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-philosophy|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-prehistory|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_law|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T16-04-45.894054.parquet
- >-
**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-public_relations|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-security_studies|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-sociology|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T16-04-45.894054.parquet
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**/details_harness|hendrycksTest-world_religions|5_2023-12-11T16-04-45.894054.parquet
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- >-
**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
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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
data_files:
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- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
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- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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- config_name: harness_hendrycksTest_college_physics_5
data_files:
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- config_name: harness_hendrycksTest_computer_security_5
data_files:
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- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
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- config_name: harness_hendrycksTest_econometrics_5
data_files:
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- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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- config_name: harness_hendrycksTest_global_facts_5
data_files:
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- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
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- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
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- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
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- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
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- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
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- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
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- config_name: harness_hendrycksTest_human_aging_5
data_files:
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- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
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- config_name: harness_hendrycksTest_international_law_5
data_files:
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- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
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- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
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- config_name: harness_hendrycksTest_machine_learning_5
data_files:
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- config_name: harness_hendrycksTest_management_5
data_files:
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- config_name: harness_hendrycksTest_marketing_5
data_files:
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- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
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- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
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- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
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- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
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- config_name: harness_hendrycksTest_nutrition_5
data_files:
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- config_name: harness_hendrycksTest_philosophy_5
data_files:
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- config_name: harness_hendrycksTest_prehistory_5
data_files:
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- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
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- config_name: harness_hendrycksTest_professional_law_5
data_files:
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- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
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- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
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- config_name: harness_hendrycksTest_public_relations_5
data_files:
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- config_name: harness_hendrycksTest_security_studies_5
data_files:
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- config_name: harness_hendrycksTest_sociology_5
data_files:
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- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- >-
**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T16-04-45.894054.parquet
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- >-
**/details_harness|hendrycksTest-virology|5_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-virology|5_2023-12-11T16-04-45.894054.parquet
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
- >-
**/details_harness|hendrycksTest-world_religions|5_2023-12-11T16-04-45.894054.parquet
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T16-04-45.894054.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T16-04-45.894054.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- '**/details_harness|winogrande|5_2023-12-11T16-04-45.894054.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-11T16-04-45.894054.parquet'
- config_name: results
data_files:
- split: 2023_12_11T16_04_45.894054
path:
- results_2023-12-11T16-04-45.894054.parquet
- split: latest
path:
- results_2023-12-11T16-04-45.894054.parquet
---
# Dataset Card for Evaluation run of Deci/DeciLM-7B-instruct
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/Deci/DeciLM-7B-instruct
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [Deci/DeciLM-7B-instruct](https://huggingface.co/Deci/DeciLM-7B-instruct) 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_Deci__DeciLM-7B-instruct",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-11T16:04:45.894054](https://huggingface.co/datasets/open-llm-leaderboard/details_Deci__DeciLM-7B-instruct/blob/main/results_2023-12-11T16-04-45.894054.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
{
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"acc_stderr": 0.033116595870832835,
"acc_norm": 0.6063162588110805,
"acc_norm_stderr": 0.03379377067263216,
"mc1": 0.34761321909424725,
"mc1_stderr": 0.016670769188897303,
"mc2": 0.49753650846026637,
"mc2_stderr": 0.015257351147769172
},
"harness|arc:challenge|25": {
"acc": 0.5665529010238908,
"acc_stderr": 0.014481376224558902,
"acc_norm": 0.6100682593856656,
"acc_norm_stderr": 0.014252959848892896
},
"harness|hellaswag|10": {
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"acc_stderr": 0.004823867761332466,
"acc_norm": 0.8237402907787293,
"acc_norm_stderr": 0.0038026223415290146
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.22,
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"acc_norm": 0.22,
"acc_norm_stderr": 0.0416333199893227
},
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},
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},
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"acc_norm": 0.6377358490566037,
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},
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},
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},
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"harness|hendrycksTest-high_school_computer_science|5": {
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},
"harness|hendrycksTest-high_school_microeconomics|5": {
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"harness|hendrycksTest-high_school_psychology|5": {
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"harness|hendrycksTest-high_school_us_history|5": {
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"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": {
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"harness|hendrycksTest-international_law|5": {
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"harness|hendrycksTest-management|5": {
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"harness|hendrycksTest-marketing|5": {
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},
"harness|hendrycksTest-medical_genetics|5": {
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"harness|hendrycksTest-moral_scenarios|5": {
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},
"harness|hendrycksTest-nutrition|5": {
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"harness|hendrycksTest-prehistory|5": {
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"harness|hendrycksTest-security_studies|5": {
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"acc_norm_stderr": 0.02840125202902294
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"harness|hendrycksTest-sociology|5": {
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"harness|hendrycksTest-us_foreign_policy|5": {
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"harness|hendrycksTest-virology|5": {
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"harness|hendrycksTest-world_religions|5": {
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"acc_norm": 0.783625730994152,
"acc_norm_stderr": 0.031581495393387324
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"harness|truthfulqa:mc|0": {
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"mc2": 0.49753650846026637,
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},
"harness|winogrande|5": {
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"acc_stderr": 0.011301439925936643
},
"harness|gsm8k|5": {
"acc": 0.46019711902956784,
"acc_stderr": 0.013728776714099363
}
}
```
### 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] | [
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andreagurioli1995/human-ai_stylometry | andreagurioli1995 | 2023-12-14T17:17:50Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T16:51:00Z | ---
dataset_info:
features:
- name: task_url
dtype: string
- name: task_name
dtype: string
- name: task_description
dtype: string
- name: language_url
dtype: string
- name: language_name
dtype: string
- name: code
dtype: string
- name: target
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 3439112
num_examples: 1004
download_size: 1469223
dataset_size: 3439112
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "human-ai_stylometry"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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RahulRaman/counting-object-sd-dataset3-clean | RahulRaman | 2023-12-11T16:57:56Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T16:57:51Z | ---
dataset_info:
features:
- name: input_image
dtype: image
- name: edit_prompt
dtype: string
- name: edited_image
dtype: image
splits:
- name: train
num_bytes: 79691147.0
num_examples: 863
download_size: 10478726
dataset_size: 79691147.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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pequeno3d/zeus | pequeno3d | 2023-12-11T17:05:04Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T17:04:41Z | ---
license: openrail
---
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Pinhamusic/candicegomes3 | Pinhamusic | 2023-12-11T18:19:59Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T18:11:06Z | ---
license: openrail
---
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xwjiang2010/pile_dedupe_train_tokenized_chunked | xwjiang2010 | 2023-12-12T17:30:30Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T18:19:54Z | ---
dataset_info:
features:
- name: input_ids
sequence: int32
splits:
- name: train
num_bytes: 32776
num_examples: 2
download_size: 17726
dataset_size: 32776
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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fr-st/tullaluana | fr-st | 2023-12-11T18:29:10Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T18:29:10Z | ---
license: openrail
---
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RahulRaman/counting-object-sd-dataset3-clean2 | RahulRaman | 2023-12-11T18:32:03Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T18:32:00Z | ---
dataset_info:
features:
- name: input_image
dtype: image
- name: edit_prompt
dtype: string
- name: edited_image
dtype: image
splits:
- name: train
num_bytes: 9617511.0
num_examples: 92
download_size: 2628890
dataset_size: 9617511.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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DIAS123/JUNIOR | DIAS123 | 2023-12-11T18:40:09Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T18:39:44Z | ---
license: openrail
---
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dsafdfsge/gfdgdgd | dsafdfsge | 2023-12-11T18:47:27Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T18:46:21Z | ---
license: apache-2.0
---
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FelipeGuerra/Colombian_Spanish_Cyberbullying_Dataset_1 | FelipeGuerra | 2023-12-11T19:30:25Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-11T18:56:21Z | ---
license: mit
---
### Dataset Summary
This dataset consists of 3570 tweets, which were manually labeled as cyberbullying or not cyberbullying. A distinguishing feature of this dataset is that for a given word, there is an annotated tweet labeled as cyberbullying that contains that word, and another tweet labeled as not cyberbullying with the same word. This is made possible because the context in which the same word is used can vary, leading to tweets being classified differently.
For instance, tweets in the not cyberbullying category predominantly contain obscene words that, in their particular context, do not correspond with cyberbullying. An example is “Marica, se me olvidó ver el partido”. Additionally, the not cyberbullying category, to a lesser extent, includes tweets sourced from trends in the Colombian region. Twitter trends reflect the most popular topics and conversations in a given area at a specific time, essentially capturing what people are discussing and sharing online in that geographical locale.
Trend-based tweets were utilized for those instances where it was not feasible to obtain not cyberbullying tweets containing a specific offensive word or phrase, such as “ojala te violen”. Conversely, tweets labeled as cyberbullying might not always contain words or phrases that are deemed strong or obscene, like in the example “te voy a buscar”.
The distribution of cyberbullying tweets and non-cyberbullying tweets was the same. The keywords and phrases used in the creation of the dataset were selected based on the categories provided in the article Guidelines for the Fine-Grained Analysis of Cyberbullying authored by Cynthia Van Hee, Ben Verhoeven, Els Lefever, Guy De Pauw, Walter Daelemans, and Véronique Hoste. Four categories were included: insult, threat, curse, and defamation. The insult category involves the use of offensive words intended to verbally hurt another person, while threat aims to harm the victim's integrity. Curse includes words that wish harm or misfortune upon a person, and defamation seeks to damage the victim’s reputation. These categories were chosen to capture a broad representation of the forms in which cyberbullying can manifest. The tweets were labeled by an occupational therapist associated with the project. | [
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louisbrulenaudet/code-douanes | louisbrulenaudet | 2023-12-12T10:43:48Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"french law",
"droit français",
"Code des douanes",
"doi:10.57967/hf/1447",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-11T19:08:27Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- french law
- droit français
- Code des douanes
source_datasets:
- original
pretty_name: Code des douanes
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- 1K<n<10K
---
# Code des douanes, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Code des douanes, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-douanes}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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belacan/bwolleh | belacan | 2023-12-11T19:13:19Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-11T19:08:53Z | ---
license: apache-2.0
license_name: ganzerfilm
license_link: LICENSE
---
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ihaflix1/coringa | ihaflix1 | 2023-12-11T19:37:09Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T19:35:14Z | ---
license: openrail
---
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] |
FelipeGuerra/Colombian_Spanish_Cyberbullying_Dataset_2 | FelipeGuerra | 2023-12-12T18:50:37Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-11T19:39:35Z | ---
license: mit
---
### Dataset Summary
This dataset consists of 2566 tweets and maintains a balanced distribution between cyberbullying and not cyberbullying. For every keyword or phrase, there is an annotated tweet labeled as cyberbullying that contains that word or phrase.
The not cyberbullying category predominantly includes tweets that do not contain obscene words and are sourced from popular and varied discussions involving colombian users, reflecting a wide range of topics and conversations.
The distribution of cyberbullying tweets and non-cyberbullying tweets was the same. The keywords and phrases used in the creation of the dataset were selected based on the categories provided in the article Guidelines for the Fine-Grained Analysis of Cyberbullying authored by Cynthia Van Hee, Ben Verhoeven, Els Lefever, Guy De Pauw, Walter Daelemans, and Véronique Hoste. Four categories were included: insult, threat, curse, and defamation. The insult category involves the use of offensive words intended to verbally hurt another person, while threat aims to harm the victim's integrity. Curse includes words that wish harm or misfortune upon a person, and defamation seeks to damage the victim’s reputation. These categories were chosen to capture a broad representation of the forms in which cyberbullying can manifest. The tweets were labeled by an occupational therapist associated with the project. | [
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Vinnyyw/Arielvozes | Vinnyyw | 2023-12-11T19:58:25Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T19:57:36Z | ---
license: openrail
---
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mj96/subject_lionel_messi | mj96 | 2023-12-11T20:13:57Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T20:13:54Z | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 1136397.0
num_examples: 14
download_size: 1137829
dataset_size: 1136397.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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DenisVousin/VozPowerMan | DenisVousin | 2023-12-11T20:20:39Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-11T20:19:19Z | ---
license: mit
---
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chentong00/propositionizer-wiki-data | chentong00 | 2023-12-11T21:51:06Z | 0 | 0 | [
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"license:apache-2.0",
"region:us"
] | [
"text2text-generation"
] | 2023-12-11T20:37:47Z | ---
license: apache-2.0
task_categories:
- text2text-generation
size_categories:
- 10K<n<100K
---
## Dataset Summary
This is the training data of the model `Propositionizer-wiki`. We prompt GPT-4 to decompose a Wikipedia paragraph into a list of propositions.
We propose this training data to explore the concept of propositions as retrieval units. The propositions are defined as follows:
1. Each proposition should correspond to a distinct piece of meaning in the text, where the composition of all propositions would represent the semantics of the entire text.
2. A proposition should be *minimal*, i.e. it cannot be further split into separate propositions.
3. A proposition should be *contextualized and self-contained* ([Choi et al. 2021](https://aclanthology.org/2021.tacl-1.27/)). A proposition should include all the necessary context from the text (e.g. coreference) to interpret its meaning.
Check out more details in the paper.
## Dataset Structure
Here we provide details about the structure of the dataset.
* `sources` represents a Wikipedia paragraph. It is always in the format of "Title: {title}. Section: {section}. {content}". The title will not be empty, but the section can be empty.
* `targets` are a list of propositions in a JSON-formatted string.
Example:
```
{
"sources": "Title: Leaning Tower of Pisa. Section: . Prior to restoration work performed between 1990 and 2001, the tower leaned at an angle of 5.5 degrees, but the tower now leans at about 3.99 degrees. This means the top of the Leaning Tower of Pisa is displaced horizontally 3.9 meters (12 ft 10 in) from the center."
"targets": "[\"Prior to restoration work performed between 1990 and 2001, the Leaning Tower of Pisa leaned at an angle of 5.5 degrees.\", \"The Leaning Tower of Pisa now leans at about 3.99 degrees.\", \"The top of the Leaning Tower of Pisa is displaced horizontally 3.9 meters (12 ft 10 in) from the center.\"]"
}
```
## Citation
```
``` | [
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reza-alipour/seg-res-7 | reza-alipour | 2023-12-11T21:06:23Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:06:18Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 40474269.0
num_examples: 98
download_size: 40473021
dataset_size: 40474269.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Flavinhouaua2022/jorge | Flavinhouaua2022 | 2023-12-11T21:18:00Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T21:15:24Z | ---
license: openrail
---
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ainzOulgun/fsajd | ainzOulgun | 2023-12-11T22:27:42Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T21:41:19Z | ---
license: openrail
---
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reza-alipour/seg-res-3 | reza-alipour | 2023-12-11T21:56:30Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:56:25Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 81953066.0
num_examples: 200
download_size: 81949341
dataset_size: 81953066.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/seg-res-2 | reza-alipour | 2023-12-11T21:56:38Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:56:34Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 82387740.0
num_examples: 200
download_size: 82384271
dataset_size: 82387740.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/seg-res-5 | reza-alipour | 2023-12-11T21:57:03Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:56:57Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 81426333.0
num_examples: 200
download_size: 81422776
dataset_size: 81426333.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/seg-res-0 | reza-alipour | 2023-12-11T21:57:26Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:57:20Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 82675102.0
num_examples: 200
download_size: 82671459
dataset_size: 82675102.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/seg-res-1 | reza-alipour | 2023-12-11T21:59:24Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:59:12Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 82848006.0
num_examples: 200
download_size: 82844517
dataset_size: 82848006.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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reza-alipour/seg-res-4 | reza-alipour | 2023-12-11T22:00:08Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T21:59:54Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 83046357.0
num_examples: 200
download_size: 83042791
dataset_size: 83046357.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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dimitristzel/Diploma | dimitristzel | 2023-12-11T22:09:31Z | 0 | 0 | [
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:zero-shot-classification",
"size_categories:10K<n<100K",
"language:en",
"region:us"
] | [
"question-answering",
"summarization",
"zero-shot-classification"
] | 2023-12-11T22:00:53Z | ---
task_categories:
- question-answering
- summarization
- zero-shot-classification
language:
- en
size_categories:
- 10K<n<100K
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jaissonjpp/ETTh1 | jaissonjpp | 2023-12-11T22:10:07Z | 0 | 0 | [
"license:cc-by-4.0",
"region:us"
] | null | 2023-12-11T22:05:37Z | ---
license: cc-by-4.0
---
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reza-alipour/seg-res-6 | reza-alipour | 2023-12-11T22:08:01Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T22:07:48Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: mask
dtype: image
- name: caption
dtype: string
- name: generated_image
dtype: image
splits:
- name: train
num_bytes: 82828710.0
num_examples: 200
download_size: 82824185
dataset_size: 82828710.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Kaue123456/HomemQueFalaONomeDosEpisodiosDoAutoDaCompadecida | Kaue123456 | 2023-12-11T22:22:07Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T22:21:23Z | ---
license: openrail
---
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open-llm-leaderboard/details_v1olet__v1olet_marcoroni-go-bruins-merge-7B | open-llm-leaderboard | 2023-12-11T22:23:42Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T22:22:57Z | ---
pretty_name: Evaluation run of v1olet/v1olet_marcoroni-go-bruins-merge-7B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-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_v1olet__v1olet_marcoroni-go-bruins-merge-7B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-11T22:20:05.133817](https://huggingface.co/datasets/open-llm-leaderboard/details_v1olet__v1olet_marcoroni-go-bruins-merge-7B/blob/main/results_2023-12-11T22-20-05.133817.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\": 0.6562832889581685,\n\
\ \"acc_stderr\": 0.031992742713714516,\n \"acc_norm\": 0.6562130552581822,\n\
\ \"acc_norm_stderr\": 0.032653591602583326,\n \"mc1\": 0.44430844553243576,\n\
\ \"mc1_stderr\": 0.017394586250743173,\n \"mc2\": 0.6142182914346945,\n\
\ \"mc2_stderr\": 0.015342703381935975\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6689419795221843,\n \"acc_stderr\": 0.013752062419817837,\n\
\ \"acc_norm\": 0.7005119453924915,\n \"acc_norm_stderr\": 0.013385021637313577\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6898028281218881,\n\
\ \"acc_stderr\": 0.004616288245259755,\n \"acc_norm\": 0.8717386974706234,\n\
\ \"acc_norm_stderr\": 0.0033369715351311744\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6592592592592592,\n\
\ \"acc_stderr\": 0.04094376269996792,\n \"acc_norm\": 0.6592592592592592,\n\
\ \"acc_norm_stderr\": 0.04094376269996792\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\
\ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.67,\n\
\ \"acc_stderr\": 0.04725815626252609,\n \"acc_norm\": 0.67,\n \
\ \"acc_norm_stderr\": 0.04725815626252609\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\": 0.7638888888888888,\n\
\ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.7638888888888888,\n\
\ \"acc_norm_stderr\": 0.03551446610810826\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \
\ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\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\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6589595375722543,\n\
\ \"acc_stderr\": 0.036146654241808254,\n \"acc_norm\": 0.6589595375722543,\n\
\ \"acc_norm_stderr\": 0.036146654241808254\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287534,\n\
\ \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287534\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.76,\n \"acc_stderr\": 0.04292346959909282,\n \"acc_norm\": 0.76,\n\
\ \"acc_norm_stderr\": 0.04292346959909282\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.6,\n \"acc_stderr\": 0.03202563076101735,\n \
\ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.03202563076101735\n },\n\
\ \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.49122807017543857,\n\
\ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.49122807017543857,\n\
\ \"acc_norm_stderr\": 0.04702880432049615\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\"\
: 0.4365079365079365,\n \"acc_stderr\": 0.0255428468174005,\n \"acc_norm\"\
: 0.4365079365079365,\n \"acc_norm_stderr\": 0.0255428468174005\n },\n\
\ \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5,\n \
\ \"acc_stderr\": 0.04472135954999579,\n \"acc_norm\": 0.5,\n \"\
acc_norm_stderr\": 0.04472135954999579\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\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\"\
: 0.49261083743842365,\n \"acc_stderr\": 0.035176035403610084,\n \"\
acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.035176035403610084\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\
: 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7878787878787878,\n \"acc_stderr\": 0.031922715695483,\n\
\ \"acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.031922715695483\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\
acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.02150024957603348,\n\
\ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.02150024957603348\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6794871794871795,\n \"acc_stderr\": 0.02366129639396428,\n \
\ \"acc_norm\": 0.6794871794871795,\n \"acc_norm_stderr\": 0.02366129639396428\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.34444444444444444,\n \"acc_stderr\": 0.02897264888484427,\n \
\ \"acc_norm\": 0.34444444444444444,\n \"acc_norm_stderr\": 0.02897264888484427\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.680672268907563,\n \"acc_stderr\": 0.030283995525884396,\n \
\ \"acc_norm\": 0.680672268907563,\n \"acc_norm_stderr\": 0.030283995525884396\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\
acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8495412844036697,\n \"acc_stderr\": 0.015328563932669235,\n \"\
acc_norm\": 0.8495412844036697,\n \"acc_norm_stderr\": 0.015328563932669235\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5138888888888888,\n \"acc_stderr\": 0.03408655867977749,\n \"\
acc_norm\": 0.5138888888888888,\n \"acc_norm_stderr\": 0.03408655867977749\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8333333333333334,\n \"acc_stderr\": 0.026156867523931045,\n \"\
acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.026156867523931045\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944863,\n \
\ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944863\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\
\ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\
\ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8015267175572519,\n \"acc_stderr\": 0.034981493854624714,\n\
\ \"acc_norm\": 0.8015267175572519,\n \"acc_norm_stderr\": 0.034981493854624714\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7768595041322314,\n \"acc_stderr\": 0.03800754475228732,\n \"\
acc_norm\": 0.7768595041322314,\n \"acc_norm_stderr\": 0.03800754475228732\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\
\ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\
\ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.754601226993865,\n \"acc_stderr\": 0.03380939813943354,\n\
\ \"acc_norm\": 0.754601226993865,\n \"acc_norm_stderr\": 0.03380939813943354\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\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\
\ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\
\ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\
\ \"acc_norm_stderr\": 0.02093019318517933\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8314176245210728,\n\
\ \"acc_stderr\": 0.013387895731543604,\n \"acc_norm\": 0.8314176245210728,\n\
\ \"acc_norm_stderr\": 0.013387895731543604\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7369942196531792,\n \"acc_stderr\": 0.023703099525258172,\n\
\ \"acc_norm\": 0.7369942196531792,\n \"acc_norm_stderr\": 0.023703099525258172\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.41899441340782123,\n\
\ \"acc_stderr\": 0.016501579306861677,\n \"acc_norm\": 0.41899441340782123,\n\
\ \"acc_norm_stderr\": 0.016501579306861677\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7287581699346405,\n \"acc_stderr\": 0.02545775669666788,\n\
\ \"acc_norm\": 0.7287581699346405,\n \"acc_norm_stderr\": 0.02545775669666788\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7170418006430869,\n\
\ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\
\ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\
: 0.48936170212765956,\n \"acc_stderr\": 0.02982074719142248,\n \"\
acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.02982074719142248\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4706649282920469,\n\
\ \"acc_stderr\": 0.012748238397365549,\n \"acc_norm\": 0.4706649282920469,\n\
\ \"acc_norm_stderr\": 0.012748238397365549\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6801470588235294,\n \"acc_stderr\": 0.02833295951403121,\n\
\ \"acc_norm\": 0.6801470588235294,\n \"acc_norm_stderr\": 0.02833295951403121\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6830065359477124,\n \"acc_stderr\": 0.018824219512706207,\n \
\ \"acc_norm\": 0.6830065359477124,\n \"acc_norm_stderr\": 0.018824219512706207\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\
\ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\
\ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.726530612244898,\n \"acc_stderr\": 0.028535560337128445,\n\
\ \"acc_norm\": 0.726530612244898,\n \"acc_norm_stderr\": 0.028535560337128445\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8557213930348259,\n\
\ \"acc_stderr\": 0.024845753212306053,\n \"acc_norm\": 0.8557213930348259,\n\
\ \"acc_norm_stderr\": 0.024845753212306053\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.86,\n \"acc_stderr\": 0.0348735088019777,\n \
\ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.0348735088019777\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5421686746987951,\n\
\ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.5421686746987951,\n\
\ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\
\ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.44430844553243576,\n\
\ \"mc1_stderr\": 0.017394586250743173,\n \"mc2\": 0.6142182914346945,\n\
\ \"mc2_stderr\": 0.015342703381935975\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8145224940805051,\n \"acc_stderr\": 0.010923965303140505\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7156937073540561,\n \
\ \"acc_stderr\": 0.012425078188395978\n }\n}\n```"
repo_url: https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|arc:challenge|25_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|gsm8k|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hellaswag|10_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-20-05.133817.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T22-20-05.133817.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- '**/details_harness|winogrande|5_2023-12-11T22-20-05.133817.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-11T22-20-05.133817.parquet'
- config_name: results
data_files:
- split: 2023_12_11T22_20_05.133817
path:
- results_2023-12-11T22-20-05.133817.parquet
- split: latest
path:
- results_2023-12-11T22-20-05.133817.parquet
---
# Dataset Card for Evaluation run of v1olet/v1olet_marcoroni-go-bruins-merge-7B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-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_v1olet__v1olet_marcoroni-go-bruins-merge-7B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-11T22:20:05.133817](https://huggingface.co/datasets/open-llm-leaderboard/details_v1olet__v1olet_marcoroni-go-bruins-merge-7B/blob/main/results_2023-12-11T22-20-05.133817.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": 0.6562832889581685,
"acc_stderr": 0.031992742713714516,
"acc_norm": 0.6562130552581822,
"acc_norm_stderr": 0.032653591602583326,
"mc1": 0.44430844553243576,
"mc1_stderr": 0.017394586250743173,
"mc2": 0.6142182914346945,
"mc2_stderr": 0.015342703381935975
},
"harness|arc:challenge|25": {
"acc": 0.6689419795221843,
"acc_stderr": 0.013752062419817837,
"acc_norm": 0.7005119453924915,
"acc_norm_stderr": 0.013385021637313577
},
"harness|hellaswag|10": {
"acc": 0.6898028281218881,
"acc_stderr": 0.004616288245259755,
"acc_norm": 0.8717386974706234,
"acc_norm_stderr": 0.0033369715351311744
},
"harness|hendrycksTest-abstract_algebra|5": {
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```
## Dataset Details
### Dataset Description
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[More Information Needed] | [
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open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp | open-llm-leaderboard | 2023-12-11T22:24:50Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T22:24:06Z | ---
pretty_name: Evaluation run of Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp](https://huggingface.co/Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-11T22:21:10.174265](https://huggingface.co/datasets/open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp/blob/main/results_2023-12-11T22-21-10.174265.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\": 0.6497954997030103,\n\
\ \"acc_stderr\": 0.03218797050617161,\n \"acc_norm\": 0.6495568440119162,\n\
\ \"acc_norm_stderr\": 0.032855200604616566,\n \"mc1\": 0.47613219094247244,\n\
\ \"mc1_stderr\": 0.017483547156961574,\n \"mc2\": 0.6270127709181503,\n\
\ \"mc2_stderr\": 0.015065515223932825\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6621160409556314,\n \"acc_stderr\": 0.013822047922283512,\n\
\ \"acc_norm\": 0.6877133105802048,\n \"acc_norm_stderr\": 0.013542598541688067\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6793467436765585,\n\
\ \"acc_stderr\": 0.004657738398900938,\n \"acc_norm\": 0.8654650468034256,\n\
\ \"acc_norm_stderr\": 0.003405288007233203\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\": 0.6296296296296297,\n\
\ \"acc_stderr\": 0.041716541613545426,\n \"acc_norm\": 0.6296296296296297,\n\
\ \"acc_norm_stderr\": 0.041716541613545426\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\
\ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\
\ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \
\ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7056603773584905,\n \"acc_stderr\": 0.028049186315695248,\n\
\ \"acc_norm\": 0.7056603773584905,\n \"acc_norm_stderr\": 0.028049186315695248\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7569444444444444,\n\
\ \"acc_stderr\": 0.03586879280080341,\n \"acc_norm\": 0.7569444444444444,\n\
\ \"acc_norm_stderr\": 0.03586879280080341\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.53,\n \"acc_stderr\": 0.050161355804659205,\n \
\ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.050161355804659205\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\
acc\": 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\"\
: 0.58,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6763005780346821,\n\
\ \"acc_stderr\": 0.035676037996391706,\n \"acc_norm\": 0.6763005780346821,\n\
\ \"acc_norm_stderr\": 0.035676037996391706\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.49019607843137253,\n \"acc_stderr\": 0.04974229460422817,\n\
\ \"acc_norm\": 0.49019607843137253,\n \"acc_norm_stderr\": 0.04974229460422817\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\": 0.5914893617021276,\n \"acc_stderr\": 0.032134180267015755,\n\
\ \"acc_norm\": 0.5914893617021276,\n \"acc_norm_stderr\": 0.032134180267015755\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\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\
\ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.42592592592592593,\n \"acc_stderr\": 0.025467149045469557,\n \"\
acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.025467149045469557\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4444444444444444,\n\
\ \"acc_stderr\": 0.044444444444444495,\n \"acc_norm\": 0.4444444444444444,\n\
\ \"acc_norm_stderr\": 0.044444444444444495\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.7709677419354839,\n \"acc_stderr\": 0.023904914311782655,\n \"\
acc_norm\": 0.7709677419354839,\n \"acc_norm_stderr\": 0.023904914311782655\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.49261083743842365,\n \"acc_stderr\": 0.035176035403610084,\n \"\
acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.035176035403610084\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\": 0.7818181818181819,\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\"\
: 0.797979797979798,\n \"acc_stderr\": 0.028606204289229872,\n \"\
acc_norm\": 0.797979797979798,\n \"acc_norm_stderr\": 0.028606204289229872\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8860103626943006,\n \"acc_stderr\": 0.022935144053919443,\n\
\ \"acc_norm\": 0.8860103626943006,\n \"acc_norm_stderr\": 0.022935144053919443\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.023946724741563976,\n\
\ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.023946724741563976\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.3333333333333333,\n \"acc_stderr\": 0.028742040903948485,\n \
\ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.028742040903948485\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\"\
: 0.304635761589404,\n \"acc_stderr\": 0.03757949922943343,\n \"acc_norm\"\
: 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943343\n },\n\
\ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8458715596330275,\n\
\ \"acc_stderr\": 0.015480826865374307,\n \"acc_norm\": 0.8458715596330275,\n\
\ \"acc_norm_stderr\": 0.015480826865374307\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\
: {\n \"acc\": 0.5231481481481481,\n \"acc_stderr\": 0.03406315360711507,\n\
\ \"acc_norm\": 0.5231481481481481,\n \"acc_norm_stderr\": 0.03406315360711507\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.7990196078431373,\n \"acc_stderr\": 0.028125972265654373,\n \"\
acc_norm\": 0.7990196078431373,\n \"acc_norm_stderr\": 0.028125972265654373\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7974683544303798,\n \"acc_stderr\": 0.026160568246601443,\n \
\ \"acc_norm\": 0.7974683544303798,\n \"acc_norm_stderr\": 0.026160568246601443\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6771300448430493,\n\
\ \"acc_stderr\": 0.031381476375754995,\n \"acc_norm\": 0.6771300448430493,\n\
\ \"acc_norm_stderr\": 0.031381476375754995\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7633587786259542,\n \"acc_stderr\": 0.03727673575596913,\n\
\ \"acc_norm\": 0.7633587786259542,\n \"acc_norm_stderr\": 0.03727673575596913\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8016528925619835,\n \"acc_stderr\": 0.03640118271990946,\n \"\
acc_norm\": 0.8016528925619835,\n \"acc_norm_stderr\": 0.03640118271990946\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\": 0.7730061349693251,\n \"acc_stderr\": 0.03291099578615769,\n\
\ \"acc_norm\": 0.7730061349693251,\n \"acc_norm_stderr\": 0.03291099578615769\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\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\
\ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\
\ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\
\ \"acc_norm_stderr\": 0.02093019318517933\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\": 0.8275862068965517,\n\
\ \"acc_stderr\": 0.013507943909371802,\n \"acc_norm\": 0.8275862068965517,\n\
\ \"acc_norm_stderr\": 0.013507943909371802\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7427745664739884,\n \"acc_stderr\": 0.023532925431044287,\n\
\ \"acc_norm\": 0.7427745664739884,\n \"acc_norm_stderr\": 0.023532925431044287\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.42681564245810055,\n\
\ \"acc_stderr\": 0.016542401954631917,\n \"acc_norm\": 0.42681564245810055,\n\
\ \"acc_norm_stderr\": 0.016542401954631917\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\
\ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7009646302250804,\n\
\ \"acc_stderr\": 0.02600330111788514,\n \"acc_norm\": 0.7009646302250804,\n\
\ \"acc_norm_stderr\": 0.02600330111788514\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7314814814814815,\n \"acc_stderr\": 0.024659685185967287,\n\
\ \"acc_norm\": 0.7314814814814815,\n \"acc_norm_stderr\": 0.024659685185967287\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.46808510638297873,\n \"acc_stderr\": 0.029766675075873866,\n \
\ \"acc_norm\": 0.46808510638297873,\n \"acc_norm_stderr\": 0.029766675075873866\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.45371577574967403,\n\
\ \"acc_stderr\": 0.012715404841277738,\n \"acc_norm\": 0.45371577574967403,\n\
\ \"acc_norm_stderr\": 0.012715404841277738\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\": 0.6633986928104575,\n \"acc_stderr\": 0.019117213911495144,\n \
\ \"acc_norm\": 0.6633986928104575,\n \"acc_norm_stderr\": 0.019117213911495144\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6818181818181818,\n\
\ \"acc_stderr\": 0.04461272175910509,\n \"acc_norm\": 0.6818181818181818,\n\
\ \"acc_norm_stderr\": 0.04461272175910509\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.763265306122449,\n \"acc_stderr\": 0.02721283588407316,\n\
\ \"acc_norm\": 0.763265306122449,\n \"acc_norm_stderr\": 0.02721283588407316\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8507462686567164,\n\
\ \"acc_stderr\": 0.025196929874827075,\n \"acc_norm\": 0.8507462686567164,\n\
\ \"acc_norm_stderr\": 0.025196929874827075\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\": 0.5180722891566265,\n\
\ \"acc_stderr\": 0.03889951252827216,\n \"acc_norm\": 0.5180722891566265,\n\
\ \"acc_norm_stderr\": 0.03889951252827216\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640038,\n\
\ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640038\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.47613219094247244,\n\
\ \"mc1_stderr\": 0.017483547156961574,\n \"mc2\": 0.6270127709181503,\n\
\ \"mc2_stderr\": 0.015065515223932825\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8074191002367798,\n \"acc_stderr\": 0.011082538847491906\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7179681576952237,\n \
\ \"acc_stderr\": 0.012394926584335688\n }\n}\n```"
repo_url: https://huggingface.co/Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|arc:challenge|25_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|gsm8k|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hellaswag|10_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-21-10.174265.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-11T22-21-10.174265.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- '**/details_harness|winogrande|5_2023-12-11T22-21-10.174265.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-11T22-21-10.174265.parquet'
- config_name: results
data_files:
- split: 2023_12_11T22_21_10.174265
path:
- results_2023-12-11T22-21-10.174265.parquet
- split: latest
path:
- results_2023-12-11T22-21-10.174265.parquet
---
# Dataset Card for Evaluation run of Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp](https://huggingface.co/Toten5/Marcoroni-v3-neural-chat-v3-3-Slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-11T22:21:10.174265](https://huggingface.co/datasets/open-llm-leaderboard/details_Toten5__Marcoroni-v3-neural-chat-v3-3-Slerp/blob/main/results_2023-12-11T22-21-10.174265.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": 0.6497954997030103,
"acc_stderr": 0.03218797050617161,
"acc_norm": 0.6495568440119162,
"acc_norm_stderr": 0.032855200604616566,
"mc1": 0.47613219094247244,
"mc1_stderr": 0.017483547156961574,
"mc2": 0.6270127709181503,
"mc2_stderr": 0.015065515223932825
},
"harness|arc:challenge|25": {
"acc": 0.6621160409556314,
"acc_stderr": 0.013822047922283512,
"acc_norm": 0.6877133105802048,
"acc_norm_stderr": 0.013542598541688067
},
"harness|hellaswag|10": {
"acc": 0.6793467436765585,
"acc_stderr": 0.004657738398900938,
"acc_norm": 0.8654650468034256,
"acc_norm_stderr": 0.003405288007233203
},
"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": 0.6296296296296297,
"acc_stderr": 0.041716541613545426,
"acc_norm": 0.6296296296296297,
"acc_norm_stderr": 0.041716541613545426
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.6907894736842105,
"acc_stderr": 0.037610708698674805,
"acc_norm": 0.6907894736842105,
"acc_norm_stderr": 0.037610708698674805
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.63,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.63,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7056603773584905,
"acc_stderr": 0.028049186315695248,
"acc_norm": 0.7056603773584905,
"acc_norm_stderr": 0.028049186315695248
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7569444444444444,
"acc_stderr": 0.03586879280080341,
"acc_norm": 0.7569444444444444,
"acc_norm_stderr": 0.03586879280080341
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.53,
"acc_stderr": 0.050161355804659205,
"acc_norm": 0.53,
"acc_norm_stderr": 0.050161355804659205
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.58,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.58,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.33,
"acc_stderr": 0.047258156262526045,
"acc_norm": 0.33,
"acc_norm_stderr": 0.047258156262526045
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6763005780346821,
"acc_stderr": 0.035676037996391706,
"acc_norm": 0.6763005780346821,
"acc_norm_stderr": 0.035676037996391706
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.49019607843137253,
"acc_stderr": 0.04974229460422817,
"acc_norm": 0.49019607843137253,
"acc_norm_stderr": 0.04974229460422817
},
"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": 0.5914893617021276,
"acc_stderr": 0.032134180267015755,
"acc_norm": 0.5914893617021276,
"acc_norm_stderr": 0.032134180267015755
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.5,
"acc_stderr": 0.047036043419179864,
"acc_norm": 0.5,
"acc_norm_stderr": 0.047036043419179864
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5379310344827586,
"acc_stderr": 0.04154659671707548,
"acc_norm": 0.5379310344827586,
"acc_norm_stderr": 0.04154659671707548
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.42592592592592593,
"acc_stderr": 0.025467149045469557,
"acc_norm": 0.42592592592592593,
"acc_norm_stderr": 0.025467149045469557
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.4444444444444444,
"acc_stderr": 0.044444444444444495,
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.044444444444444495
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.35,
"acc_stderr": 0.047937248544110196,
"acc_norm": 0.35,
"acc_norm_stderr": 0.047937248544110196
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7709677419354839,
"acc_stderr": 0.023904914311782655,
"acc_norm": 0.7709677419354839,
"acc_norm_stderr": 0.023904914311782655
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.49261083743842365,
"acc_stderr": 0.035176035403610084,
"acc_norm": 0.49261083743842365,
"acc_norm_stderr": 0.035176035403610084
},
"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": 0.7818181818181819,
"acc_stderr": 0.03225078108306289,
"acc_norm": 0.7818181818181819,
"acc_norm_stderr": 0.03225078108306289
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.797979797979798,
"acc_stderr": 0.028606204289229872,
"acc_norm": 0.797979797979798,
"acc_norm_stderr": 0.028606204289229872
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.8860103626943006,
"acc_stderr": 0.022935144053919443,
"acc_norm": 0.8860103626943006,
"acc_norm_stderr": 0.022935144053919443
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6641025641025641,
"acc_stderr": 0.023946724741563976,
"acc_norm": 0.6641025641025641,
"acc_norm_stderr": 0.023946724741563976
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.3333333333333333,
"acc_stderr": 0.028742040903948485,
"acc_norm": 0.3333333333333333,
"acc_norm_stderr": 0.028742040903948485
},
"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": 0.304635761589404,
"acc_stderr": 0.03757949922943343,
"acc_norm": 0.304635761589404,
"acc_norm_stderr": 0.03757949922943343
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8458715596330275,
"acc_stderr": 0.015480826865374307,
"acc_norm": 0.8458715596330275,
"acc_norm_stderr": 0.015480826865374307
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5231481481481481,
"acc_stderr": 0.03406315360711507,
"acc_norm": 0.5231481481481481,
"acc_norm_stderr": 0.03406315360711507
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.7990196078431373,
"acc_stderr": 0.028125972265654373,
"acc_norm": 0.7990196078431373,
"acc_norm_stderr": 0.028125972265654373
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7974683544303798,
"acc_stderr": 0.026160568246601443,
"acc_norm": 0.7974683544303798,
"acc_norm_stderr": 0.026160568246601443
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6771300448430493,
"acc_stderr": 0.031381476375754995,
"acc_norm": 0.6771300448430493,
"acc_norm_stderr": 0.031381476375754995
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.7633587786259542,
"acc_stderr": 0.03727673575596913,
"acc_norm": 0.7633587786259542,
"acc_norm_stderr": 0.03727673575596913
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.8016528925619835,
"acc_stderr": 0.03640118271990946,
"acc_norm": 0.8016528925619835,
"acc_norm_stderr": 0.03640118271990946
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7685185185185185,
"acc_stderr": 0.04077494709252626,
"acc_norm": 0.7685185185185185,
"acc_norm_stderr": 0.04077494709252626
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7730061349693251,
"acc_stderr": 0.03291099578615769,
"acc_norm": 0.7730061349693251,
"acc_norm_stderr": 0.03291099578615769
},
"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": 0.7766990291262136,
"acc_stderr": 0.04123553189891431,
"acc_norm": 0.7766990291262136,
"acc_norm_stderr": 0.04123553189891431
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8846153846153846,
"acc_stderr": 0.02093019318517933,
"acc_norm": 0.8846153846153846,
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```
## Dataset Details
### Dataset Description
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[More Information Needed] | [
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kanishka/counterfactual_babylm_aann_all_det_anan | kanishka | 2023-12-13T01:24:55Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T22:28:21Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 581871592
num_examples: 11632617
- name: validation
num_bytes: 56120230
num_examples: 1026747
download_size: 0
dataset_size: 637991822
---
# Dataset Card for "counterfactual_babylm_aann_all_det_anan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Simaosantos/Cremoso | Simaosantos | 2023-12-11T22:29:44Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-11T22:28:44Z | ---
license: openrail
---
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kanishka/counterfactual_babylm_aann_all_det_naan | kanishka | 2023-12-13T01:24:57Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T22:28:58Z | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 581871758
num_examples: 11632617
- name: validation
num_bytes: 56120230
num_examples: 1026747
download_size: 0
dataset_size: 637991988
---
# Dataset Card for "counterfactual_babylm_aann_all_det_naan"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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anthony-wss/librispeech_asr-audiodec_encodec_24k | anthony-wss | 2023-12-12T00:25:07Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T23:05:24Z | ---
configs:
- config_name: default
data_files:
- split: train.clean.360
path: data/train.clean.360-*
- split: train.other.500
path: data/train.other.500-*
dataset_info:
features:
- name: text
dtype: string
- name: id
dtype: string
- name: unit
sequence:
sequence: int64
splits:
- name: train.clean.360
num_bytes: 1070603220
num_examples: 104014
- name: train.other.500
num_bytes: 1462474737
num_examples: 148688
download_size: 406727746
dataset_size: 2533077957
---
# Dataset Card for "librispeech_asr-audiodec_encodec_24k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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venkat-srinivasan-nexusflow/multiapi_prototype_CVECPE_Only_dec11 | venkat-srinivasan-nexusflow | 2023-12-11T23:29:25Z | 0 | 0 | [
"region:us"
] | null | 2023-12-11T23:29:24Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: prediction
dtype: string
- name: ground_truth
dtype: string
- name: correctness
dtype: int64
splits:
- name: standard
num_bytes: 23976
num_examples: 78
download_size: 13073
dataset_size: 23976
configs:
- config_name: default
data_files:
- split: standard
path: data/standard-*
---
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System36/dylan_beta | System36 | 2023-12-11T23:34:07Z | 0 | 0 | [
"license:cc-by-nc-sa-2.0",
"region:us"
] | null | 2023-12-11T23:32:07Z | ---
license: cc-by-nc-sa-2.0
---
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louisbrulenaudet/code-securite-sociale | louisbrulenaudet | 2023-12-12T10:42:47Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"french law",
"droit français",
"Code de la sécurité sociale",
"doi:10.57967/hf/1445",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-12T00:15:15Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- french law
- droit français
- Code de la sécurité sociale
source_datasets:
- original
pretty_name: Code de la sécurité sociale
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- 1K<n<10K
---
# Code de la sécurité sociale, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Code de la sécurité sociale, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-securite-sociale}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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venkat-srinivasan-nexusflow/multiapi_prototype_VT_dec11 | venkat-srinivasan-nexusflow | 2023-12-12T00:16:54Z | 0 | 1 | [
"region:us"
] | null | 2023-12-12T00:16:53Z | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: prediction
dtype: string
- name: ground_truth
dtype: string
- name: correctness
dtype: int64
splits:
- name: standard
num_bytes: 55371
num_examples: 151
download_size: 21433
dataset_size: 55371
configs:
- config_name: default
data_files:
- split: standard
path: data/standard-*
---
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atmallen/quirky_popqa_pythia-410m | atmallen | 2023-12-12T06:54:18Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T00:17:57Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: choices
sequence: string
- name: label
dtype: int64
- name: popularity
dtype: int64
- name: difficulty
dtype: float64
- name: statement
dtype: string
- name: character
dtype: string
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: bob_log_odds
dtype: float64
splits:
- name: train
num_bytes: 7653912
num_examples: 49068
- name: validation
num_bytes: 624668
num_examples: 4000
- name: test
num_bytes: 623972
num_examples: 4000
download_size: 2401317
dataset_size: 8902552
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
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Snowyzoom/edu1 | Snowyzoom | 2023-12-12T00:19:14Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T00:18:21Z | ---
license: openrail
---
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567-labs/wikipedia-embedding-bge-base-en-v1.5-sample | 567-labs | 2023-12-12T00:39:38Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T00:25:31Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: embedding
sequence: float64
splits:
- name: train
num_bytes: 191214046
num_examples: 28404
download_size: 190908742
dataset_size: 191214046
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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breno30/KarlosWonney | breno30 | 2023-12-12T00:35:47Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T00:35:24Z | ---
license: openrail
---
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567-labs/wikipedia-embedding-bge-small-en-v1.5-sample | 567-labs | 2023-12-17T03:25:15Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T00:44:30Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: embedding
sequence: float64
splits:
- name: train
num_bytes: 1015245725
num_examples: 277027
download_size: 1014183442
dataset_size: 1015245725
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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Raphael04/eduardo | Raphael04 | 2023-12-12T00:59:46Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T00:59:16Z | ---
license: openrail
---
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atmallen/quirky_popqa_pythia-410m_alice_easy | atmallen | 2023-12-12T06:54:20Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T01:12:52Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: choices
sequence: string
- name: label
dtype: int64
- name: popularity
dtype: int64
- name: difficulty
dtype: float64
- name: statement
dtype: string
- name: character
dtype: string
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: bob_log_odds
dtype: float64
splits:
- name: train
num_bytes: 956505.0212765958
num_examples: 6132
- name: validation
num_bytes: 72149.154
num_examples: 462
- name: test
num_bytes: 76436.57
num_examples: 490
download_size: 402157
dataset_size: 1105090.7452765957
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
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atmallen/quirky_popqa_pythia-410m_alice_hard | atmallen | 2023-12-12T06:54:21Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T01:12:54Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: choices
sequence: string
- name: label
dtype: int64
- name: popularity
dtype: int64
- name: difficulty
dtype: float64
- name: statement
dtype: string
- name: character
dtype: string
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: bob_log_odds
dtype: float64
splits:
- name: train
num_bytes: 956816.9929078014
num_examples: 6134
- name: validation
num_bytes: 81519.174
num_examples: 522
- name: test
num_bytes: 77372.528
num_examples: 496
download_size: 396583
dataset_size: 1115708.6949078015
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
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atmallen/quirky_popqa_pythia-410m_alice | atmallen | 2023-12-12T06:54:23Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T01:12:57Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: choices
sequence: string
- name: label
dtype: int64
- name: popularity
dtype: int64
- name: difficulty
dtype: float64
- name: statement
dtype: string
- name: character
dtype: string
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: bob_log_odds
dtype: float64
splits:
- name: train
num_bytes: 3826956.0
num_examples: 24534
- name: validation
num_bytes: 312334.0
num_examples: 2000
- name: test
num_bytes: 311986.0
num_examples: 2000
download_size: 1551397
dataset_size: 4451276.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
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Simaosantos/Cremosinho | Simaosantos | 2023-12-12T01:15:28Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T01:14:04Z | ---
license: openrail
---
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oegbo/mini-platypus | oegbo | 2023-12-12T01:14:51Z | 0 | 1 | [
"region:us"
] | null | 2023-12-12T01:14:50Z | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 4186564
num_examples: 1000
download_size: 2245925
dataset_size: 4186564
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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louisbrulenaudet/code-sport | louisbrulenaudet | 2023-12-12T10:41:37Z | 0 | 0 | [
"task_categories:text-generation",
"task_categories:table-question-answering",
"task_categories:summarization",
"task_categories:conversational",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fr",
"license:apache-2.0",
"finetuning",
"legal",
"french law",
"droit français",
"Code du sport",
"doi:10.57967/hf/1443",
"region:us"
] | [
"text-generation",
"table-question-answering",
"summarization",
"conversational"
] | 2023-12-12T01:17:27Z | ---
license: apache-2.0
language:
- fr
multilinguality:
- monolingual
tags:
- finetuning
- legal
- french law
- droit français
- Code du sport
source_datasets:
- original
pretty_name: Code du sport
task_categories:
- text-generation
- table-question-answering
- summarization
- conversational
size_categories:
- 1K<n<10K
---
# Code du sport, non-instruct (11-12-2023)
This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach.
Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks.
Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways:
- Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions.
- Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs.
- Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more.
- Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs.
- Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text.
## Dataset generation
This JSON file is a list of dictionaries, each dictionary contains the following fields:
- `instruction`: `string`, presenting the instruction linked to the element.
- `input`: `string`, signifying the input details for the element.
- `output`: `string`, indicating the output information for the element.
We used the following list of instructions for generating the dataset:
```python
instructions = [
"Compose l'intégralité de l'article sous forme écrite.",
"Écris la totalité du contenu de l'article.",
"Formule la totalité du texte présent dans l'article.",
"Produis l'intégralité de l'article en écriture.",
"Développe l'article dans son ensemble par écrit.",
"Génère l'ensemble du texte contenu dans l'article.",
"Formule le contenu intégral de l'article en entier.",
"Rédige la totalité du texte de l'article en entier.",
"Compose l'intégralité du contenu textuel de l'article.",
"Rédige l'ensemble du texte qui constitue l'article.",
"Formule l'article entier dans son contenu écrit.",
"Composez l'intégralité de l'article sous forme écrite.",
"Écrivez la totalité du contenu de l'article.",
"Formulez la totalité du texte présent dans l'article.",
"Développez l'article dans son ensemble par écrit.",
"Générez l'ensemble du texte contenu dans l'article.",
"Formulez le contenu intégral de l'article en entier.",
"Rédigez la totalité du texte de l'article en entier.",
"Composez l'intégralité du contenu textuel de l'article.",
"Écrivez l'article dans son intégralité en termes de texte.",
"Rédigez l'ensemble du texte qui constitue l'article.",
"Formulez l'article entier dans son contenu écrit.",
"Composer l'intégralité de l'article sous forme écrite.",
"Écrire la totalité du contenu de l'article.",
"Formuler la totalité du texte présent dans l'article.",
"Produire l'intégralité de l'article en écriture.",
"Développer l'article dans son ensemble par écrit.",
"Générer l'ensemble du texte contenu dans l'article.",
"Formuler le contenu intégral de l'article en entier.",
"Rédiger la totalité du texte de l'article en entier.",
"Composer l'intégralité du contenu textuel de l'article.",
"Rédiger l'ensemble du texte qui constitue l'article.",
"Formuler l'article entier dans son contenu écrit.",
"Quelles sont les dispositions de l'article ?",
"Quelles dispositions sont incluses dans l'article ?",
"Quelles sont les dispositions énoncées dans l'article ?",
"Quel est le texte intégral de l'article ?",
"Quelle est la lettre de l'article ?"
]
```
## Citing this project
If you use this code in your research, please use the following BibTeX entry.
```BibTeX
@misc{louisbrulenaudet2023,
author = {Louis Brulé Naudet},
title = {Code du sport, non-instruct (11-12-2023)},
howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-sport}},
year = {2023}
}
```
## Feedback
If you have any feedback, please reach out at [[email protected]](mailto:[email protected]). | [
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LoonyZX/Roxanne | LoonyZX | 2023-12-12T01:46:51Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T01:44:47Z | ---
license: openrail
---
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Liareizz/manugavassivoice | Liareizz | 2023-12-12T02:20:15Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T02:19:21Z | ---
license: openrail
---
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OpenChatDev/new-codeprompts | OpenChatDev | 2023-12-12T02:24:40Z | 0 | 1 | [
"region:us"
] | null | 2023-12-12T02:24:21Z | ---
dataset_info:
features:
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 116885434
num_examples: 125623
download_size: 53998853
dataset_size: 116885434
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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open-llm-leaderboard/details_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T | open-llm-leaderboard | 2023-12-12T02:56:44Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T02:56:04Z | ---
pretty_name: Evaluation run of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T)\
\ 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_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-12T02:53:47.167196](https://huggingface.co/datasets/open-llm-leaderboard/details_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T/blob/main/results_2023-12-12T02-53-47.167196.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\": 0.2675448542417715,\n\
\ \"acc_stderr\": 0.03118011664128985,\n \"acc_norm\": 0.2690761116467705,\n\
\ \"acc_norm_stderr\": 0.03195175927273723,\n \"mc1\": 0.20930232558139536,\n\
\ \"mc1_stderr\": 0.014241219434785828,\n \"mc2\": 0.3678523017186956,\n\
\ \"mc2_stderr\": 0.013764237138063459\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.31143344709897613,\n \"acc_stderr\": 0.013532472099850942,\n\
\ \"acc_norm\": 0.33532423208191126,\n \"acc_norm_stderr\": 0.013796182947785562\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4458275243975304,\n\
\ \"acc_stderr\": 0.004960408362133243,\n \"acc_norm\": 0.5938060147381,\n\
\ \"acc_norm_stderr\": 0.00490117891790085\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.26666666666666666,\n\
\ \"acc_stderr\": 0.03820169914517905,\n \"acc_norm\": 0.26666666666666666,\n\
\ \"acc_norm_stderr\": 0.03820169914517905\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.1513157894736842,\n \"acc_stderr\": 0.029162631596843975,\n\
\ \"acc_norm\": 0.1513157894736842,\n \"acc_norm_stderr\": 0.029162631596843975\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.26,\n\
\ \"acc_stderr\": 0.0440844002276808,\n \"acc_norm\": 0.26,\n \
\ \"acc_norm_stderr\": 0.0440844002276808\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.2641509433962264,\n \"acc_stderr\": 0.02713429162874171,\n\
\ \"acc_norm\": 0.2641509433962264,\n \"acc_norm_stderr\": 0.02713429162874171\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2222222222222222,\n\
\ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.2222222222222222,\n\
\ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542127,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542127\n \
\ },\n \"harness|hendrycksTest-college_computer_science|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-college_mathematics|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.23699421965317918,\n\
\ \"acc_stderr\": 0.03242414757483098,\n \"acc_norm\": 0.23699421965317918,\n\
\ \"acc_norm_stderr\": 0.03242414757483098\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237656,\n\
\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237656\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.23,\n \"acc_stderr\": 0.042295258468165065,\n \"acc_norm\": 0.23,\n\
\ \"acc_norm_stderr\": 0.042295258468165065\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.2936170212765957,\n \"acc_stderr\": 0.029771642712491227,\n\
\ \"acc_norm\": 0.2936170212765957,\n \"acc_norm_stderr\": 0.029771642712491227\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2543859649122807,\n\
\ \"acc_stderr\": 0.04096985139843672,\n \"acc_norm\": 0.2543859649122807,\n\
\ \"acc_norm_stderr\": 0.04096985139843672\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135303,\n\
\ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135303\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.2777777777777778,\n \"acc_stderr\": 0.023068188848261114,\n \"\
acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.023068188848261114\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2222222222222222,\n\
\ \"acc_stderr\": 0.037184890068181146,\n \"acc_norm\": 0.2222222222222222,\n\
\ \"acc_norm_stderr\": 0.037184890068181146\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\": 0.2161290322580645,\n\
\ \"acc_stderr\": 0.02341529343356852,\n \"acc_norm\": 0.2161290322580645,\n\
\ \"acc_norm_stderr\": 0.02341529343356852\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.2512315270935961,\n \"acc_stderr\": 0.030516530732694433,\n\
\ \"acc_norm\": 0.2512315270935961,\n \"acc_norm_stderr\": 0.030516530732694433\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \"acc_norm\"\
: 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.2727272727272727,\n \"acc_stderr\": 0.03477691162163659,\n\
\ \"acc_norm\": 0.2727272727272727,\n \"acc_norm_stderr\": 0.03477691162163659\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.2222222222222222,\n \"acc_stderr\": 0.02962022787479049,\n \"\
acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02962022787479049\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.23834196891191708,\n \"acc_stderr\": 0.03074890536390988,\n\
\ \"acc_norm\": 0.23834196891191708,\n \"acc_norm_stderr\": 0.03074890536390988\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.28205128205128205,\n \"acc_stderr\": 0.0228158130988966,\n \
\ \"acc_norm\": 0.28205128205128205,\n \"acc_norm_stderr\": 0.0228158130988966\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.24074074074074073,\n \"acc_stderr\": 0.026067159222275815,\n \
\ \"acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.026067159222275815\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\"\
: 0.23841059602649006,\n \"acc_stderr\": 0.03479185572599661,\n \"\
acc_norm\": 0.23841059602649006,\n \"acc_norm_stderr\": 0.03479185572599661\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.23669724770642203,\n \"acc_stderr\": 0.01822407811729908,\n \"\
acc_norm\": 0.23669724770642203,\n \"acc_norm_stderr\": 0.01822407811729908\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\": 0.29411764705882354,\n\
\ \"acc_stderr\": 0.03198001660115071,\n \"acc_norm\": 0.29411764705882354,\n\
\ \"acc_norm_stderr\": 0.03198001660115071\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\
: {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\
\ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.37668161434977576,\n\
\ \"acc_stderr\": 0.032521134899291884,\n \"acc_norm\": 0.37668161434977576,\n\
\ \"acc_norm_stderr\": 0.032521134899291884\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.22900763358778625,\n \"acc_stderr\": 0.036853466317118506,\n\
\ \"acc_norm\": 0.22900763358778625,\n \"acc_norm_stderr\": 0.036853466317118506\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.24793388429752067,\n \"acc_stderr\": 0.03941897526516303,\n \"\
acc_norm\": 0.24793388429752067,\n \"acc_norm_stderr\": 0.03941897526516303\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.28703703703703703,\n\
\ \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.28703703703703703,\n\
\ \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.3006134969325153,\n \"acc_stderr\": 0.03602511318806771,\n\
\ \"acc_norm\": 0.3006134969325153,\n \"acc_norm_stderr\": 0.03602511318806771\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\
\ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\
\ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.2621359223300971,\n \"acc_stderr\": 0.04354631077260597,\n\
\ \"acc_norm\": 0.2621359223300971,\n \"acc_norm_stderr\": 0.04354631077260597\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2606837606837607,\n\
\ \"acc_stderr\": 0.028760348956523414,\n \"acc_norm\": 0.2606837606837607,\n\
\ \"acc_norm_stderr\": 0.028760348956523414\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.2835249042145594,\n\
\ \"acc_stderr\": 0.016117318166832283,\n \"acc_norm\": 0.2835249042145594,\n\
\ \"acc_norm_stderr\": 0.016117318166832283\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.21676300578034682,\n \"acc_stderr\": 0.022183477668412853,\n\
\ \"acc_norm\": 0.21676300578034682,\n \"acc_norm_stderr\": 0.022183477668412853\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\": 0.238562091503268,\n \"acc_stderr\": 0.02440439492808787,\n\
\ \"acc_norm\": 0.238562091503268,\n \"acc_norm_stderr\": 0.02440439492808787\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.3215434083601286,\n\
\ \"acc_stderr\": 0.026527724079528872,\n \"acc_norm\": 0.3215434083601286,\n\
\ \"acc_norm_stderr\": 0.026527724079528872\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.2716049382716049,\n \"acc_stderr\": 0.02474862449053737,\n\
\ \"acc_norm\": 0.2716049382716049,\n \"acc_norm_stderr\": 0.02474862449053737\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.21631205673758866,\n \"acc_stderr\": 0.024561720560562796,\n \
\ \"acc_norm\": 0.21631205673758866,\n \"acc_norm_stderr\": 0.024561720560562796\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.23533246414602346,\n\
\ \"acc_stderr\": 0.010834432543912234,\n \"acc_norm\": 0.23533246414602346,\n\
\ \"acc_norm_stderr\": 0.010834432543912234\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.3639705882352941,\n \"acc_stderr\": 0.029227192460032025,\n\
\ \"acc_norm\": 0.3639705882352941,\n \"acc_norm_stderr\": 0.029227192460032025\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.25326797385620914,\n \"acc_stderr\": 0.01759348689536683,\n \
\ \"acc_norm\": 0.25326797385620914,\n \"acc_norm_stderr\": 0.01759348689536683\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.2909090909090909,\n\
\ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.2909090909090909,\n\
\ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.15510204081632653,\n \"acc_stderr\": 0.0231747988612186,\n\
\ \"acc_norm\": 0.15510204081632653,\n \"acc_norm_stderr\": 0.0231747988612186\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.23880597014925373,\n\
\ \"acc_stderr\": 0.030147775935409224,\n \"acc_norm\": 0.23880597014925373,\n\
\ \"acc_norm_stderr\": 0.030147775935409224\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \
\ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.3192771084337349,\n\
\ \"acc_stderr\": 0.03629335329947861,\n \"acc_norm\": 0.3192771084337349,\n\
\ \"acc_norm_stderr\": 0.03629335329947861\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.2046783625730994,\n \"acc_stderr\": 0.03094445977853321,\n\
\ \"acc_norm\": 0.2046783625730994,\n \"acc_norm_stderr\": 0.03094445977853321\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.20930232558139536,\n\
\ \"mc1_stderr\": 0.014241219434785828,\n \"mc2\": 0.3678523017186956,\n\
\ \"mc2_stderr\": 0.013764237138063459\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6022099447513812,\n \"acc_stderr\": 0.013755743513749029\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.014404852160727824,\n \
\ \"acc_stderr\": 0.0032820559171369574\n }\n}\n```"
repo_url: https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|arc:challenge|25_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|gsm8k|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hellaswag|10_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T02-53-47.167196.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T02-53-47.167196.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- '**/details_harness|winogrande|5_2023-12-12T02-53-47.167196.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-12T02-53-47.167196.parquet'
- config_name: results
data_files:
- split: 2023_12_12T02_53_47.167196
path:
- results_2023-12-12T02-53-47.167196.parquet
- split: latest
path:
- results_2023-12-12T02-53-47.167196.parquet
---
# Dataset Card for Evaluation run of TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T) 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_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-12T02:53:47.167196](https://huggingface.co/datasets/open-llm-leaderboard/details_TinyLlama__TinyLlama-1.1B-intermediate-step-1195k-token-2.5T/blob/main/results_2023-12-12T02-53-47.167196.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
{
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},
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}
}
```
## 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] | [
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taesiri/video-game-question-answering-mixtral-8x7b-instruct-v0-1 | taesiri | 2023-12-12T22:28:45Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T02:57:42Z | ---
dataset_info:
features:
- name: id
dtype: string
- name: image
dtype: string
- name: conversations
dtype: string
- name: model
dtype: string
splits:
- name: train
num_bytes: 43411441
num_examples: 74111
download_size: 14462964
dataset_size: 43411441
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
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dronemeout/scans | dronemeout | 2023-12-12T03:04:36Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-12T03:03:42Z | ---
license: mit
---
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dincc04/dataset | dincc04 | 2023-12-12T03:15:47Z | 0 | 0 | [
"license:mit",
"region:us"
] | null | 2023-12-12T03:15:47Z | ---
license: mit
---
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heegyu/CoT-collection-ko | heegyu | 2023-12-12T03:20:48Z | 0 | 0 | [
"license:cc-by-4.0",
"region:us"
] | null | 2023-12-12T03:16:34Z | ---
license: cc-by-4.0
---
- original dataset: [korean data from kaist-ai/Multilingual-CoT-Collection](https://huggingface.co/datasets/kaist-ai/Multilingual-CoT-Collection) | [
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kanxue/alfworld_sft_path | kanxue | 2023-12-17T07:14:39Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-12T03:18:48Z | ---
license: apache-2.0
---
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BitTranslate/chatgpt-prompts-Swedish | BitTranslate | 2023-12-12T03:22:37Z | 0 | 0 | [
"license:cc0-1.0",
"ChatGPT",
"region:us"
] | null | 2023-12-12T03:20:03Z | ---
license: cc0-1.0
tags:
- ChatGPT
--- | [
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collabora/whisper-hindi-preprocessed | collabora | 2023-12-12T07:11:47Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T03:27:33Z | ---
dataset_info:
features:
- name: input_features
sequence:
sequence: float32
- name: input_length
dtype: float64
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 668819734185.926
num_examples: 694964
- name: test
num_bytes: 2093443544.0
num_examples: 2179
download_size: 337918400583
dataset_size: 670913177729.926
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
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Lask8/gradio-lipsync-wav2lip | Lask8 | 2023-12-12T03:50:04Z | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | null | 2023-12-12T03:28:46Z | ---
title: Gradio Lipsync Wav2lip
emoji: 👄
colorFrom: indigo
colorTo: blue
sdk: gradio
python_version: 3.8
sdk_version: 3.40.1
suggested_hardware: "t4-medium"
app_file: app.py
pinned: false
license: apache-2.0
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | [
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ainzOulgun/fsajdd | ainzOulgun | 2023-12-12T03:39:39Z | 0 | 0 | [
"license:openrail",
"region:us"
] | null | 2023-12-12T03:39:11Z | ---
license: openrail
---
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open-llm-leaderboard/details_janhq__supermario-slerp | open-llm-leaderboard | 2023-12-12T03:40:50Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T03:40:07Z | ---
pretty_name: Evaluation run of janhq/supermario-slerp
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [janhq/supermario-slerp](https://huggingface.co/janhq/supermario-slerp) on the\
\ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_janhq__supermario-slerp\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-12T03:37:12.561456](https://huggingface.co/datasets/open-llm-leaderboard/details_janhq__supermario-slerp/blob/main/results_2023-12-12T03-37-12.561456.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\": 0.6537706437546362,\n\
\ \"acc_stderr\": 0.031995288620737625,\n \"acc_norm\": 0.6536617491214738,\n\
\ \"acc_norm_stderr\": 0.03265751997212851,\n \"mc1\": 0.43818849449204406,\n\
\ \"mc1_stderr\": 0.017369236164404438,\n \"mc2\": 0.6010546669403226,\n\
\ \"mc2_stderr\": 0.015217019912801435\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6578498293515358,\n \"acc_stderr\": 0.013864152159177278,\n\
\ \"acc_norm\": 0.689419795221843,\n \"acc_norm_stderr\": 0.013522292098053069\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6773551085441147,\n\
\ \"acc_stderr\": 0.004665327309399185,\n \"acc_norm\": 0.8657637920732921,\n\
\ \"acc_norm_stderr\": 0.0034020920763237457\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\
\ \"acc_stderr\": 0.041539484047423976,\n \"acc_norm\": 0.6370370370370371,\n\
\ \"acc_norm_stderr\": 0.041539484047423976\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.7236842105263158,\n \"acc_stderr\": 0.03639057569952929,\n\
\ \"acc_norm\": 0.7236842105263158,\n \"acc_norm_stderr\": 0.03639057569952929\n\
\ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\
: {\n \"acc\": 0.720754716981132,\n \"acc_stderr\": 0.027611163402399715,\n\
\ \"acc_norm\": 0.720754716981132,\n \"acc_norm_stderr\": 0.027611163402399715\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\
\ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\
\ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \
\ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.53,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.53,\n\
\ \"acc_norm_stderr\": 0.050161355804659205\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\": 0.6705202312138728,\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\": 0.39215686274509803,\n \"acc_stderr\": 0.048580835742663454,\n\
\ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.048580835742663454\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\": 0.5957446808510638,\n \"acc_stderr\": 0.03208115750788684,\n\
\ \"acc_norm\": 0.5957446808510638,\n \"acc_norm_stderr\": 0.03208115750788684\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\
\ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\
\ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\
\ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.42592592592592593,\n \"acc_stderr\": 0.02546714904546955,\n \"\
acc_norm\": 0.42592592592592593,\n \"acc_norm_stderr\": 0.02546714904546955\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\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
: 0.7741935483870968,\n \"acc_stderr\": 0.023785577884181015,\n \"\
acc_norm\": 0.7741935483870968,\n \"acc_norm_stderr\": 0.023785577884181015\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\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\
: 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.03256866661681102,\n\
\ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.03256866661681102\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586818,\n \"\
acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586818\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.021500249576033456,\n\
\ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.021500249576033456\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.023946724741563976,\n\
\ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.023946724741563976\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.35185185185185186,\n \"acc_stderr\": 0.029116617606083004,\n \
\ \"acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.029116617606083004\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.02983796238829194,\n \
\ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.02983796238829194\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.33112582781456956,\n \"acc_stderr\": 0.038425817186598696,\n \"\
acc_norm\": 0.33112582781456956,\n \"acc_norm_stderr\": 0.038425817186598696\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8568807339449541,\n \"acc_stderr\": 0.015014462497168589,\n \"\
acc_norm\": 0.8568807339449541,\n \"acc_norm_stderr\": 0.015014462497168589\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5416666666666666,\n \"acc_stderr\": 0.03398110890294636,\n \"\
acc_norm\": 0.5416666666666666,\n \"acc_norm_stderr\": 0.03398110890294636\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078966,\n \"\
acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078966\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944867,\n \
\ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944867\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\": 0.03547771004159465,\n\
\ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159465\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098824,\n \"\
acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098824\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\
\ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\
\ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\
\ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\
\ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\
\ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\
\ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\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\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8339719029374202,\n\
\ \"acc_stderr\": 0.013306478243066302,\n \"acc_norm\": 0.8339719029374202,\n\
\ \"acc_norm_stderr\": 0.013306478243066302\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7427745664739884,\n \"acc_stderr\": 0.02353292543104429,\n\
\ \"acc_norm\": 0.7427745664739884,\n \"acc_norm_stderr\": 0.02353292543104429\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.39553072625698327,\n\
\ \"acc_stderr\": 0.016353415410075775,\n \"acc_norm\": 0.39553072625698327,\n\
\ \"acc_norm_stderr\": 0.016353415410075775\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7287581699346405,\n \"acc_stderr\": 0.025457756696667885,\n\
\ \"acc_norm\": 0.7287581699346405,\n \"acc_norm_stderr\": 0.025457756696667885\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\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \
\ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\
: 0.48936170212765956,\n \"acc_stderr\": 0.02982074719142248,\n \"\
acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.02982074719142248\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.47131681877444587,\n\
\ \"acc_stderr\": 0.012749206007657474,\n \"acc_norm\": 0.47131681877444587,\n\
\ \"acc_norm_stderr\": 0.012749206007657474\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6838235294117647,\n \"acc_stderr\": 0.028245687391462927,\n\
\ \"acc_norm\": 0.6838235294117647,\n \"acc_norm_stderr\": 0.028245687391462927\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6830065359477124,\n \"acc_stderr\": 0.018824219512706207,\n \
\ \"acc_norm\": 0.6830065359477124,\n \"acc_norm_stderr\": 0.018824219512706207\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6818181818181818,\n\
\ \"acc_stderr\": 0.044612721759105085,\n \"acc_norm\": 0.6818181818181818,\n\
\ \"acc_norm_stderr\": 0.044612721759105085\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.726530612244898,\n \"acc_stderr\": 0.028535560337128445,\n\
\ \"acc_norm\": 0.726530612244898,\n \"acc_norm_stderr\": 0.028535560337128445\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\
\ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\
\ \"acc_norm_stderr\": 0.02587064676616913\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\": 0.5421686746987951,\n\
\ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.5421686746987951,\n\
\ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8128654970760234,\n \"acc_stderr\": 0.02991312723236804,\n\
\ \"acc_norm\": 0.8128654970760234,\n \"acc_norm_stderr\": 0.02991312723236804\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.43818849449204406,\n\
\ \"mc1_stderr\": 0.017369236164404438,\n \"mc2\": 0.6010546669403226,\n\
\ \"mc2_stderr\": 0.015217019912801435\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8129439621152328,\n \"acc_stderr\": 0.01095971643524291\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7210007581501138,\n \
\ \"acc_stderr\": 0.012354115779970306\n }\n}\n```"
repo_url: https://huggingface.co/janhq/supermario-slerp
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-12.561456.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-12.561456.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-12.561456.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-12.561456.parquet'
- config_name: results
data_files:
- split: 2023_12_12T03_37_12.561456
path:
- results_2023-12-12T03-37-12.561456.parquet
- split: latest
path:
- results_2023-12-12T03-37-12.561456.parquet
---
# Dataset Card for Evaluation run of janhq/supermario-slerp
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [janhq/supermario-slerp](https://huggingface.co/janhq/supermario-slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_janhq__supermario-slerp",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-12T03:37:12.561456](https://huggingface.co/datasets/open-llm-leaderboard/details_janhq__supermario-slerp/blob/main/results_2023-12-12T03-37-12.561456.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": 0.6537706437546362,
"acc_stderr": 0.031995288620737625,
"acc_norm": 0.6536617491214738,
"acc_norm_stderr": 0.03265751997212851,
"mc1": 0.43818849449204406,
"mc1_stderr": 0.017369236164404438,
"mc2": 0.6010546669403226,
"mc2_stderr": 0.015217019912801435
},
"harness|arc:challenge|25": {
"acc": 0.6578498293515358,
"acc_stderr": 0.013864152159177278,
"acc_norm": 0.689419795221843,
"acc_norm_stderr": 0.013522292098053069
},
"harness|hellaswag|10": {
"acc": 0.6773551085441147,
"acc_stderr": 0.004665327309399185,
"acc_norm": 0.8657637920732921,
"acc_norm_stderr": 0.0034020920763237457
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.32,
"acc_stderr": 0.04688261722621504,
"acc_norm": 0.32,
"acc_norm_stderr": 0.04688261722621504
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6370370370370371,
"acc_stderr": 0.041539484047423976,
"acc_norm": 0.6370370370370371,
"acc_norm_stderr": 0.041539484047423976
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.7236842105263158,
"acc_stderr": 0.03639057569952929,
"acc_norm": 0.7236842105263158,
"acc_norm_stderr": 0.03639057569952929
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.64,
"acc_stderr": 0.04824181513244218,
"acc_norm": 0.64,
"acc_norm_stderr": 0.04824181513244218
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.720754716981132,
"acc_stderr": 0.027611163402399715,
"acc_norm": 0.720754716981132,
"acc_norm_stderr": 0.027611163402399715
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7708333333333334,
"acc_stderr": 0.03514697467862388,
"acc_norm": 0.7708333333333334,
"acc_norm_stderr": 0.03514697467862388
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.46,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.46,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.53,
"acc_stderr": 0.050161355804659205,
"acc_norm": 0.53,
"acc_norm_stderr": 0.050161355804659205
},
"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": 0.6705202312138728,
"acc_stderr": 0.03583901754736412,
"acc_norm": 0.6705202312138728,
"acc_norm_stderr": 0.03583901754736412
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.39215686274509803,
"acc_stderr": 0.048580835742663454,
"acc_norm": 0.39215686274509803,
"acc_norm_stderr": 0.048580835742663454
},
"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": 0.5957446808510638,
"acc_stderr": 0.03208115750788684,
"acc_norm": 0.5957446808510638,
"acc_norm_stderr": 0.03208115750788684
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.4824561403508772,
"acc_stderr": 0.04700708033551038,
"acc_norm": 0.4824561403508772,
"acc_norm_stderr": 0.04700708033551038
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5448275862068965,
"acc_stderr": 0.04149886942192117,
"acc_norm": 0.5448275862068965,
"acc_norm_stderr": 0.04149886942192117
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.42592592592592593,
"acc_stderr": 0.02546714904546955,
"acc_norm": 0.42592592592592593,
"acc_norm_stderr": 0.02546714904546955
},
"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": 0.36,
"acc_stderr": 0.048241815132442176,
"acc_norm": 0.36,
"acc_norm_stderr": 0.048241815132442176
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7741935483870968,
"acc_stderr": 0.023785577884181015,
"acc_norm": 0.7741935483870968,
"acc_norm_stderr": 0.023785577884181015
},
"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": 0.7,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.7,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7757575757575758,
"acc_stderr": 0.03256866661681102,
"acc_norm": 0.7757575757575758,
"acc_norm_stderr": 0.03256866661681102
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7878787878787878,
"acc_stderr": 0.029126522834586818,
"acc_norm": 0.7878787878787878,
"acc_norm_stderr": 0.029126522834586818
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9015544041450777,
"acc_stderr": 0.021500249576033456,
"acc_norm": 0.9015544041450777,
"acc_norm_stderr": 0.021500249576033456
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6641025641025641,
"acc_stderr": 0.023946724741563976,
"acc_norm": 0.6641025641025641,
"acc_norm_stderr": 0.023946724741563976
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.35185185185185186,
"acc_stderr": 0.029116617606083004,
"acc_norm": 0.35185185185185186,
"acc_norm_stderr": 0.029116617606083004
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6974789915966386,
"acc_stderr": 0.02983796238829194,
"acc_norm": 0.6974789915966386,
"acc_norm_stderr": 0.02983796238829194
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.33112582781456956,
"acc_stderr": 0.038425817186598696,
"acc_norm": 0.33112582781456956,
"acc_norm_stderr": 0.038425817186598696
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.8568807339449541,
"acc_stderr": 0.015014462497168589,
"acc_norm": 0.8568807339449541,
"acc_norm_stderr": 0.015014462497168589
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.5416666666666666,
"acc_stderr": 0.03398110890294636,
"acc_norm": 0.5416666666666666,
"acc_norm_stderr": 0.03398110890294636
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8235294117647058,
"acc_stderr": 0.026756401538078966,
"acc_norm": 0.8235294117647058,
"acc_norm_stderr": 0.026756401538078966
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.8143459915611815,
"acc_stderr": 0.025310495376944867,
"acc_norm": 0.8143459915611815,
"acc_norm_stderr": 0.025310495376944867
},
"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": 0.03547771004159465,
"acc_norm": 0.7938931297709924,
"acc_norm_stderr": 0.03547771004159465
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.7933884297520661,
"acc_stderr": 0.03695980128098824,
"acc_norm": 0.7933884297520661,
"acc_norm_stderr": 0.03695980128098824
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.8055555555555556,
"acc_stderr": 0.038260763248848646,
"acc_norm": 0.8055555555555556,
"acc_norm_stderr": 0.038260763248848646
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7668711656441718,
"acc_stderr": 0.0332201579577674,
"acc_norm": 0.7668711656441718,
"acc_norm_stderr": 0.0332201579577674
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.44642857142857145,
"acc_stderr": 0.04718471485219588,
"acc_norm": 0.44642857142857145,
"acc_norm_stderr": 0.04718471485219588
},
"harness|hendrycksTest-management|5": {
"acc": 0.7864077669902912,
"acc_stderr": 0.040580420156460344,
"acc_norm": 0.7864077669902912,
"acc_norm_stderr": 0.040580420156460344
},
"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": 0.75,
"acc_stderr": 0.04351941398892446,
"acc_norm": 0.75,
"acc_norm_stderr": 0.04351941398892446
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8339719029374202,
"acc_stderr": 0.013306478243066302,
"acc_norm": 0.8339719029374202,
"acc_norm_stderr": 0.013306478243066302
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7427745664739884,
"acc_stderr": 0.02353292543104429,
"acc_norm": 0.7427745664739884,
"acc_norm_stderr": 0.02353292543104429
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.39553072625698327,
"acc_stderr": 0.016353415410075775,
"acc_norm": 0.39553072625698327,
"acc_norm_stderr": 0.016353415410075775
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.7287581699346405,
"acc_stderr": 0.025457756696667885,
"acc_norm": 0.7287581699346405,
"acc_norm_stderr": 0.025457756696667885
},
"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": 0.75,
"acc_stderr": 0.02409347123262133,
"acc_norm": 0.75,
"acc_norm_stderr": 0.02409347123262133
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.48936170212765956,
"acc_stderr": 0.02982074719142248,
"acc_norm": 0.48936170212765956,
"acc_norm_stderr": 0.02982074719142248
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.47131681877444587,
"acc_stderr": 0.012749206007657474,
"acc_norm": 0.47131681877444587,
"acc_norm_stderr": 0.012749206007657474
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6838235294117647,
"acc_stderr": 0.028245687391462927,
"acc_norm": 0.6838235294117647,
"acc_norm_stderr": 0.028245687391462927
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6830065359477124,
"acc_stderr": 0.018824219512706207,
"acc_norm": 0.6830065359477124,
"acc_norm_stderr": 0.018824219512706207
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6818181818181818,
"acc_stderr": 0.044612721759105085,
"acc_norm": 0.6818181818181818,
"acc_norm_stderr": 0.044612721759105085
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.726530612244898,
"acc_stderr": 0.028535560337128445,
"acc_norm": 0.726530612244898,
"acc_norm_stderr": 0.028535560337128445
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.8407960199004975,
"acc_stderr": 0.02587064676616913,
"acc_norm": 0.8407960199004975,
"acc_norm_stderr": 0.02587064676616913
},
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},
"harness|gsm8k|5": {
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"acc_stderr": 0.012354115779970306
}
}
```
## Dataset Details
### Dataset Description
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[More Information Needed] | [
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open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2 | open-llm-leaderboard | 2023-12-12T03:41:32Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T03:40:42Z | ---
pretty_name: Evaluation run of mistralai/Mistral-7B-Instruct-v0.2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-12T03:37:50.599841](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2/blob/main/results_2023-12-12T03-37-50.599841.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\": 0.6077550413417533,\n\
\ \"acc_stderr\": 0.03310328786623656,\n \"acc_norm\": 0.6122661125091963,\n\
\ \"acc_norm_stderr\": 0.03377303167526721,\n \"mc1\": 0.5275397796817626,\n\
\ \"mc1_stderr\": 0.01747693019071219,\n \"mc2\": 0.6825629969752945,\n\
\ \"mc2_stderr\": 0.015176655501749976\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.5895904436860068,\n \"acc_stderr\": 0.014374922192642664,\n\
\ \"acc_norm\": 0.6313993174061433,\n \"acc_norm_stderr\": 0.014097810678042203\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6677952599083847,\n\
\ \"acc_stderr\": 0.0047004138249425636,\n \"acc_norm\": 0.8488348934475204,\n\
\ \"acc_norm_stderr\": 0.003574776594108505\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.5703703703703704,\n\
\ \"acc_stderr\": 0.042763494943765995,\n \"acc_norm\": 0.5703703703703704,\n\
\ \"acc_norm_stderr\": 0.042763494943765995\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.625,\n \"acc_stderr\": 0.039397364351956274,\n \
\ \"acc_norm\": 0.625,\n \"acc_norm_stderr\": 0.039397364351956274\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.6,\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\": 0.6716981132075471,\n \"acc_stderr\": 0.02890159361241178,\n\
\ \"acc_norm\": 0.6716981132075471,\n \"acc_norm_stderr\": 0.02890159361241178\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\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \
\ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\
\ \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.53,\n\
\ \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.53,\n \
\ \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.5895953757225434,\n\
\ \"acc_stderr\": 0.037507570448955356,\n \"acc_norm\": 0.5895953757225434,\n\
\ \"acc_norm_stderr\": 0.037507570448955356\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4215686274509804,\n \"acc_stderr\": 0.04913595201274498,\n\
\ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.04913595201274498\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\
\ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5319148936170213,\n \"acc_stderr\": 0.03261936918467382,\n\
\ \"acc_norm\": 0.5319148936170213,\n \"acc_norm_stderr\": 0.03261936918467382\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.40350877192982454,\n\
\ \"acc_stderr\": 0.04615186962583703,\n \"acc_norm\": 0.40350877192982454,\n\
\ \"acc_norm_stderr\": 0.04615186962583703\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\"\
: 0.36772486772486773,\n \"acc_stderr\": 0.024833839825562413,\n \"\
acc_norm\": 0.36772486772486773,\n \"acc_norm_stderr\": 0.024833839825562413\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\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \
\ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\
\ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.632258064516129,\n\
\ \"acc_stderr\": 0.02743086657997347,\n \"acc_norm\": 0.632258064516129,\n\
\ \"acc_norm_stderr\": 0.02743086657997347\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n\
\ \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.65,\n \"acc_stderr\": 0.047937248544110196,\n \"acc_norm\"\
: 0.65,\n \"acc_norm_stderr\": 0.047937248544110196\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\"\
: 0.7626262626262627,\n \"acc_stderr\": 0.030313710538198896,\n \"\
acc_norm\": 0.7626262626262627,\n \"acc_norm_stderr\": 0.030313710538198896\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8549222797927462,\n \"acc_stderr\": 0.025416343096306443,\n\
\ \"acc_norm\": 0.8549222797927462,\n \"acc_norm_stderr\": 0.025416343096306443\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.5564102564102564,\n \"acc_stderr\": 0.025189149894764205,\n\
\ \"acc_norm\": 0.5564102564102564,\n \"acc_norm_stderr\": 0.025189149894764205\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.3,\n \"acc_stderr\": 0.027940457136228395,\n \"acc_norm\"\
: 0.3,\n \"acc_norm_stderr\": 0.027940457136228395\n },\n \"harness|hendrycksTest-high_school_microeconomics|5\"\
: {\n \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121626,\n\
\ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121626\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"\
acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\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\"\
: 0.4444444444444444,\n \"acc_stderr\": 0.03388857118502326,\n \"\
acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.03388857118502326\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.7647058823529411,\n \"acc_stderr\": 0.029771775228145624,\n \"\
acc_norm\": 0.7647058823529411,\n \"acc_norm_stderr\": 0.029771775228145624\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7552742616033755,\n \"acc_stderr\": 0.027985699387036423,\n \
\ \"acc_norm\": 0.7552742616033755,\n \"acc_norm_stderr\": 0.027985699387036423\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6188340807174888,\n\
\ \"acc_stderr\": 0.03259625118416827,\n \"acc_norm\": 0.6188340807174888,\n\
\ \"acc_norm_stderr\": 0.03259625118416827\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7404580152671756,\n \"acc_stderr\": 0.03844876139785271,\n\
\ \"acc_norm\": 0.7404580152671756,\n \"acc_norm_stderr\": 0.03844876139785271\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8099173553719008,\n \"acc_stderr\": 0.03581796951709282,\n \"\
acc_norm\": 0.8099173553719008,\n \"acc_norm_stderr\": 0.03581796951709282\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7407407407407407,\n\
\ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.7407407407407407,\n\
\ \"acc_norm_stderr\": 0.042365112580946336\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\": 0.44642857142857145,\n\
\ \"acc_stderr\": 0.047184714852195886,\n \"acc_norm\": 0.44642857142857145,\n\
\ \"acc_norm_stderr\": 0.047184714852195886\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\
\ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8632478632478633,\n\
\ \"acc_stderr\": 0.022509033937077785,\n \"acc_norm\": 0.8632478632478633,\n\
\ \"acc_norm_stderr\": 0.022509033937077785\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \
\ \"acc_norm\": 0.67,\n \"acc_norm_stderr\": 0.04725815626252609\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7803320561941252,\n\
\ \"acc_stderr\": 0.014805384478371153,\n \"acc_norm\": 0.7803320561941252,\n\
\ \"acc_norm_stderr\": 0.014805384478371153\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.6965317919075145,\n \"acc_stderr\": 0.024752411960917205,\n\
\ \"acc_norm\": 0.6965317919075145,\n \"acc_norm_stderr\": 0.024752411960917205\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.311731843575419,\n\
\ \"acc_stderr\": 0.015491756531894637,\n \"acc_norm\": 0.311731843575419,\n\
\ \"acc_norm_stderr\": 0.015491756531894637\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.6862745098039216,\n \"acc_stderr\": 0.026568921015457138,\n\
\ \"acc_norm\": 0.6862745098039216,\n \"acc_norm_stderr\": 0.026568921015457138\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7041800643086816,\n\
\ \"acc_stderr\": 0.025922371788818777,\n \"acc_norm\": 0.7041800643086816,\n\
\ \"acc_norm_stderr\": 0.025922371788818777\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7006172839506173,\n \"acc_stderr\": 0.02548311560119546,\n\
\ \"acc_norm\": 0.7006172839506173,\n \"acc_norm_stderr\": 0.02548311560119546\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.450354609929078,\n \"acc_stderr\": 0.029680105565029036,\n \
\ \"acc_norm\": 0.450354609929078,\n \"acc_norm_stderr\": 0.029680105565029036\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4348109517601043,\n\
\ \"acc_stderr\": 0.012661233805616302,\n \"acc_norm\": 0.4348109517601043,\n\
\ \"acc_norm_stderr\": 0.012661233805616302\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6176470588235294,\n \"acc_stderr\": 0.02952009569768776,\n\
\ \"acc_norm\": 0.6176470588235294,\n \"acc_norm_stderr\": 0.02952009569768776\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.630718954248366,\n \"acc_stderr\": 0.019524316744866353,\n \
\ \"acc_norm\": 0.630718954248366,\n \"acc_norm_stderr\": 0.019524316744866353\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7090909090909091,\n\
\ \"acc_stderr\": 0.04350271442923243,\n \"acc_norm\": 0.7090909090909091,\n\
\ \"acc_norm_stderr\": 0.04350271442923243\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7061224489795919,\n \"acc_stderr\": 0.02916273841024977,\n\
\ \"acc_norm\": 0.7061224489795919,\n \"acc_norm_stderr\": 0.02916273841024977\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7313432835820896,\n\
\ \"acc_stderr\": 0.03134328358208954,\n \"acc_norm\": 0.7313432835820896,\n\
\ \"acc_norm_stderr\": 0.03134328358208954\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \
\ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4939759036144578,\n\
\ \"acc_stderr\": 0.03892212195333047,\n \"acc_norm\": 0.4939759036144578,\n\
\ \"acc_norm_stderr\": 0.03892212195333047\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\
\ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5275397796817626,\n\
\ \"mc1_stderr\": 0.01747693019071219,\n \"mc2\": 0.6825629969752945,\n\
\ \"mc2_stderr\": 0.015176655501749976\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7719021310181531,\n \"acc_stderr\": 0.011793015817663597\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.400303260045489,\n \
\ \"acc_stderr\": 0.013495926436566438\n }\n}\n```"
repo_url: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-50.599841.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-50.599841.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-50.599841.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-50.599841.parquet'
- config_name: results
data_files:
- split: 2023_12_12T03_37_50.599841
path:
- results_2023-12-12T03-37-50.599841.parquet
- split: latest
path:
- results_2023-12-12T03-37-50.599841.parquet
---
# Dataset Card for Evaluation run of mistralai/Mistral-7B-Instruct-v0.2
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-12T03:37:50.599841](https://huggingface.co/datasets/open-llm-leaderboard/details_mistralai__Mistral-7B-Instruct-v0.2/blob/main/results_2023-12-12T03-37-50.599841.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": 0.6077550413417533,
"acc_stderr": 0.03310328786623656,
"acc_norm": 0.6122661125091963,
"acc_norm_stderr": 0.03377303167526721,
"mc1": 0.5275397796817626,
"mc1_stderr": 0.01747693019071219,
"mc2": 0.6825629969752945,
"mc2_stderr": 0.015176655501749976
},
"harness|arc:challenge|25": {
"acc": 0.5895904436860068,
"acc_stderr": 0.014374922192642664,
"acc_norm": 0.6313993174061433,
"acc_norm_stderr": 0.014097810678042203
},
"harness|hellaswag|10": {
"acc": 0.6677952599083847,
"acc_stderr": 0.0047004138249425636,
"acc_norm": 0.8488348934475204,
"acc_norm_stderr": 0.003574776594108505
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.5703703703703704,
"acc_stderr": 0.042763494943765995,
"acc_norm": 0.5703703703703704,
"acc_norm_stderr": 0.042763494943765995
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.625,
"acc_stderr": 0.039397364351956274,
"acc_norm": 0.625,
"acc_norm_stderr": 0.039397364351956274
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```
## Dataset Details
### Dataset Description
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[More Information Needed] | [
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open-llm-leaderboard/details_wang7776__Llama-2-7b-chat-hf-30-sparsity | open-llm-leaderboard | 2023-12-12T03:41:40Z | 0 | 0 | [
"region:us"
] | null | 2023-12-12T03:40:53Z | ---
pretty_name: Evaluation run of wang7776/Llama-2-7b-chat-hf-30-sparsity
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [wang7776/Llama-2-7b-chat-hf-30-sparsity](https://huggingface.co/wang7776/Llama-2-7b-chat-hf-30-sparsity)\
\ 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_wang7776__Llama-2-7b-chat-hf-30-sparsity\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-12T03:37:48.728667](https://huggingface.co/datasets/open-llm-leaderboard/details_wang7776__Llama-2-7b-chat-hf-30-sparsity/blob/main/results_2023-12-12T03-37-48.728667.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\": 0.45732892704529104,\n\
\ \"acc_stderr\": 0.03428010617513505,\n \"acc_norm\": 0.4621141078743541,\n\
\ \"acc_norm_stderr\": 0.035035452136234484,\n \"mc1\": 0.2913096695226438,\n\
\ \"mc1_stderr\": 0.015905987048184828,\n \"mc2\": 0.4482303614832581,\n\
\ \"mc2_stderr\": 0.01566475317876804\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.4786689419795222,\n \"acc_stderr\": 0.014598087973127108,\n\
\ \"acc_norm\": 0.5247440273037542,\n \"acc_norm_stderr\": 0.014593487694937742\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5774746066520613,\n\
\ \"acc_stderr\": 0.004929517011508224,\n \"acc_norm\": 0.7657837084246166,\n\
\ \"acc_norm_stderr\": 0.0042264246245106935\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.04605661864718381,\n \
\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.04605661864718381\n },\n\
\ \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4074074074074074,\n\
\ \"acc_stderr\": 0.042446332383532286,\n \"acc_norm\": 0.4074074074074074,\n\
\ \"acc_norm_stderr\": 0.042446332383532286\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.48026315789473684,\n \"acc_stderr\": 0.040657710025626036,\n\
\ \"acc_norm\": 0.48026315789473684,\n \"acc_norm_stderr\": 0.040657710025626036\n\
\ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\
: {\n \"acc\": 0.4830188679245283,\n \"acc_stderr\": 0.030755120364119898,\n\
\ \"acc_norm\": 0.4830188679245283,\n \"acc_norm_stderr\": 0.030755120364119898\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5069444444444444,\n\
\ \"acc_stderr\": 0.04180806750294938,\n \"acc_norm\": 0.5069444444444444,\n\
\ \"acc_norm_stderr\": 0.04180806750294938\n },\n \"harness|hendrycksTest-college_chemistry|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-college_computer_science|5\": {\n \"\
acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\"\
: 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621505,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621505\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3699421965317919,\n\
\ \"acc_stderr\": 0.036812296333943194,\n \"acc_norm\": 0.3699421965317919,\n\
\ \"acc_norm_stderr\": 0.036812296333943194\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.19607843137254902,\n \"acc_stderr\": 0.039505818611799616,\n\
\ \"acc_norm\": 0.19607843137254902,\n \"acc_norm_stderr\": 0.039505818611799616\n\
\ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\
: {\n \"acc\": 0.37872340425531914,\n \"acc_stderr\": 0.03170995606040655,\n\
\ \"acc_norm\": 0.37872340425531914,\n \"acc_norm_stderr\": 0.03170995606040655\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.32456140350877194,\n\
\ \"acc_stderr\": 0.044045561573747664,\n \"acc_norm\": 0.32456140350877194,\n\
\ \"acc_norm_stderr\": 0.044045561573747664\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\"\
: 0.25925925925925924,\n \"acc_stderr\": 0.022569897074918424,\n \"\
acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.022569897074918424\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.23015873015873015,\n\
\ \"acc_stderr\": 0.03764950879790604,\n \"acc_norm\": 0.23015873015873015,\n\
\ \"acc_norm_stderr\": 0.03764950879790604\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.5225806451612903,\n\
\ \"acc_stderr\": 0.02841498501970786,\n \"acc_norm\": 0.5225806451612903,\n\
\ \"acc_norm_stderr\": 0.02841498501970786\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.3399014778325123,\n \"acc_stderr\": 0.033327690684107895,\n\
\ \"acc_norm\": 0.3399014778325123,\n \"acc_norm_stderr\": 0.033327690684107895\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.41,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\
: 0.41,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.593939393939394,\n \"acc_stderr\": 0.03834816355401181,\n\
\ \"acc_norm\": 0.593939393939394,\n \"acc_norm_stderr\": 0.03834816355401181\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.5959595959595959,\n \"acc_stderr\": 0.03496130972056129,\n \"\
acc_norm\": 0.5959595959595959,\n \"acc_norm_stderr\": 0.03496130972056129\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.6683937823834197,\n \"acc_stderr\": 0.03397636541089118,\n\
\ \"acc_norm\": 0.6683937823834197,\n \"acc_norm_stderr\": 0.03397636541089118\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.38461538461538464,\n \"acc_stderr\": 0.024666744915187222,\n\
\ \"acc_norm\": 0.38461538461538464,\n \"acc_norm_stderr\": 0.024666744915187222\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.25925925925925924,\n \"acc_stderr\": 0.026719240783712177,\n \
\ \"acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.026719240783712177\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.4117647058823529,\n \"acc_stderr\": 0.03196876989195778,\n \
\ \"acc_norm\": 0.4117647058823529,\n \"acc_norm_stderr\": 0.03196876989195778\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2913907284768212,\n \"acc_stderr\": 0.03710185726119995,\n \"\
acc_norm\": 0.2913907284768212,\n \"acc_norm_stderr\": 0.03710185726119995\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.6440366972477064,\n \"acc_stderr\": 0.020528559278244214,\n \"\
acc_norm\": 0.6440366972477064,\n \"acc_norm_stderr\": 0.020528559278244214\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.2638888888888889,\n \"acc_stderr\": 0.030058202704309846,\n \"\
acc_norm\": 0.2638888888888889,\n \"acc_norm_stderr\": 0.030058202704309846\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.6372549019607843,\n \"acc_stderr\": 0.03374499356319355,\n \"\
acc_norm\": 0.6372549019607843,\n \"acc_norm_stderr\": 0.03374499356319355\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.6160337552742616,\n \"acc_stderr\": 0.031658678064106674,\n \
\ \"acc_norm\": 0.6160337552742616,\n \"acc_norm_stderr\": 0.031658678064106674\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5426008968609866,\n\
\ \"acc_stderr\": 0.03343577705583065,\n \"acc_norm\": 0.5426008968609866,\n\
\ \"acc_norm_stderr\": 0.03343577705583065\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.48091603053435117,\n \"acc_stderr\": 0.04382094705550989,\n\
\ \"acc_norm\": 0.48091603053435117,\n \"acc_norm_stderr\": 0.04382094705550989\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.628099173553719,\n \"acc_stderr\": 0.04412015806624504,\n \"acc_norm\"\
: 0.628099173553719,\n \"acc_norm_stderr\": 0.04412015806624504\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5462962962962963,\n\
\ \"acc_stderr\": 0.04812917324536823,\n \"acc_norm\": 0.5462962962962963,\n\
\ \"acc_norm_stderr\": 0.04812917324536823\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.49079754601226994,\n \"acc_stderr\": 0.03927705600787443,\n\
\ \"acc_norm\": 0.49079754601226994,\n \"acc_norm_stderr\": 0.03927705600787443\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3482142857142857,\n\
\ \"acc_stderr\": 0.04521829902833586,\n \"acc_norm\": 0.3482142857142857,\n\
\ \"acc_norm_stderr\": 0.04521829902833586\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.6407766990291263,\n \"acc_stderr\": 0.047504583990416946,\n\
\ \"acc_norm\": 0.6407766990291263,\n \"acc_norm_stderr\": 0.047504583990416946\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6965811965811965,\n\
\ \"acc_stderr\": 0.030118210106942638,\n \"acc_norm\": 0.6965811965811965,\n\
\ \"acc_norm_stderr\": 0.030118210106942638\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.6360153256704981,\n\
\ \"acc_stderr\": 0.017205684809032232,\n \"acc_norm\": 0.6360153256704981,\n\
\ \"acc_norm_stderr\": 0.017205684809032232\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.4797687861271676,\n \"acc_stderr\": 0.026897049996382868,\n\
\ \"acc_norm\": 0.4797687861271676,\n \"acc_norm_stderr\": 0.026897049996382868\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2446927374301676,\n\
\ \"acc_stderr\": 0.014378169884098405,\n \"acc_norm\": 0.2446927374301676,\n\
\ \"acc_norm_stderr\": 0.014378169884098405\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.4738562091503268,\n \"acc_stderr\": 0.028590752958852394,\n\
\ \"acc_norm\": 0.4738562091503268,\n \"acc_norm_stderr\": 0.028590752958852394\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5466237942122186,\n\
\ \"acc_stderr\": 0.02827435985489425,\n \"acc_norm\": 0.5466237942122186,\n\
\ \"acc_norm_stderr\": 0.02827435985489425\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.5308641975308642,\n \"acc_stderr\": 0.02776768960683392,\n\
\ \"acc_norm\": 0.5308641975308642,\n \"acc_norm_stderr\": 0.02776768960683392\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.35106382978723405,\n \"acc_stderr\": 0.02847350127296376,\n \
\ \"acc_norm\": 0.35106382978723405,\n \"acc_norm_stderr\": 0.02847350127296376\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.34159061277705344,\n\
\ \"acc_stderr\": 0.012112391320842854,\n \"acc_norm\": 0.34159061277705344,\n\
\ \"acc_norm_stderr\": 0.012112391320842854\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.3713235294117647,\n \"acc_stderr\": 0.02934980313976587,\n\
\ \"acc_norm\": 0.3713235294117647,\n \"acc_norm_stderr\": 0.02934980313976587\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.43790849673202614,\n \"acc_stderr\": 0.020071257886886525,\n \
\ \"acc_norm\": 0.43790849673202614,\n \"acc_norm_stderr\": 0.020071257886886525\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.4727272727272727,\n\
\ \"acc_stderr\": 0.04782001791380063,\n \"acc_norm\": 0.4727272727272727,\n\
\ \"acc_norm_stderr\": 0.04782001791380063\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.46530612244897956,\n \"acc_stderr\": 0.031932070244253145,\n\
\ \"acc_norm\": 0.46530612244897956,\n \"acc_norm_stderr\": 0.031932070244253145\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6417910447761194,\n\
\ \"acc_stderr\": 0.03390393042268814,\n \"acc_norm\": 0.6417910447761194,\n\
\ \"acc_norm_stderr\": 0.03390393042268814\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.4457831325301205,\n\
\ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.4457831325301205,\n\
\ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.6900584795321637,\n \"acc_stderr\": 0.035469769593931624,\n\
\ \"acc_norm\": 0.6900584795321637,\n \"acc_norm_stderr\": 0.035469769593931624\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2913096695226438,\n\
\ \"mc1_stderr\": 0.015905987048184828,\n \"mc2\": 0.4482303614832581,\n\
\ \"mc2_stderr\": 0.01566475317876804\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6961325966850829,\n \"acc_stderr\": 0.01292620947548357\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.17058377558756635,\n \
\ \"acc_stderr\": 0.010360898504733311\n }\n}\n```"
repo_url: https://huggingface.co/wang7776/Llama-2-7b-chat-hf-30-sparsity
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: [email protected]
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-48.728667.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-12T03-37-48.728667.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-48.728667.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-12T03-37-48.728667.parquet'
- config_name: results
data_files:
- split: 2023_12_12T03_37_48.728667
path:
- results_2023-12-12T03-37-48.728667.parquet
- split: latest
path:
- results_2023-12-12T03-37-48.728667.parquet
---
# Dataset Card for Evaluation run of wang7776/Llama-2-7b-chat-hf-30-sparsity
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [wang7776/Llama-2-7b-chat-hf-30-sparsity](https://huggingface.co/wang7776/Llama-2-7b-chat-hf-30-sparsity) 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_wang7776__Llama-2-7b-chat-hf-30-sparsity",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-12T03:37:48.728667](https://huggingface.co/datasets/open-llm-leaderboard/details_wang7776__Llama-2-7b-chat-hf-30-sparsity/blob/main/results_2023-12-12T03-37-48.728667.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": 0.45732892704529104,
"acc_stderr": 0.03428010617513505,
"acc_norm": 0.4621141078743541,
"acc_norm_stderr": 0.035035452136234484,
"mc1": 0.2913096695226438,
"mc1_stderr": 0.015905987048184828,
"mc2": 0.4482303614832581,
"mc2_stderr": 0.01566475317876804
},
"harness|arc:challenge|25": {
"acc": 0.4786689419795222,
"acc_stderr": 0.014598087973127108,
"acc_norm": 0.5247440273037542,
"acc_norm_stderr": 0.014593487694937742
},
"harness|hellaswag|10": {
"acc": 0.5774746066520613,
"acc_stderr": 0.004929517011508224,
"acc_norm": 0.7657837084246166,
"acc_norm_stderr": 0.0042264246245106935
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.3,
"acc_stderr": 0.04605661864718381,
"acc_norm": 0.3,
"acc_norm_stderr": 0.04605661864718381
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.4074074074074074,
"acc_stderr": 0.042446332383532286,
"acc_norm": 0.4074074074074074,
"acc_norm_stderr": 0.042446332383532286
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.48026315789473684,
"acc_stderr": 0.040657710025626036,
"acc_norm": 0.48026315789473684,
"acc_norm_stderr": 0.040657710025626036
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.43,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.4830188679245283,
"acc_stderr": 0.030755120364119898,
"acc_norm": 0.4830188679245283,
"acc_norm_stderr": 0.030755120364119898
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.5069444444444444,
"acc_stderr": 0.04180806750294938,
"acc_norm": 0.5069444444444444,
"acc_norm_stderr": 0.04180806750294938
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.29,
"acc_stderr": 0.045604802157206845,
"acc_norm": 0.29,
"acc_norm_stderr": 0.045604802157206845
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.37,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.37,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.32,
"acc_stderr": 0.04688261722621505,
"acc_norm": 0.32,
"acc_norm_stderr": 0.04688261722621505
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.3699421965317919,
"acc_stderr": 0.036812296333943194,
"acc_norm": 0.3699421965317919,
"acc_norm_stderr": 0.036812296333943194
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.19607843137254902,
"acc_stderr": 0.039505818611799616,
"acc_norm": 0.19607843137254902,
"acc_norm_stderr": 0.039505818611799616
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.52,
"acc_stderr": 0.050211673156867795,
"acc_norm": 0.52,
"acc_norm_stderr": 0.050211673156867795
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.37872340425531914,
"acc_stderr": 0.03170995606040655,
"acc_norm": 0.37872340425531914,
"acc_norm_stderr": 0.03170995606040655
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.32456140350877194,
"acc_stderr": 0.044045561573747664,
"acc_norm": 0.32456140350877194,
"acc_norm_stderr": 0.044045561573747664
},
"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": 0.25925925925925924,
"acc_stderr": 0.022569897074918424,
"acc_norm": 0.25925925925925924,
"acc_norm_stderr": 0.022569897074918424
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.23015873015873015,
"acc_stderr": 0.03764950879790604,
"acc_norm": 0.23015873015873015,
"acc_norm_stderr": 0.03764950879790604
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.34,
"acc_stderr": 0.04760952285695235,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695235
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.5225806451612903,
"acc_stderr": 0.02841498501970786,
"acc_norm": 0.5225806451612903,
"acc_norm_stderr": 0.02841498501970786
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.3399014778325123,
"acc_stderr": 0.033327690684107895,
"acc_norm": 0.3399014778325123,
"acc_norm_stderr": 0.033327690684107895
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.41,
"acc_stderr": 0.04943110704237102,
"acc_norm": 0.41,
"acc_norm_stderr": 0.04943110704237102
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.593939393939394,
"acc_stderr": 0.03834816355401181,
"acc_norm": 0.593939393939394,
"acc_norm_stderr": 0.03834816355401181
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.5959595959595959,
"acc_stderr": 0.03496130972056129,
"acc_norm": 0.5959595959595959,
"acc_norm_stderr": 0.03496130972056129
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.6683937823834197,
"acc_stderr": 0.03397636541089118,
"acc_norm": 0.6683937823834197,
"acc_norm_stderr": 0.03397636541089118
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.38461538461538464,
"acc_stderr": 0.024666744915187222,
"acc_norm": 0.38461538461538464,
"acc_norm_stderr": 0.024666744915187222
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.25925925925925924,
"acc_stderr": 0.026719240783712177,
"acc_norm": 0.25925925925925924,
"acc_norm_stderr": 0.026719240783712177
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.4117647058823529,
"acc_stderr": 0.03196876989195778,
"acc_norm": 0.4117647058823529,
"acc_norm_stderr": 0.03196876989195778
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.2913907284768212,
"acc_stderr": 0.03710185726119995,
"acc_norm": 0.2913907284768212,
"acc_norm_stderr": 0.03710185726119995
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.6440366972477064,
"acc_stderr": 0.020528559278244214,
"acc_norm": 0.6440366972477064,
"acc_norm_stderr": 0.020528559278244214
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.2638888888888889,
"acc_stderr": 0.030058202704309846,
"acc_norm": 0.2638888888888889,
"acc_norm_stderr": 0.030058202704309846
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.6372549019607843,
"acc_stderr": 0.03374499356319355,
"acc_norm": 0.6372549019607843,
"acc_norm_stderr": 0.03374499356319355
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.6160337552742616,
"acc_stderr": 0.031658678064106674,
"acc_norm": 0.6160337552742616,
"acc_norm_stderr": 0.031658678064106674
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.5426008968609866,
"acc_stderr": 0.03343577705583065,
"acc_norm": 0.5426008968609866,
"acc_norm_stderr": 0.03343577705583065
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.48091603053435117,
"acc_stderr": 0.04382094705550989,
"acc_norm": 0.48091603053435117,
"acc_norm_stderr": 0.04382094705550989
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.628099173553719,
"acc_stderr": 0.04412015806624504,
"acc_norm": 0.628099173553719,
"acc_norm_stderr": 0.04412015806624504
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.5462962962962963,
"acc_stderr": 0.04812917324536823,
"acc_norm": 0.5462962962962963,
"acc_norm_stderr": 0.04812917324536823
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.49079754601226994,
"acc_stderr": 0.03927705600787443,
"acc_norm": 0.49079754601226994,
"acc_norm_stderr": 0.03927705600787443
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.3482142857142857,
"acc_stderr": 0.04521829902833586,
"acc_norm": 0.3482142857142857,
"acc_norm_stderr": 0.04521829902833586
},
"harness|hendrycksTest-management|5": {
"acc": 0.6407766990291263,
"acc_stderr": 0.047504583990416946,
"acc_norm": 0.6407766990291263,
"acc_norm_stderr": 0.047504583990416946
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.6965811965811965,
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```
## Dataset Details
### Dataset Description
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[More Information Needed] | [
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